Keywords: Integrated control and diagnostics, Signal processing, Soft computing
Abstract: To improve the recognition accuracy of the weld and weld detect in the pipeline inspection, an identification method based on least squares twin support vector machine (LSTSVM) is proposed. The magnetic flux leakage (MFL) signal features are extracted according to the fluctuation and shape features, which are input into LSTSVM, LSTSVM to recognize weld, weld detect, detect and normal condition. Particle swarm optimization is used to optimize the penalty parameters and kernel parameters of LSTSVM to achieve high identification accuracy. The experimental results show that the recognition accuracy of the proposed method is 98.7%, which is higher than those of back propagation neural network, support vector machine and LSTSVM.

Keywords: Neural networks, Energy efficient systems, Distributed systems
Abstract: In recent years, cloud computing and big data services are widely adopted by large-scale enterprises. The energy consumption of cloud data centers (CDCs) has also increased dramatically. To effectively reduce the harm on the environment, a growing number of CDCs consider renewable energy instead of fossil energy, and concentrate on reducing idle time of servers by forecasting short-term workload demands for proactively provisioning computational resources and balancing server load in advance. However, due to temporal fluctuation in workload demands and renewable energy, it is a huge challenge to precisely predict their short-term trends. This work adopts basic methods in the field of signal processing and proposes a time series prediction method based on multi-scale wavelet transformation. Extensive experiments based on real-life datasets demonstrate that the proposed method achieves higher accuracy than several typical baseline methods.

Keywords: Modelling and simulation, Renewable energy and sustainability
Abstract: In recent years, advances in IT technology affects a plethora of sectors such as environmental monitoring and management. Open source web map based Geographic Information Systems (GIS) offer a significant advantage in monitoring and representation for many environmental parameters. Here a WebGIS platform based on OpenLayers is presented that displays a set of environmental parameters using novel techniques such as schematic-color methods and 2D arrays. OpenLayers is an open source web maps development tool for WebGIS client that it is characterized by small size and powerful functionality compared with commercial WebGIS software. The data is derived from a set of environmental stations that have been placed in 2 case study areas, in the Port of Igoumenitsa (Greece). The stations transmit data using MQTT protocol that provides convenience and security in data communication. The data is displayed on the platform via a heatmap and color schemes as well as through a 2D array and it can provide both historical and future data. It is noted that the proposed platform is adaptable to making modifications and expansions such as adding new environmental variables for viewing or adding new stations and case study areas by using configuration files that requires minimal programmable skills.

Keywords: Process control, Feedback stabilization, Optimisation
Abstract: This paper deals with the FeedBack/ FeedForward (FB/FF) control of a gantry crane system. To speed-up the payload transition while minimizing its oscillations, a new 2DoF control architecture is proposed. The main novelties are: 1) the FF control action is given by the optimally weighed sum of the two contributions due to FF Plant Inversion a (FFPI) and FF Closed Loop Inversion (FFCLI) control schemes which can be recovered as particular cases; 2) the FF control input is the result of a ''worst case'' optimization problem.

Keywords: Process control, Energy efficient systems, Modelling and simulation
Abstract: Two main approaches to optimisation of load allocation for a system of compressors working in parallel rely on either minimisation of power or maximisation of efficiency. This paper shows that the two approaches are not equivalent. An example with two compressors confirms that the two approaches do not give the same solution.

Keywords: Modelling and simulation, Process control, Intelligent control systems
Abstract: In this paper, the experimental data-based procedure for design and adaptation of robust feeding profiles for recombinant E.coli fed-batch cultivation processes has been proposed. In the first step of the procedure, a maximum glucose consumption rate in biomass growth and target protein production phases must be determined using data from an unlimited growth cultivation. Afterwards, various scenarios for glucose feeding rate need to be designed by setting different levels of glucose consumption rate limitation during the cultivation process. Then the procedure includes the realization of these planned cultivation experiments. The experiments provide the opportunity to select robust and efficient glucose feeding profiles, which then are recommended for implementation in recombinant protein production processes. The proposed procedure also includes a method for adaptation of the designed feeding profile for the case when the process disturbances are significant and glucose begins to accumulate unpredictably in the cultivation medium. The proposed procedure has been tested in simulation studies using the "virtual bioreactor" approach. The simulation tests have shown the efficiency of the proposed procedure. For the realization of the proposed procedure, a required software has been developed and is being prepared for implementation in industrial PLC.

Keywords: Optimisation, Intelligent transportation systems, Multi-agent systems
Abstract: The neat and clean surrounding is the main driving force for any city to be called a smart city. In order to address current societal and business challenges, the objective is to provide a closed loop solution to enable collectionon-demand of wastes by connecting waste data, waste and sorting prediction models, and users/customers with the waste management system. In that context, the focus will be to improve the waste collection process in terms of collection cost, collection time, CO2, customers’ satisfaction, and value added by improving the sorting behavior of the customers. This is of critical importance in accordance with strategic goals 2021-2025 for quality of life, use of resources. Within the overall objective, an important goal that needs to be solved is the collection on demand of the waste and the present paper addresses this by tackling the optimization problem related to the routing.

Keywords: Intelligent transportation systems, Industrial automation, manufacturing, Optimisation
Abstract: The vehicle routing problem is a combinatorial optimization problem of computing routes to serve customers while minimizing a cost function, typically the traveled distance or the number of vehicles required. Industrial applications of the problem in manufacturing plants are the scheduling and routing of Automated Guided Vehicles (AGVs) to deliver material between storage areas and assembly stations. For in-plant transportation it is necessary to take the limited space of the plant floor into account during scheduling and routing in order to limit the number of AGVs that are at certain areas at a given time. In addition, AGVs are most often powered by batteries and therefore have limited operating range and non-negligible charging time that will also affect the scheduling and routing decisions. In this paper we provide a monolithic model formulation for the scheduling and routing of AGVs with given time-windows for delivering material, restricted by capacity constraints on the path network, and with the need for battery recharge. The problem is modelled and solved using optimizing Satisfiability Modulo Theory (SMT) solvers. The approach is evaluated on a set of generated problem instances, showing that the solver can handle medium size instances in a reasonable amount of time.

Keywords: Intelligent transportation systems, Fuzzy logic and fuzzy control
Abstract: The traffic problem is a significant concern for many metropolitans around the world. Controlling the flow of traffic is problematic in terms of many complexities and uncertainties. Despite this situation, this problem needs to be solved as it reduces the productivity and living standards. Modern traffic control methods offer a more effective solution, unlike traditional methods. The regions with the highest traffic density in cities are the regions with many traffic intersections. In this paper, using the Simulation of Urban MObility (SUMO) program, a multi-traffic intersection simulation environment was created by gathering data from a crucial real-life region in Istanbul. Using Fuzzy Logic Control (FLC) and actuated control methods, traffic light controllers are designed for multiple intersections. The results are compared using the data obtained from the designed traffic light control methods and traditional traffic light control methods.

Keywords: Intelligent transportation systems, Cyber-physical systems, Automotive control
Abstract: Longitudinal control for platoons of connected autonomous vehicles is a hot research topic in the Cooperative Intelligent Transport Systems (C-ITSs) domain. Most of the existing results solve the platooning problem asymptotically, without ensuring that the consensus could be achieved in a finite settling time. To this aim, in this work we address the problem of guaranteeing the leader-tracking for heterogeneous vehicles platoons in a fixed time despite the presence of external disturbances. To solve this problem, by exploiting the integral sliding mode (ISM) approach and the Lyapunov theory, we propose a distributed control strategy able to ensure the leader-tracking in a finite settling time which is independent from any vehicles initial conditions. The simulation analysis, carried out in two different driving scenarios, confirms the effectiveness of the theoretical derivation.

