Keywords: Biologically inspired systems, Navigation, Robotics
Abstract: Autonomous navigation requires multi-sensors data fusion provided either by global navigation satellite systems (GNSS) devices, inertial measurement units, radars and cameras to achieve accurate localization. Each technological solution features advantages but suffers also from drawbacks. Data fusion aims at maintaining a strong level of accuracy and robustness to make autonomous navigation systems reliable enough to be embedded on board any autonomous vehicles. However, there are still environmental contexts in which most sensors drift or even fail to provide correct estimates. In this study, we discuss the opportunity to use a celestial compass inspired by the desert ants' visual system which is able to extract heading information from the polarization pattern of the skylight in the ultraviolet (UV) spectrum. This new sensing mode has been mounted on-top a car and tested outdoor on a 18.6km-long journey in town and compared with GNSS estimates. The UV celestial compass yielded promising performances regarding its low complexity and the root mean square error of the orientation error was only 0.55°. Our results suggest the suitability of such parsimonious insect-inspired solutions for robotic purposes in urban field like the last mile delivery.

Keywords: Modelling and simulation, Systems biology, Computational methods
Abstract: The apoptotic signaling pathway designates a set of biochemical reactions involved in programmed cell death. One of the triggering mechanisms of apoptosis is the binding of death ligands to death receptors on the cell membrane, a known stimulus for the activation of the so-called extrinsic apoptosis signaling pathway. Stimulation by death ligands results in an important variability in cell response dynamics that elicits differing fates: cell survival or cell death. To understand the hallmarks of this cell fate decision and the heterogeneity of cell response, a system of ordinary differential equations based on mass-action rate laws was implemented to represent the reactions at the receptor level and evaluate the cell dynamics in response to anticancer drugs.

Keywords: Navigation, Biologically inspired systems, Robotics
Abstract: Navigating insects like desert ants are known to robustly estimate their position from their nest while foraging for food, for several hundred meters across hostile environments, by means of very low resolution visual information processing. This tour de force stands for a great source of inspiration to design smart, parsimonious and robust solutions to make robots of any size navigate in global navigation satellite systems-denied or in cluttered environments. In this study, we introduce a new insect-inspired omnidirectional visual sensor (640x120 pixels; 120 fps). The inter-pixel angle is equal to 0.6° and the acceptance angle is equal to 1.5°, which is comparable to those observed in predatory flying insects. This sensor was embedded on-board the AntBot robot, a six-legged walking robot mimicking desert ants at morphological, locomotive and sensing levels. Despite the residual visual oscillations of the field of view while walking, the robot successfully detected fixed obstacles and was able to locate itself with an accuracy as low as 25 ± 10 cm, which actually corresponds to an average error of only 3 strides (hexapod stride length: 8.2 cm) after a 9m-long journey. This suggests that low-acuity visual sensors, inherently requiring few computational resources, are good candidates for ant-like familiarity-based navigation in cluttered environments.

Keywords: Optimisation, Biologically inspired systems, Nonlinear systems
Abstract: This paper discusses the use of optimal control strategies for ascertaining efficient usage of infection eliminating methodologies. The mathematical model of tuberculosis is considered which is incorporated with three control terms. The preventive controls used for containing the spread of tuberculosis, include vaccinations along with treatment control for the latent, susceptible and infected population. By implementing the Pseudospectral method on the Tuberculosis model, the original continuous-time optimal control problem is converted into its equivalent non-linear programming problem and then solved. On the application of the proposed control scheme, a minimization in the intervention cost and a significant reduction in the disease burden is expected. A comparative analysis between the widely used Legendre Pseudospectral method and Chebyshev Pseudospectral method when applied to the mathematical model of tuberculosis is included in this work. The response of the states in the absence of any control effort is also included to demonstrate the effect of optimal control strategy on the disease.

Keywords: Process control, System identification, Biomedical engineering
Abstract: The contribution of this paper is to present a state-feedback design method for the automatic control of the Neuromuscular Blockade Level (NMB) based on pole placement scheme. The typical clinical procedure in surgery room begins by the administration of an initial bolus in order to enable a fast intubation, followed by a piecewise constant infusion of a certain neuromuscular relaxant (here, rocuronium). This latter procedure, known as TCI (Target Controlled Infusion) aims at reaching and maintaining a desired level for the NMB. First, the identification of the parameters of a PPM (parameter parsimonious model) is performed using the bolus response until the NMB reaches the target NMB level. Thereafter, the controller is tuned according to the identified patient parameters, in order to suitably place the poles, leading to an individualized target control infusion. The pole placement criterion is based on a weighted cost function that takes into account both the tracking performance and the average administered drug dose. The obtained results are illustrated by means of simulations.