Keywords: Intelligent transportation systems, Intelligent control systems
Abstract: Today’s urban mobility requires results for resolving increasingly complex demands on the traffic management system. Hence, the main problem is to achieve a satisfactory level of service for urban motorways as part of the urban traffic network. In addition, with the introduction of Connected and Autonomous Vehicles (CAVs), additional challenges for modern control systems arise. This study focuses on the Variable Speed Limit (VSL) based on Q-Learning with CAVs as actuators in the control loop. The Q-Learning algorithm is combined with the two-step Temporal Difference target to increase the effectiveness of the algorithm for learning the VSL control policy for mixed traffic flows. Different CAV penetration rates are analyzed, and the results are compared with a rule-based VSL and the no control case. The obtained results show that Q-Learning based VSL can learn the control policy and improve the Total Travel Time and Mean Travel Time for different CAV penetration rates. The results are most apparent in the case of low CAV penetration rates. There is also an indication that the increase of the CAV penetration rate reduces the need for separate VSL control.

Keywords: Intelligent transportation systems, Neural networks
Abstract: In the context of autonomous driving, early identification and interpretation of surrounding vehicle’s maneuvers are key elements to ensure a high-level of road safety. In this paper, we present a new concept to classify and predict surrounding vehicle maneuvers on highway using Deep Neural Networks (DNN). This paper also illustrates how this concept can be applied to real-world data gathered in the HighD project. Contrary to other maneuvers classification approaches, the proposed approach consists of dividing the lane change maneuver into three stages: preparation, insertion and adjustment, and identifying each stage by using DNN based model. The model is trained and tested using the HighD dataset, it shows satisfactory performances in classification and anticipation of lane changes.

Keywords: Robotics, Industrial automation, manufacturing, Image processing
Abstract: Real-time control of cooperative robots, or cobots, in industrial environments is a mandatory task to reduce the risk for workers by improving their safety. The task of cobot control always requires input data about the surroundings to enable planning procedures and proper reactions to unpredictable events, such as human actions. In this case, the exact position of the humans can be easily inferred from RGB-D cameras, whose output can be processed by body tracking modules to produce exact pose estimations in real-time. This paper experimentally explores the performance of the affordable Microsoft Azure Kinect RGB-D camera and its body-tracking library. A parametric analysis of the uncertainty of the estimation of the skeleton joints is performed by changing the ambient light conditions, the presence of occlusions, the infrared camera resolution, and the human-camera distance. The output of this investigation proves the need for uncertainty management in the control of cobots working with humans.

Keywords: Robotics, Virtual and augmented reality, Mechatronic systems
Abstract: In the context of Mobile Augmented Reality (MAR), hand-based interaction with virtual environments is still an open challenge. Virtual objects projected on the smartphone screen are on a different layer than the camera-captured images, hence the user’s hand cannot get in contact with virtual entities. In this work, we present an improvement to a previously published proof-of-concept that aims at overcoming current MAR limitations by mapping the hand in the virtual reference. To this end, we developed an ad hoc haptic interface for the finger to provide feedback and track while enhancing wearability. A wrist-worn display compacts the hardware on a single-arm, leaving the other completely free. The overall system is affordable thanks to the use of the smart-phone as core technology and provides “on-demand” augmented reality, tailored for daily activities scenarios. Eighteen users were enrolled to compare the wristband based system and the standard hand-held smartphone montage. Quantitative and qualitative results show that our system was positively received by the subjects, that completed the experimental task achieving similar performance in the two conditions but expressed their preference for the wrist-worn display.

Keywords: Computational methods, Nonlinear systems, Robotics
Abstract: This paper investigates the effects of the numerical method employed to solve the system of differential equations that characterise a closed-loop inverse kinematics (CLIK) algorithm in the discrete-time domain. The paper presents a detailed comparison between a 4th order method, namely the Runge-Kutta 4 (RK4) and the explicit Euler 1-st order method, that is the one most used in the applications. In spite of a lower complexity of the mathematical model, simulations on a 7-Degree-Of-Freedom (DOF) show that using explicit Euler produces better performance in different conditions, e.g., when considering a constant Cartesian reference. On the other hand, significantly lower tracking error is observed for timevarying Cartesian reference when using RK4. This method also generates smoother joint trajectories when moving through a kinematic singularity. Finally, the results suggest that stability of the closed-loop algorithm is retained for larger gain values when using RK4.

Keywords: Multi-agent systems, Formation control, Robotics
Abstract: In this work, we consider the problem of coordinating the motion of a platoon of unicycle robots navigating inside an obstacle-cluttered workspace. We assume that each robot is equipped with on-board sensors that allow it to perceive nearby obstacles and obtain its relative position with respect to its preceding robot. Additionally, no robot other than the leader of the team is able to localize itself within the workspace and no centralized communication network exists, i.e., explicit information exchange between the agents is unavailable. To tackle this problem, we adopt a leader-follower architecture and propose a novel, decentralized control law for each robot-follower, based on the Prescribed Performance Control method, which guarantees collision-free tracking and visual connectivity maintenance by ensuring that each follower maintains its predecessor within its camera field of view while keeping static obstacles out of the line of sight for all times. Finally, we verify the efficacy of the proposed control scheme through simulations.

Keywords: Robotics, Industrial automation, manufacturing, Nonlinear systems
Abstract: In this paper we present a robot for non-destructive visual scanning of an outside shell of the reactor vessel internals. The robot has a total of four degrees of freedom where one of the joints has nonlinear kinematics characteristics due to the construction of the rail-guided joint structure. The problem of solving the nonlinear kinematics of the robot has been addressed by taking the environmental and geometry constraints into account. Kinematics is used to calculate the scan path to cover a specified part of the reactor vessel internals. The described method has been implemented in an user-oriented visualization and control software tool called Fiona, which was tested on a real robot. We demonstrate the effectiveness of the presented method using Fiona in a simulated reactor vessel internals inspection environment.

Keywords: Robotics, Industrial automation, manufacturing
Abstract: A fundamental prerequisite to achieve a successful human-robot cooperation is human safety, which becomes even more crucial when multiple robots are involved in the cooperative task. A general solution for addressing safety in human-multi-robot scenarios is proposed in this paper. Human safety is assessed by a safety field which accounts for the multirobot system as a whole. The assessment of human safety is exploited within an optimization protocol where the robots’ cooperative task trajectory is scaled whenever required, while exploiting the system redundancy. Control Barrier Functions (CBFs) are adopted to set up the optimization problem and kinematic and dynamic constraints are taken into consideration. Finally, simulations on a realistic setup composed of three industrial mobile manipulators show the effectiveness of the proposed solution.

Keywords: Linear systems, Algebraic and geometric methods, Robust control
Abstract: This paper addresses the problem of computing the k-moments of a plant from a finite number of measurements of input-output data. The k-moments are (modulo a simple, one-to-one transformation) the values of the transfer matrix and its derivatives computed at specific frequencies, and are instrumental to solve several problems in identification, model reduction, estimation and control.

The deterministic setting is considered. At the best of the authors knowledge, in comparison with previously published methods for the same setting, the proposed approach is simpler, is not limited to k-moments with k=0, and provides exact evaluations of k-moments based only on a finite number of measurements, whereas most competing methods mostly provide estimates that are only asymptotically correct, or require the complete identification of the plant.

As a simple application, an output tracking problem is considered, and a solution providing deadbeat convergence is proposed.

Keywords: Power systems and smart grid, Robust control, Disturbance rejection
Abstract: This article addresses the design problem of aggressive load frequency controllers which are robust against load disturbances. The controller design is comprised of three components and the design is formulated as a multiobjective LMI optimization problem. The first component places the closed loop poles in a predefined convex LMI region while providing fast transient response and disturbance rejection. The second component implements the required integral action and determines the closed--loop bandwidth, while the third component places a limit on the control energy. H_{infty}/mixed--sensitivity methodologies are employed in a state--space formulation leading to a tuning strategy with an engineering interpretation Simulation studies are offered to illustrate the efficiency of the control design.

Keywords: Robust control, Process control, Time-delay systems
Abstract: Abstract—Holomorphic Dynamical systems is a class of infinite dimensional systems with a infinite number of zeros and no poles. Systems in this class are always BIBO stable with an exact finite settling time for the step response, because they are in feedforward mode, without any inherent feedback physical mechanism. In this paper a precise definition of Holomorphic Dynamical systems is given along with a stability result. Time solutions are also discussed and its control is addressed. This kind of systems are often present in PDE modelling of mass and energy transport phenomena for industrial plant units. Examples and one control application are presented, illustrating the approach described.

Keywords: Fault tolerant control, Aerospace control, Robust control
Abstract: This paper presents a design example of structured H_{infty} control-based passive Fault-Tolerant Flight Control (FTFC) for the longitudinal motion of a research airplane MuPAL-alpha, and also presents the results of Hardware-In-the-Loop Simulation (HILS) tests using the actual MuPAL-alpha. The FTFC comprising PID and feedforward gains is designed using verb|hinfstruct| command implemented in MATLAB^{textregistered} for the linearized longitudinal airplane motion model combined with a Linear Time-Invariant Parameter-Dependent (LTIPD) system representing the modeling errors of the onboard actuator and a Linear Parameter-Varying (LPV) system representing the possible actuator efficiency reduction. As verb|hinfstruct| command cannot handle parameter-dependent systems directly, we adopt two-step design, {it viz.}, we first obtain controller gain candidates which are common for multiple Linear Time-Invariant (LTI) models selected from the combined system comprising the longitudinal motion model, the LTIPD system and the LPV system with specifically fixed parameter values, and we then analyze the actual performance using the combined system via Linear Matrix Inequalities (LMIs) under the supposed parameter variation rate bounds.

Keywords: Fuzzy logic and fuzzy control, Robust control, Nonlinear systems
Abstract: The design of H_infty observer-based controllers for nonlinear systems represented by Takagi–Sugeno models in continuous time is studied here, in the presence of parameter uncertainties and external disturbances. Conditions are developed in terms of Linear Matrix Inequalities (LMIs), thanks to a change of variables to avoid bilinear terms. Thanks to this, observer and controller gains can be deduced in terms of LMIs conditions, which can be practically solved in a single step. The simulation of a four-tank lab system is used to show the advantage of the methodology proposed, revealing a good compromise between the controller simplicity and conservatism, outperforming previous approaches.

Keywords: Robust control, Time-delay systems, Mechatronic systems
Abstract: For systems with order of dynamics higher than two and oscillating loads with low damping, a non-collocation of the sensing and control can deteriorate robustness of the feedback and, in worst case, even bring it to instability. Furthermore, for a contactless sensing of the oscillating mechanical load, like in the system under investigation, the control structure is often restricted to the single proportional feedback only. This paper proposes a novel robust feedback control scheme for a low-damped fourth-order system using solely the measured load displacement. For reference tracking, the loop shaping design relies on a band reject filter, while the plant uncertainties are used as robustness measure for determining the feedback gain. Since prime uncertainties are due to the stiffness of elastic link, correspondingly connecting spring, and due to the gain of actuator transducer, the loop sensitivity function with additive plant variation is used for robustness measure. In order to deal with unknown disturbances, which are inherently exciting the load oscillations independently of the loop shaping performance, an output delay-based compensator is proposed as a second control-degree-of-freedom. That one requires an estimate of the load oscillation frequency only and does not affect the shaped open-loop behavior, correspondingly sensitivity function. An extensive numerical setup of the modeled system, a two-mass oscillator with contactless sensing of the load under gravity and low damping of the connecting spring, is used for the control evaluation and assessment of its robustness.

Keywords: Education and training
Abstract: The lack of consolidated therapeutic protocols to counteract the COVID-19 has drawn attention to the social role of hygiene rules to prevent the escalation of infections. Particular focus has been put on the importance of limiting face-touch occurrences. Given that SARS-CoV-2 transmission can occur by self-inoculation, impeding the virus to reach eyes, nose or mouth is paramount to prevent infections. To deal with this aspect, several methods for estimating hand proximity to face and notifying the user about face-touch occurrences have been developed. In this overview, we present the most relevant, ready-to-use, and large-scale deployable solutions. Most of them consist in applications running on smartwatches/smartphones or relying on wearable accessories, e.g. smartbands. Although the use for the COVID-19 emergency nowadays is the most urgent application, these solutions can be employed in ordinary daily life as simple tools to discourage face-touching, decreasing the probability to get infections from the environment, or as habit reversal therapy.

Keywords: Signal processing, Networked systems
Abstract: COVID-19 and other highly transmissible respiratory infections are considerable challenges to all countries’ health and medical systems. Due to the virus cross-infection and limited medical and healthcare resources, many countries have encountered difficulties in bearing or dealing with this situation. Fortunately, the vast majority of positive patients are asymptomatic or show mild symptoms, so it is necessary to carry out isolation staying home and basically monitor their disease’s progress to detect potential worsening signs promptly. According to the above issues, this work provides an effective solution by proposing a remote telehealth monitoring approach for infected subjects in self-isolation that is based on a multisensor fusion method. In this approach, we use a radar sensor to monitor basic activities and breathing patterns; we also obtain the patient’s blood oxygen saturation and heartbeat information through a smart wrist bracelet. Experimental results show that our method is practical and feasible for monitoring subjects in a self-isolated environment.

Keywords: Assistive technology
Abstract: Urban areas in the European Union (EU) are ageing fast. As part the "Operational Programme for the Implementation of the European Cohesion Policy for the period 2014–2020", some EU member-states have prioritized promoting the availability of affordable, sustainable and high-quality services, including health and social services for old and very old inhabitants. These services include long-term care. The key issue which until now has not been answered is how to develop a quantitative model for measuring the quality of nursing and social care services for the elderly, and how to plan social facilities the elderly that will be available in accordance with the demand. Many EU member states do not have a compact system for the regulation of long-term care. Services and rights arise from the different existing systems—health, pension and disability insurance—as well as from the social welfare system. Given the demographic structure and projections developed by the European Commission and presented in The Ageing Report 2021, there is a need for reform that will enable the establishment of a uniform system of high-quality community-based services for the ageing and for those that will need institution forms of care. Several EU member-states are preparing new legislation in the field of long-term care (LTC), which will have to take into consideration the different types of social facilities where LTC services will be provided. This will require the development of models for projections of needs and eligibility for integrated health and social services, LTC, monitoring of recipients of services and funds for LTC, and coordinating the development of integrated community-based services. In the paper, we review the literature, highlight the gaps and propose future research agenda.