Keywords: Distributed systems, Predictive control, Automotive control
Abstract: This paper proposes a distributed model predictive control (DMPC) strategy with known delays in the communication network. The algorithm is suitable for a vehicle platooning application in the cooperative adaptive cruise control (CACC) framework. All the platoon vehicles are connected in a uni-directional wireless communication network. The simulation results for a five-vehicle platoon show that the DMPC optimization problem can successfully accommodate for the communication delays, while a velocity-dependent inter-vehicle spacing-policy for the follower vehicles is used.

Keywords: Formation control, Distributed systems, Multi-agent systems
Abstract: The ever-increasing number of vehicles that use the current infrastructure brings many disadvantages, among which one can emphasize traffic congestion and decreased safety, mostly due to human error. While the human drivers are aided more and more by different automated functionalities that help them make the best decisions at certain times or may even be replaced by higher-level functionalities, automated vehicles are far from being deployed in series on the roads because it is difficult to ensure functional safety at all times. Moreover, automated vehicles would solve only half of the problem, i.e., removing the human factor from the loop, but the number of vehicles would not decrease which leads to the same traffic congestion. One solution would be to reduce the space between the vehicles, but this implies even higher functional safety of the automated features. Another idea is to make use of the vehicle platooning concept based on cooperative adaptive cruise control and extend it to the multiple-lane use-case. This would involve coordinating a group of vehicles traveling on a multiple-lane road to maintain small gaps between them even at highway speeds. The solution implies an exchange of information between vehicles, such that their trajectories are optimized at all times. Thus, this paper considers the design and development of a control architecture for multiple-lane vehicle flocking based on their cooperative decisions. The simulation results obtained using a simulator based on SUMO and Matlab illustrate the capabilities of the proposed methodology.

Keywords: Intelligent control systems, Predictive control, Energy efficient systems
Abstract: Smart Home applications tend to be more focused not only on responding to user’s actions but also on anticipating his needs and adding controls to support these needs. Researchers have developed so far methods which consider behavior modeling for easier identification of deviating situations or automating user actions, comfort and energy saving models which aim to optimize consumption while keeping the habitant perception of the environmental state at a proper level, or context awareness integrated with the building automatic control systems to adapt environmental control rules to the house special characteristics. This paper proposes a user comfort management architecture which processes inputs from context analysis and behavior modelling modules to achieve a narrow control scheme fitted to user’s perception of comfort and able to adapt to different action scenarios. Such a system considers the acquisition of temperature, humidity, and CO2 data, as well as inputs from presence sensors and integrates air conditioning equipment for set-point change or room thermostat control. Electrical consumers patterns can also be identified in relationship with user behavior to support energy efficiency algorithms. The paper discusses the requirements the models should feature, the functional aspects and proposes an algorithm for their integration.

Keywords: Robotics, Industrial automation, manufacturing, Mechatronic systems
Abstract: The paper presents a solution for visual servoing problem that is implemented on a robotic arm from an industrial flexible assembly line. This line respects the Industry 4.0 paradigm, thus having a modular structure consisting of five stations. Each station includes a Programmable Logic Controller equipment for local control and communication modules for connection with other stations. The paper is focused on the design and implementation of the visual servoing system which ensures the line flexibility. The experimental results validate the system functionality and indicate remarkable performances.

Keywords: Wireless sensor networks, Unmanned systems, Hybrid systems
Abstract: The paper proposes a cheap hybrid ground-air sensor network for environmental parameter measurements. The ground sensors are grouped into clusters, each cluster having several sensory nodes connected to a cluster head that sends the relevant data to the aerial, mobile nodes - unmanned aerial vehicles (UAVs). Thus, using optimal trajectories, the UAVs are used both for measuring directly environmental parameters, as well as for collecting data from ground sensors. The authors present the modules' implementation of the hybrid system: ordinary sensory nodes, cluster heads, ground control stations, communication modems and UAV platforms. Finally, the performances of the realized hybrid network are analyzed from multiple points of view: energy consumption, time, and data acquisition efficiency.