Keywords: Fault tolerant control, Predictive control, Networked systems
Abstract: This paper presents a health-aware Model Predictive Control (MPC) including fault-tolerant capabilities for drinking water transport networks. When a fault has occurred, the predictive controller must be redesigned to deal with the fault. This is done by considering the system reliability that is incorporated into the MPC model. The inclusion of components and system reliability in the MPC model is done through the Linear Parameter Varying (LPV) modelling approach with the aim of maximizing the availability of the system by considering system reliability. As a result, the MPC design is modified by considering the reliability model such that additionally to achieve the best achievable performance after the fault, the controller try to preserve the remaining useful life. The solution to the optimization problem related to the MPC problem is achieved by solving a series of Quadratic Programming (QP) problems thanks to the proposed LPV formulation. The proposed approach is applied to a part of a real drinking water transport network of Barcelona for demonstrating the performance of the method.

Keywords: Wireless sensor networks, Signal processing, Biomedical engineering
Abstract: This paper describes a wearable monitoring system for sEMG and coherent motion data signals that is primarily aimed at real-time tracking of workers' activity for the analysis and prevention of Work-related Musculoskeletal Disorders (WMSDs). The device supports the data recording, real-time streaming, and analysis of up to four 9-axis inertial units and up to 8 independent single-ended surface Electromyography (sEMG) signals. The device has been developed to acquire, elaborate and integrate information related to the arm motion and forces with a minimal encumbrance on the operator's arm. The paper discusses the design of the device and presents a validation of the measuring capabilities of the system.

Keywords: Modelling and simulation, System identification, Systems biology
Abstract: The COVID-19 pandemic is bringing disruptive effects on the healthcare system, economy and social life of countries all over the world. Even though the elder portion of the population is the most severely affected by the coronavirus disease, the counter-measures introduced so far by the governments do not take into account age structure, and the restrictions act uniformly on the population irrespectively of age. In this paper, we introduce a SIRD model with age classes for studying the impact on the epidemic evolution of lockdown policies applied heterogeneously on the different age groups of the population. The proposed model is then applied to COVID-19 data from the state of Tennessee. The simulation results suggest that a selective lockdown, while having a lighter socio-economic impact, may bring benefits in terms of reduction of the mortality rate that are comparable to the ones obtained by a uniform lockdown.

Keywords: Modelling and simulation, Networked systems
Abstract: In this paper, a modeling framework is proposed to represent the dynamic behavior of both passenger and freight flows in a large-scale multi-modal transportation network. It consists of a macroscopic model developed to support decision makers who intend to utilize the full mobility capacity of a geographical area by allocating the mobility demand on different modes (road and rail transport) or by suggesting multi-modal itineraries. In the proposed modeling framework, the passenger demand allocation on a multi-modal transportation network is obtained by defining and solving an appropriate multi-modal assignment problem.

Keywords: Optimisation, Modelling and simulation, Industrial automation, manufacturing
Abstract: This paper addresses the multi-drop container loading problem (CLP), i.e., the problem of packing multiple bins -associated to multiple deliveries to one or more customers- into a finite number of transport units (TUs). Differently from the traditional CLP, the multi-drop CLP has been rarely handled in the literature, while effective algorithms to automatically solve this problem are needed to improve the efficiency and sustainability of internal logistics. To this aim, we propose a novel algorithm that solves a delivery-based mixed integer linear programming formulation of the problem. The algorithm efficiently determines the optimal composition of TUs by minimizing the unused space, while fulfilling a set of geometric and safety constraints, and complying with the delivery allocation. In particular, the proposed algorithm includes two steps: the first aims at clustering bins into groups to be compatibly loaded in various TUs; the latter aims at determining the optimal configuration of each group in the related TU. Finally, the proposed algorithm is applied to several realistic case studies with the aim of testing and analysing its effectiveness in producing stable and compact TU loading configurations in a short computation time, despite the high computational complexity of the multi-drop CLP.

Keywords: Intelligent transportation systems, Optimisation, Industrial automation, manufacturing
Abstract: New technologies, such as Unmanned Aerial Vehicles (UAVs), are transforming facilities and vehicles into intelligent systems that will significantly modify logistic deliveries in any organization. With the appearance of automated vehicles, drones offer multiple new technological solutions that might trigger different delivery networks or boost new delivery services. Differently from the related works, where a single specific delivery system model is typically addressed, this paper deals with the use of UAVs for logistic deliveries focusing on a multi-criteria analysis of trendy drone-based system architectures. In particular, using the cross-efficiency Data Envelopment Analysis approach, a comparative analysis among three different delivery systems is performed: the classic system based on trucks only, the drone-only system using a fleet of drones, and the hybrid truck and drone system combining trucks and drones. The proposed technique constitutes an effective decision-making tool aimed at helping delivery companies in selecting the optimal delivery system architecture according to their specific needs. The effectiveness of the proposed methodology is shown by a simulation analysis based on a realistic data case study that pertains to the main logistic service providers.

Keywords: Intelligent transportation systems, Predictive control, Embedded control systems
Abstract: This paper proposes a Model Predictive Control (MPC) strategy for Connected and Automated Vehicles (CAVs), able to work in intelligent cooperative driving environments and to provide Advanced Driver Assistance Systems (ADAS) at SAE automation level L4 (High Automation). The control strategy is implemented from a vehicle point of view, interfaced with a Smart Road infrastructure in order to: i) receive Cooperative-Intelligent Transportation Systems (C-ITS) services such as dynamic speed limits by Intelligent Speed Assistance (ISA); ii) provide ADAS functionalities such as Adaptive Cruise Control (ACC), Emergency Electronic Brake (EEB) and Lane Keeping System (LKS). The MPC design is based on nonlinear bicycle model for coupled longitudinal-lateral vehicle dynamics, extended with additional information related to an ahead vehicle. The MPC provides wheel torque and steering angle (at the wheels). We used MATLAB/Simulink (R2020b) to develop and verify model and control. The MPC was compiled for STM32 MCU to run Processor In the Loop (PIL) testing on an ST NUCLEO-H743ZI2. PIL provides information about memory usage of MPC and execution time on MCU. The main objective is to verify that the cycle execution time of the MPC is lower than 10 ms, the typical cycle time of CAN messages. The proposed methodology is general and can be applied to any kind of vehicle and for different road conditions.

Keywords: Intelligent transportation systems
Abstract: The increasing diffusion of electric mobility requires specific attention to the end-users expectations as well as to stakeholders roles and needs. New solutions have to be proposed to improve the driving and charging experience using the electric vehicles by providing tailored tools and services. In this context, this paper shows how ICT (Information and Communications Technology) tools can allow the transition towards such a smart and sustainable mobility. Within the European project H2020 ELVITEN, with particular focus on Electric Light-category Vehicles (EL-Vs), a proper set of ICT services are proposed, including the brokering and booking service for vehicles and charging stations, the ICT platform for monitoring the electric vehicle fleets, the serious game app and the incentive management platform. In the project context, it is demonstrated that EL-Vs and related ICT services are suitable means of transport and tools, respectively, to encourage users towards a new mobility that is electric and sustainable.

Keywords: Cyber-physical systems, Modelling and simulation, Optimisation
Abstract: In most countries, Municipal solid waste (MSW) collection and disposal are among the major problems of the urban environment. To this concern, the Key Enabling Technologies of Industry 4.0 (I4.0) play a crucial role. The I4.0 brings the new industrial paradigm in the smart cities, with strong cooperation of the digital and physical worlds through the cyber-physical systems. In particular, the intelligent bins (so-called smart bins) allow monitoring and provide real-time information on their capacity use. If, on the one hand, the MSW collection process is a topic widely investigated in the scientific literature, on the other hand, the studies on the adoption of the smart bins in MSW collection aren't that widespread. A technical-economic assessment of the implementation of the MSW collection based on the dynamic vehicle routing led by smart bins for a southern Italian town is proposed in the present work. The study evaluates the impact on the MSW collection considering the changes in terms of frequency of bins collected and dynamic vehicle routing, given by the residual capacity data provided from smart bins. To this concern, the costs and the emission due to MSW collection are minimized conducting a scenario analysis finalized to identify the proper service level to the citizenship, under municipal regulations, forecasting the residual capacity of each smart bin. Results of the case study showed that the adoption of the smart bins leads to significant benefits in both economic and environmental terms, providing proper service level for citizens.

Keywords: Linear systems, Robotics, Modelling and simulation
Abstract: The main goal of this paper is to estimate the parameters of a DC electric motor using the new estimation method of dynamic expansion of the regressor and mixing (DREM). Input voltage and armature current are assumed to be measured. The position and velocity of the rotor are unmeasured. The parameters under consideration are the motor armature-winding resistance and inductance, back emf constant, motor torque constant, a moment of inertia, and viscous friction. The system output is angular position, armature voltage (system input). Experimental results are presented to demonstrate the application of this approach. In these experiments, the approach was readily implemented and gave more accurate estimates than conventional methods.

Keywords: Biomedical engineering, Mechatronic systems, Robotics
Abstract: This work proposes a novel control methodology to achieve gait symmetry in trans-femoral amputated patients with prostheses. The proposed approach allows to overcome the limits of classical model-based control strategies by introducing a Deep Reinforcement Learning (DRL) method trained ad hoc for generating the velocity control signals fed into the active lower-limb robotic prosthesis. More specifically, the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm is used to concurrently learn a Q-function and the best policy. The proposal has the advantages of being model-free and capable of adapting to different walking velocities, just requiring few measurements and without the need to online re-tune the control parameters when the human motions change. The proposed model-free approach has been tested in a realistic scenario simulated in the CoppeliaSim environment relying on gait patterns retrieved experimentally by means of markers placed on a human subject.

Keywords: Robotics
Abstract: In robot assisted minimally invasive surgery long instruments are inserted inside the patient's body through tiny incisions in the patient's skin. During surgery, it is important to constraint the motion of the instrument not to stress the incision wall to avoid injuring the patient. Hence the incision point is desired to act like a remote center of motion (RCM). The breathing or/and heartbeat function means that the incision point is time-varying. With a general purpose manipulator such desired RCM should be actively imposed by the control function. In this work, we propose a control scheme that achieves this objective for hands-on procedures in which the robot is directly manipulated by the surgeon. The proposed control scheme is proved to satisfy the moving RCM constraint while the controlled robot is passive under the exertion of a human generalized force. Simulation and experimental results are given utilizing a KUKA LWR4+.

Keywords: Robotics, Nonlinear control, Autonomous systems
Abstract: The article addresses the tracking control problem of differentially driven nonholonomic Wheeled Mobile Robots (WMRs) whose nonlinear kinematic-dynamic equations of motion subject to bounded inputs. To overcome the difficulties arising from the constraints in the system and to avoid singular states, the potential for their appearance is common in this system, we implement sigmoid functions in the feedback loop. Also, since the speed variables (linear and angular) that enter the kinematic subsystem are not independent variables and are the result of the action of bounded forces/torques on the dynamic system, we present a special way of reconstructing them. Using the flatness property of the system, the article presents a control algorithm for tracking a time-parameterized path (a geometric path with an associated timing-law). The proposed control scheme allows us to present conditions on the required trajectory that, if they are met, the input signals satisfy the given restrictions and ensures convergence to the reference trajectory.

Keywords: Robotics, Decentralized control, Autonomous systems
Abstract: Despite the recent developments in robotic technology that have introduced robots in various fields of industry, agriculture, service, security, etc., complex applications that involve multiple robots performing a task in physical interaction with humans, require further investigation. Towards this direction, we propose an impedance control scheme for multiple mobile manipulators assisting a human in transporting/manipulating a rigidly grasped object. The human operator plans the object's motion, whereas the robot-team imposes predefined impedance properties on the object to reduce the human effort required to execute the task, without assuming either knowledge of the desired object trajectory or explicit inter-robot communication. Moreover, to achieve the desired impedance properties two novel decentralized estimation schemes are employed to derive the human motion intention and the human exerted wrench. Finally, a simulated paradigm verifies the theoretical findings.

Keywords: Robust control, Aerospace control, Nonlinear control
Abstract: This work addresses the attitude tracking problem of reusable launch vehicle (RLV) in its re-entry phase under limited use of communication resources. The inherent nonlinear dynamics and challenging environmental conditions render the objective of navigating the RLV along a desired path to be a difficult task. In this regard, a time-delay based control (TDC) strategy with input hysteresis quantizer is proposed to achieve robustness against external disturbances and model uncertainties. The TDC approach utilizes input-output data of the immediate past instant for estimating the uncertainties effecting the space shuttle. While, the input quantizer discretizes the continuous TDC command to a finite set of predefined discrete levels. Thus, wireless transmission of control command to the actuator is carried out at a lower rate and obeys the communication constraint. Stability analysis using Lyapunov's method is carried out to demonstrate uniformly ultimately bounded (UUB) convergence of the system states on application of the proposed control scheme. Simulation studies have been included to highlight efficacy of the proposed control scheme in terms of robust tracking of the reference trajectory and control update reduction.

Keywords: System identification, Education and training, Robotics
Abstract: Educational Robotics (ER) is a powerful tool to help students learn school subjects, robotics, and developing cognitive skills and soft skills. Assessing the learning outcomes of ER activities requires the identification of the model that underly the process. Machine learning can be useful to identify such models and to interpret data. This paper aims to present a system that could help integrating Educational Data Mining and Learning Analytics techniques into the open-ended learning environment that characterizes the constructionist approach of ER. Both supervised and unsupervised learning methods could be applied to extract meaningful information. Students’ approaches to learning as well as a prediction of their final performance could inform teachers’ decision and facilitate the implementation of effective ER activities in formal and non formal education. First results show good premises for a future broader implementation, but more research is needed to face all the open issues.

Keywords: Networked systems, Time-delay systems, Cyber-physical systems
Abstract: In this paper, the robust finite-time leader-following consensus problem for homogeneous uncertain linear Multi-Agent Systems (MASs) in the presence of time-varying communication delays is addressed and solved via a distributed time-delay PID-like control strategy. To analytically prove the robust finite-time stability of the resulting delayed neutral-type closed-loop MAS, we leverage both the descriptor transformation and the Lyapunov–Krasovskii theory. Delay-dependent finite-time stability conditions are expressed as a set of Linear Matrix Inequalities (LMIs), whose solutions allows obtaining both the weighted L2 gain and the state trajectories bound. Numerical results confirm the theoretical derivation and the effectiveness of the proposed approach in guaranteeing that each agent converges towards the leader reference behavior in a finite-time interval despite the presence of both time-varying delays and external disturbances.

Keywords: Soft computing, Neural networks, Computational methods
Abstract: Black box functions are often used by machine learning algorithms. These functions do not provide convenient way of analyzing sensitivity of response to input variables. This paper presents Sparse Grid Regression method to be used for converting black box function into a dimension wise expansion model. Such model provides an excellent tool for interpretation and sensitivity analysis. A neural network was used as an example when comparing the novel Sparse Grid Regression method with commonly used quasi Monte Carlo algorithm. A significant advantage in computational efficiency of the proposed Sparse Grid Regression method was observed.