Keywords: Aerospace control, Guidance, Robust control
Abstract: Over the last few decades, the computational capabilities of the state-of-the-art processors have increased extensively and are now capable of performing multiple parallel computations. However, due to constraint on cost, weight, and space, they are not generally installed as an on-board processor of an interceptor. This limitation of the computational capabilities of the missile processor is addressed in this paper, by designing an event-triggered strategy which reduces the number of control updates. In addition to achieving the primary objective of capturing the target, the proposed guidance strategy enables the interceptor to tackle external disturbances that it encounters. Further the conservative assumption of apriori knowledge about the upper bound of the disturbances is eliminated by adaptively tuning the gains of the proposed guidance law. Input saturation has also been considered on the control effort of the missile so as to be consistent with most practical interceptor systems. Lyapunov theory has been used to demonstrate asymptotic stability of the closed-loop system states under the proposed event-triggered control scheme. Numerical simulations for the guidance strategy on the commonly occurring tail-chase and head-on engagement scenarios are performed along with a comparative performance analysis with the periodic time-triggered technique.

Keywords: Adaptive control, Distributed systems, Linear systems
Abstract: Recently, the first result on backstepping-based adaptive control of a 1 -D linear hyperbolic partial differential equation (PDE) with an uncertain transport speed was presented. The system also had an uncertain, constant in-domain coefficient, and the derived controller achieved convergence to zero in the L_infty -sense in finite time. In this paper, we extend that result to systems with a spatially varying in-domain coefficient, achieving asymptotic convergence to zero in the L_infty -sense. Additionally, for the case of having a constant in-domain coefficient, the new method is shown to have a slightly improved finite-time convergence time. The theory is illustrated in simulations.

Keywords: Adaptive control, Distributed systems, Linear systems
Abstract: We construct a method of dealing with the problem of overparameterization in model reference adaptive control (MRAC) of 2 times 2 linear hyperbolic partial differential equations (PDEs). The method is based on linear interpolation of the uncertain parameters. The proposed method is demonstrated in simulations of the fluid mechanics of a drilling system, and compared to a previously derived, overparameterized MRAC scheme, showing improved tracking and convergence properties.

Keywords: Adaptive control
Abstract: In this paper a gradient observer and finite-time observer of stator flux are developed for non-salient permanent magnet synchronous motors. The methods described here are based on implementation of LTI filters and DREM techniques. The motor resistance and inductance are assumed to be known.

Keywords: Adaptive control, Distributed systems, Linear systems
Abstract: We extend a previous result regarding adaptive control of a linear hyperbolic partial differential equation (PDE) with time-varying in-domain source coefficient in two ways. Firstly, we introduce a parametrization of the uncertain time-varying in-domain source coefficient that allows for a broader class of systems compared to previous result. Secondly, and more importantly, we introduce an uncertain scaling factor in the input boundary condition which is present in most applications, but wasn't handled in the previous result. All system parameters except the transport speed are uncertain and time-varying, although parametrizable as a linear combination of uncertain constants and certain time-variance. Closed-loop convergence of the state to the origin is proven, and performance is demonstrated for a numerical example.

Keywords: Computational methods, Genetic and evolutionary computation, Robotics
Abstract: A control problem for a group of robots is considered. The robots have to move from given initial conditions to terminal ones without collisions between themselves and stationary obstacles. To solve the problem, the optimal synthesized control method is used. According to this method firstly the control system synthesis problem for each robot is solved. As a result, the control system stabilizes the robot relative to some point in the state space. After that positions of these stable equilibrium points in the state space for each robot are found so that all robots can move from point to point till the terminal positions without collisions. For synthesis problem on the first stage the Cartesian genetic programming is used. This method of symbolic regression allows to find a mathematical expression for control function in the form of special code by a special genetic algorithm. It’s shown, that using the symbolic regression methods directly doesn’t allow to find a synthesized control function in a code space, because this search space does not have numerical measure for distance between two elements of the space. So the Cartesian genetic programming was modified and the principle of small variations of the basic solution was included in it. A computational example of controlling eight robots on the plane with phase constraints is presented.