Keywords: Computational intelligence, Fuzzy logic and fuzzy control, Wireless sensor networks
Abstract: Indoor air quality has a critical impact on human and animal health and well-being. Because of the confinement during the Covid-19 health crisis, millions of people were forced to stay at home. Therefore, living environments should incorporate an automated monitoring system to detect unfavorable air quality scenarios. Also, Internet of things (IoT) due to their ability to carry air low-cost sensing units have become a cheap alternative to monitor pollution values in a given area. However, enough still needs to be learned as these types of studies are expected to increase in the future years. In this paper, we have developed an intelligent IoT-fuzzy-based device based on low-cost sensors for indoor air quality monitoring ( IoT-fuzzy-based AQM). It used a type-1 fuzzy inference system to improve the measurement accuracy of the low-cost sensors and to estimate the air quality index. Experiment tests are made in an indoor environment (home), where the obtained results have proved the effectiveness of the realized system.

Keywords: System identification, Time-delay systems, Industrial automation, manufacturing
Abstract: In the industry, due to transport phenomena and non-linearities, high order linear models are often used to fit the process behaviour. In several applications, a first order model with a delay can give a satisfying result when compared to the actual process. This paper focuses on the identification of a continuous time first order plus dead time (FOPDT) process. In this context, identification of process dynamics is important because it enables the process engineer, to quickly design a control strategy that meets customer’s requirements. In this paper an instrumental variable recursive least squares, with a variable forgetting factor (VFF-IVRLS) algorithm is proposed. The online implementation is done by adding robust start and stop conditions. A Schneider PLC is used to apply step tests in order to identify the system response. The robustness of the proposed methodology is discussed and tested with real industrial data. The data is collected by the sensors of the system.

Keywords: Energy efficient systems, Distributed systems, Optimisation
Abstract: Significant changes have occurred all over the world even over the past decade in the energy landscape. Globally, there’s a big push towards a 100% incorporation of wind and solar power for electricity production, with synergistic support from various technologies. For example, in the US, natural gas prices have declined, costs of renewable energy technologies have come down, and large-scale battery energy storage technologies have advanced rapidly. There are however a host of challenges, most of which are due to the intermittency and unpredictability of the renewable energy resources. This talk will focus on some of the solutions for the deep integration of these renewable resources for electricity production that are control centric. A distributed optimization approach that judiciously combines renewable generation with storage and flexible loads has the possibility for ensuring power balances while preserving privacy and ensuring security. A distributed control approach that enables a coordinated network of millions of controllers, all integrated with solar and wind power generation nodes, storage sites, and flexible consumption can lead to effective frequency regulation and voltage control in real‐time. A wholistic and grid-wide integration of devices and systems including IoT devices, microgrids, distribution systems, transmission systems, and markets can lead to a power grid that allows deep decarbonization and ensures reliability and resilience. In this talk, some of these challenges, highlights of the current research in distributed optimization and control, and opportunities for future directions will be discussed. Examples of use cases that illustrate the role of systems and control in renewable‐rich power grids will be presented.

Keywords: Biomedical engineering, Robust control
Abstract: Many countries are adopting a periodic epidemic control strategy to manage the COVID-19 epidemic, switching between lighter (open) and heavier (close) restrictions. We comparatively assess an open-close and a close-open strategy, quantifying the ensuing costs. We show that, while the two strategies have comparable socio-economic costs, the open-close strategy leads to a much heavier burden in terms of deaths and pressure on the healthcare system. Our findings confirm that preemptive approaches are largely preferable, because they lead to improved epidemic control without aggravation of social and economic losses. Procrastination, in the adoption of countermeasures such as lockdown, has a huge, and easily quantifiable, cost in terms of infections, hospitalisations and human lives.

Keywords: Complex systems, Modelling and simulation, Game theory
Abstract: As witnessed throughout the COVID-19 pandemic, the collective response of the population to take up appropriate self-protective behaviors plays a critical role in shaping the outcome of an epidemic outbreak. In this work, we propose a framework to model the collective behavioral response to COVID-19 and to the implementation of non-pharmaceutical interventions (NPIs). Analytical insights and numerical simulations are used to investigate the model and assess the impact of NPIs on the behavioral response and, consequently, their effectiveness in mitigating the outbreak.

Keywords: Multi-agent systems, Modelling and simulation, Networked systems
Abstract: The COVID-19 outbreak has forced most countries to impose new contact-limiting restrictions at workplaces, universities, schools, and more broadly in our societies. Yet, the power and limitations of these unprecedented strategies for containing virus spread within the populations remain unquantified. Here, we develop a simulation study to analyze COVID-19 outbreak magnitudes on three real-life contact networks stemming from a workplace, a primary school and a high school in France. Our study provides the first fine-grained analysis of the impact of contact-limiting strategies at workplaces, schools and high schools, including (1) Rotating, in which workers are evenly split into two shifts that alternate on a daily or weekly basis; and (2) On-Off, where the whole group alternates periods of normal work interactions with complete telecommuting. We model epidemics spread in these different setups using an SEIR transmission model enriched with the coronavirus most salient features: super-spreaders, infectious asymptomatic individuals, and pre-symptomatic infectious periods. Our study yields clear results: the ranking of the strategies based on their ability to mitigate epidemic propagation in the network from a first index case is the same for all network topologies (work place, primary school and high school). Namely, from best to worst: Rotating week-by-week, Rotating day-by-day, On-Off week-by-week, and On-Off day-by-day. Moreover, our results show that when the local reproduction number within the network is below 1.38, all four strategies efficiently control outbreak by decreasing effective local reproduction number under 1. These results can support public health decisions and telecommuting organization.

Keywords: Modelling and simulation, System identification, Nonlinear systems
Abstract: The recent trends of the COVID-19 research have been devoted to disease transmission modeling, with the aim of investigating the effects of different mitigation strategies mainly through scenario-based simulations. In this context we propose a novel non-linear time-varying model that effectively supports policy-makers in predicting and analyzing the dynamics of COVID-19 secondary waves. Specifically, this paper proposes an accurate SIRUCQTHE epidemiological model to get reliable predictions on the pandemic dynamics. Differently from the related literature, in the fitting phase, we make use of the google mobility reports to identify and predict the evolution of the infection rate. The effectiveness of the presented method is tested on the network of Italian regions. First, we describe the Italian epidemiological scenario in the COVID-19 second wave of contagions, showing the raw data available for the Italian scenario and discussing the main assumptions on the system parameters. Then, we present the different steps of the procedure used for the dynamical fitting of the SIRUCQTHE model. Finally, we compare the estimation results with the real data on the COVID-19 secondary waves in Italy. Provided the availability of reliable data to calibrate the model in heterogeneous scenarios, the proposed approach can be easily extended to cope with other scenarios.

Keywords: Networked systems, Modelling and simulation, Decentralized control
Abstract: This work examines a discrete-time networked SIR (susceptible-infected-recovered) epidemic model, where the graph, infection, and recovery parameters may be time-varying. We provide a sufficient condition for the SIR model to converge to the set of healthy states exponentially. We propose a stochastic framework to estimate the system states from observed testing data and provide an analytic expression for the error of the estimation algorithm. Employing the estimated system states, we provide a novel eradication strategy that guarantees at least exponential convergence to the set of healthy states. We illustrate the results via simulations over northern Indiana, USA.

Keywords: Complex systems, Networked systems, Modelling and simulation
Abstract: The COVID-19 pandemic has laid bare the importance of non-pharmaceutical interventions in the containment of airborne infectious diseases. Social distancing and mask-wearing have been found to contain COVID-19 spreading across a number of observational studies, but a precise understanding of their combined effectiveness is lacking. An underdeveloped area of research entails the quantification of the specific role of each of these measures when they are differentially adopted by the population. Here, we make a first step in this direction, by establishing a susceptible-exposed-infected-removed epidemic model on a temporal network, evolving according to the activity-driven paradigm. Through analytical and numerical insight, we study epidemic spreading as a function of the proportion of the population following public health measures, the extent of social distancing, and the efficacy of masks in protecting the wearer and others. Our model demonstrates that social distancing and mask-wearing can be effective in preventing COVID-19 outbreaks if adherence to both measures involves a substantial fraction of the population.

Keywords: Modelling and simulation, Nonlinear systems, Optimisation
Abstract: Dynamic optimization of proteins (including endotoxin), cells and spore production by B. thuringiensis needs to use robust models coupled with control strategies. In this work, two models were proposed to describe proteins and spores production using Bacillus thuringiensis kurstaki LIP. Models were calibrated and the obtained parameters were in the literature range. The best model was selected to implement two control strategies assuming fed-batch and Sequential Batch reactor cultures. Both approaches allowed to maximize protein and spore productivities, but the fed-batch strategy gave the best performances.

Keywords: Time-delay systems, Feedback stabilization, Optimisation
Abstract: Eigenvalue-optimization-based stabilization of multi-input multi-output linear time-invariant systems is considered. The system is allowed to be a retarded time-delay system with discrete time-delays. No restriction has been made on the number of time-delays. Instead of conventional static or dynamic delay-free output feedback, delayed output feedback is considered in the controller part. Furthermore, in the case of multi-input and/or multi-output, the controller is allowed to introduce a different time-delay in each input-output channel. Benchmark examples illustrate the effectiveness of the proposed method.

Keywords: Process control, Linear systems, Time-delay systems
Abstract: A graphical technique for the design of PI/PID controllers to achieve desired closed-loop frequency-domain as well as time-domain specifications simultaneously, is proposed in this paper. Both frequency and time-domain performance measures such as gain margin, phase margin, maximum percentage overshoot and settling time can be specified before controller tuning. Simplicity of the technique is an added advantage. The concept of stability boundary locus along with gain phase margin tester (GPMT) is used to compute constant gain and phase margin boundaries in the controller parameters plane. Common area of constant gain and phase margin boundaries within the all stability region is the desired gain and phase margin region (DGPMR). A novel graphical technique using the direct synthesis approach is proposed to obtain the desired closed-loop time response. Curves corresponding to the time-domain performance measures (maximum percentage overshoot and settling time) are drawn in the controller parameters plane. Intersection of the above-said curves within the DGPMR gives the desired controller parameters. Simulation results for a non minimum-phase third-order process and hardware experimental results for a DC-DC boost converter with comparison are given to show the effectiveness of the proposed tuning strategy.

Keywords: Linear systems
Abstract: Some recent papers have extended the concept of finite-time stability (FTS) to the context of 2-D linear systems, where it has been referred to as finite-region stability (FRS). FRS methodologies make even more sense than the classical FTS approach developed for 1-D systems, since the state variables of 2-D systems often depend on a pair of space coordinates, rather than on time, as it is the case, for instance, of the image processing framework. Since space coordinates clearly belong to finite intervals, FRS techniques are much more effective than the classical Lyapunov approach, which looks to the asymptotic behavior of the system over an infinite interval. To this regard, the novel contribution consists of a new sufficient condition for FRS of linear time-varying (LTV) discrete-time 2-D systems, which turns out to be less conservative than those ones provided in the existing literature. Then, a sufficient condition to solve the finite-region stabilization problem is proposed. All the results provided in the paper lead to optimization problems constrained by linear matrix inequalities (LMIs), that can be solved via widely available software. Numerical examples illustrate and validate the effectiveness of the proposed technique.

Keywords: Linear systems, Nonlinear control
Abstract: The main goal of the paper is to project parametric constraints into the design conditions of an observer with unknown input for nonlinear Metzler-Lipschitz systems. By extending the set of the linear matrix inequalities to guaranty the Metzler system matrix structure of the unknown input observer, the desired observer positive performances are maintained throughout observer functionality. The presented modification yields the observer performance when the design conditions are formulated by the set of linear matrix inequalities with the redefined structure of Lyapynov inequality. In contrast with the case of linear systems, new related properties had to be deduced to characterise Metzler-Lipschitz state estimation in the unknown-input observer structure.

Keywords: Optimisation
Abstract: This paper gives an in-depth review of the most common iterative methods for unconstrained optimization using two functions that belong to a class of Rosenbrock functions as a performance test. This study covers the Steepest Gradient Descent Method, the Newton-Raphson Method, and the Fletcher-Reeves Conjugate Gradient method. In addition, four different step-size selecting methods including fixed-step-size, variable step-size, quadratic-fit, and golden section method were considered. Due to the computational nature of solving minimization problems, testing the algorithms is an essential part of this paper. Therefore, an extensive set of numerical test results is also provided to present an insightful and a comprehensive comparison of the reviewed algorithms. This study highlights the differences and the trade-offs involved in comparing these algorithms.

Keywords: Intelligent control systems, Predictive control
Abstract: Reinforcement Learning (RL) has recently demonstrated a stunning ability to solve problems that were previously considered intractable. However, RL is not exempt from drawbacks, which include the difficulty in providing closed-loop stability and safety guarantees. We propose to alleviate these issues by using Model Predictive Control (MPC) as a function approximator within RL. The main idea is that MPC is used to provide the sought guarantees, while RL is used to exploit the remaining degrees of freedom to tune MPC so as to deliver the best performance for the true system rather than for the model used inside MPC.

Keywords: Predictive control, Power systems and smart grid, Nonlinear systems
Abstract: Designing a controller for bilinear DC-DC boost converters which can guarantee safe and stable operation of the interconnected devices is always of major importance. In this paper, based on Sum of Squares (SOS) optimization, a controller is designed to guarantee Lyapunov stability for the closed-loop system. The optimization is formulated in order to achieve the largest possible Region of Attraction (ROA) for the considered equilibrium point while taking into account input and states constraints. The ROA and the Lyapunov function obtained with SOS are respectively taken as Terminal Set (TS) and Terminal Penalty (TP) of the Model Predictive Control (MPC). Compared to MPC without TS and TP, the use of these ingredients allows to guarantee stability in an enlarged ROA even with short prediction, thus limiting the computational complexity of the method. The proposed approach is demonstrated in simulation on a discrete-time bilinear model of a DC-DC boost converter. In order to account for the unmeasured states, a Kalman Filter is also used.

Keywords: Predictive control, Nonlinear control, Hybrid systems
Abstract: An algorithm for nonlinear optimal generalized predictive functional control is defined for controlling discrete-time piecewise affine systems. The main piecewise affine form is transferred into a corresponding state-dependent system form. The principal piecewise affine system's hybrid properties are retained, and both the continuous and switching dynamics are combined in the same system description. This method enables the use of nonlinear generalized predictive functional control for this hybrid system class. In the generalized predictive functional control method, different classical controller structures can be employed in the feedback loop, such as PI, PID or other classical transfer-function structures. The loop controller is defined here to have a PI structure, and its selected linear transfer-functions set is multiplied by gains that are found to minimize a GPC type of cost-index. The simulation results are shown using a model of a continuous stirred tank reactor.

Keywords: Predictive control, Robotics, Embedded control systems
Abstract: The computational cost of implementing Model Predictive Control (MPC) restricts its use in robotic systems with fast dynamics. The use of optimization algorithms to find a control solution is responsible for most of the computational cost. Explicit MPC (eMPC) solutions aim to overcome the computational cost problem by performing the optimization process before runtime. The main contribution of this work is to compare the computational cost of the conventional MPC to the computational cost of eMPC, in the quadrotor stabilization task. The controllers are evaluated in two different scenarios, one in a Model-in-Loop (MIL) environment and the other using the Robot Operating System (ROS) in a Processor-in-Loop (PIL) setup. The results show that eMPC is an alternative to implement predictive controllers with determinism in computational time execution, due to the use of only algebraic operations at runtime, without any numerical tools, but, with the disadvantage of using a significant amount of memory.

Keywords: Predictive control, Nonlinear control, Robotics
Abstract: The goal of this paper is to present a nonlinear Model Predictive Control scheme for boom cranes, one of the most common type of rotary cranes. In this paper we first present a complete mathematical model for this type of cranes where it is possible to control the two rotations of the crane and the cable length. Then, we design a Model Predictive Control law able to drive the load to a desired position while fulfilling mechanical and safety constraints. We finally compare our controller to a partial feedback linearization coupled with a proportional derivative control with gravity compensation applied to the same model.

Keywords -

Boom cranes; Robotics; Motion control; Under-actuated systems; Nonlinear Model Predictive Control.

Keywords: Optimisation, Linear systems, Automotive control
Abstract: We examine the path following problem in the framework of relaxed barrier function based Model Predictive Control for linear discrete-time systems. We establish exponential stability and constraint satisfaction guarantees of the closed-loop system. Furthermore, we propose a simple algorithm that is applied to different maneuvers in automated driving and we compare the algorithm with a trajectory tracking controller.

Keywords: Game theory, Wireless sensor networks, Networked systems
Abstract: Wireless Sensor Networks channel exhibits significant complexity when attempting to analyse theoretically the network layer of the wireless stack. A parameter of this layer is the Packet Reception Ratio (PRR). Optimising PRR can result in transmission reliability and high throughput. Considering wireless nodes as players, we can construct game-theoretic models that can be utilised to solve transmission reception problems in a distributed nature. In this paper, we give necessary conditions to use potential game approaches with PRR utility functions.

Keywords: Intelligent control systems, Wireless sensor networks
Abstract: This paper deals with the problem of resource management in Multi-Access Networks. A Reinforcement Learning based hierarchical control strategy is presented. The main contribution of the proposed approach is its capability of simultaneously tacking the load balancing and QoS management problems in a scalable, dynamic and closed-loop way. The effectiveness of the proposed solution has been proved in a specific case study in the context of which the performances of the proposed algorithm have been compared with a standard load balancing controller.

Keywords: Nonlinear systems, Networked systems, Distributed systems
Abstract: This paper develops Lyapunov and converse Lyapunov theorems for discrete-time stochastic semistable nonlinear dynamical systems expressed by Ito-type difference equations possessing a continuum of equilibria. Specifically, we provide necessary and sufficient Lyapunov conditions for stochastic semistability and show that stochastic semistability implies the existence of a continuous Lyapunov function whose difference operator involves a discrete-time analog of the infinitesimal generator for continuous-time Ito dynamical systems and decreases along the dynamical system sample solution sequences satisfying an inequality involving the average distance to the set of the system equilibria. These results are then used to develop semistable consensus protocols for discrete-time networks with communication uncertainty capturing measurement noise and attenuation errors in the information transfer between agents. The proposed distributed control architecture involves the exchange of information between agents guaranteeing that the closed-loop dynamical network is stochastically semistable to an equipartitioned equilibrium representing a state of almost sure consensus consistent with basic discrete-time thermodynamic principles.

Keywords: Formation control, Swarms
Abstract: Recently we have developed a tracking-control technique that is based on a Newton-Raphson flow, system-output prediction, and controller speedup. This paper investigates an application of the technique to a swarm of mobile agents which have to maintain a given formation while in motion. The control is essentially distributed, where each agent, except for the leading one, collects information only from the agents immediately ahead of it. The motion dynamics of the agents are two dimensional and linear, but the tracking control technique can be extended to nonlinear systems as well. We investigate a specific example by simulation, and the results indicate convergence and several additional salient features of the control technique.

Keywords: Optimisation, Distributed systems, Networked systems
Abstract: In this paper, relations between distributed consensus-based optimization and a network resource allocation problem are considered. It is shown that first-order gradient algorithm for distributed consensus-based optimization can be used for finding an optimal solution of distributed resource allocation with synchronous protocol under weaker assumptions than those given in the literature. Moreover, second-order gradient algorithm for distributed consensus-based optimization is presented that can be employed for solving distributed resource allocation problems. As a result, several algorithms used for distributed consensus-based optimization can now be applied to derive distributed algorithms for resource allocation. It is shown that first and second order gradient algorithms for distributed resource allocation can be utilized for finding an optimal solution of distributed consensus-based optimization as well. The results presented in this paper can be applied to time-varying or random directed networks with or without synchronous protocols with arbitrary initialization. Finally, a numerical example of a distributed estimation in wireless sensor networks is given to demonstrate the results.

Keywords: System identification, Modelling and simulation, Linear systems
Abstract: The study of lateral dynamics is of great importance for the vehicle behavior analysis during turning maneuvers, and it is fundamental to stability or path control systems used in autonomous vehicles. This case study focuses on the identification of a continuous-time linear model of a 6x6 military vehicle for different speeds. Field data of the vehicle during a North Atlantic Treaty Organization (NATO) double lane change maneuvers were used, and transfer functions between the yaw rate (output) and the steering wheel angle (input) were identified using the CONTSID toolbox. Based on the estimated models, the results show a good agreement with the experimental measurements and it is possible to analyze the system's poles and zeros behavior, as well as the frequency response of the system with speed variation. As conclusions, an increase in the vehicle's speed implies a higher magnitude gain, and the poles of the system present the tendency to move from an underdamped to an overdamped system.

Keywords: Education and training
Abstract: Evidence worldwide speaks of limited presence of women in STEM sectors. This starts from the early stages of higher education, and gets even worse in both academia and in the job market, with only few examples of women with C-level positions in STEM-related companies. The overall phenomenon that sees the proportion of women progressively shrinking while escalating the professional ladder is known as “leaky pipeline”, and presents itself both in academia and the industry career path. Is this a conscious choice or an unconscious, education-based opt out obligation? For sure, early infancy imprinting plays an important role in the self-perception of girls, and the so-called “role-congruity” models shaping our society still tend to place women outside the scientific and technological arena. The panel will review the current state of different aspects of involvement of women in STEM studies, careers and competencies, analysing the impact they may have on their lives, families and society at large. The panel will also analyse how the COVID-19 pandemic is affecting the working environment of both academic and non-academic women, discussing how work/life balance issues affect productivity, and how pandemic and post-pandemic caring duties can have long-term effect on the career development, putting forward proposals for taking these aspects into practical consideration in the career evaluation processes of the post-COVID era.

Moderator: Mara Tanelli, Politecnico di Milano

Opening remarks: Mariagrazia Dotoli, Politecnico di Bari

Panelists:

Letizia Jaccheri Norwegian university of Science and Technology.

Jinane Abounadi Massachusetts Institute of Technology, Boston, USA.

Thomas Parisini Imperial College London, London, UK; Università degli studi di Trieste, Trieste, Italy.

Maria Domenica di Benedetto, Università degli Studi dell’Aquila, L’Aquila, Italy.

Elisabetta Camussi Universita’ degli Studi di Milano Bicocca, Milano, Italy.

Laura Giarrè Università di Modena e Reggio Emilia, Italy.