Keywords: Game theory, Robotics, Predictive control
Abstract: In this work, non-cooperative competitive games between two unmanned ground robots using Nonlinear Model Predictive Control (NMPC) while incorporating obstacle avoidance techniques are studied. The objective of the first player (pursuer) is to minimize the relative distance and orientation between itself and the second player (evader) while avoiding obstacles, whereas the evader does the opposite. The Pursuit-Evasion Game (PEG) being a typical class of a differential game is formulated as a zero-sum game with two homogeneous players in five different game scenarios. The objective function of each player is formulated as a double optimization problem and is solved separately using NMPC techniques. The optimal trajectory of each player is computed iteratively by considering the best response of the opponent player. The level of information is assumed to be symmetric. Simulations of various scenarios show the winning possibility of each player.

Keywords: Intelligent control systems, Robotics
Abstract: This paper presents a methodology to determine the shortest path in the joint space of a cable-driven parallel robot for point-to-point motions. The formulation is based on the joint space domain i.e., cable length and the shortest path in joint space is determined between the two points. The path is constrained by the 4th degree polynomial in the Cartesian space and the objective function representing the total path length in the joint space is formulated. The parameters of the path are obtained by minimizing the objective function using genetic algorithm while satisfying the non-negative cable tension constraints. The proposed methodology is validated using a 3-DOF planar and a 6-DOF spatial cable-driven robot. The obtained optimized shortest path is compared to a straight-line path and the results obtained shows a significant reduction in the joint space path length of a cable-driven parallel robot for the optimized path. The reduction will be even more significant for the large-scale cable-driven parallel robot.

Keywords: Optimisation, Nonlinear control, Robotics
Abstract: In this paper, the problem of controlling compliance of a robotic tensegrity structure (finding the state of the structure which produces desired stiffness) is discussed. Tensegrity structures have a number of unique properties: they are well suited for uncertain environments, are easily deployed, impact resistant, foldable and light-weight and thus provide a desirable component for a number of robotics applications. They are currently being used as a structural element of robotic extraterrestrial probes, crawling robots, swimming robots and others. The compliance control problem here is solved by a convex relaxation of the original non-convex program, which in turn is done by introducing two linear models: one for the stiffness matrix and one for the elastic forces. Solution accuracy is controlled by introducing an iterative scheme, solving the convex problem on each iteration. Proposed algorithm converges providing accuracy better than 0.01 N/m in terms of stiffness using only 10 iterations of the algorithm, and the accuracy of force equilibrium is better than 1 N.

Keywords: Robotics, Nonlinear control
Abstract: High degree of maneuverability in omnidirectional mobile robots, which stems from their holonomic nature, has posed them as an attractive solution in a variety of applications. This paper studies the problem of trajectory control in omnidirectional robots based on practical observations. More specifically, the dynamics of the low-level motor drivers are explicitly incorporated during the development of a hierarchical controller. Lyapunov’s stability theorem is then used to analytically derive the control law which could achieve seamless integration of different control structure hierarchies. The simulation results show the effectiveness of the proposed method compared to other commonly-used algorithms. Furthermore, the controller exhibits low sensitivity to model parameter variations despite its model-based nature, which would be a very beneficial feature in practical implementations as it would limit the need for extensive modeling and calibration.

Keywords: Autonomous systems, Robotics, Unmanned systems
Abstract: Biofouling is a challenge for finfish farming as it can impact cage stability and fish health. Amongst others, current strategies against biofouling rely heavily on removal of biofouling using in-situ pressure cleaning of nets. The cleaning waste is released into the water where it can impact the health of the cultured fish. Grooming, the regular cleaning of nets to prevent biofouling communities from establishing, is one novel strategy that is currently explored using tethered underwater robots. In addition, remotely operated vehicles (ROVs) are used for inspection of the net to ensure its integrity and prevent fish escapes, while stationary sensors at the farm barge are employed to extrapolate on environmental conditions in the net pens. In this paper, the requirements for a permanently resident, autonomous and tetherless subsea robot for cleaning and inspection are proposed. As such, the robot aims to combine several application areas and offer a solution to the biofouling challenge while at the same time providing better safeguardig of net integrity and monitoring of environmental conditions directly in the pen. Using the SEATONOMY method from an operational viewpoint, the robot's individual operations are analysed. This included i) Environmental condition monitoring, ii) Net and biofouling inspection, iii) Growth prevention and iv) Docking. As a result, the specifications and requirements for the development of a novel robotic system that is able to perform simultaneous inspection, growth prevention and monitoring in fish cages fully autonomously are derived. The paper proposes the development of new technology and biofouling management strategy that will contribute to increase the efficiency and production demands in aquaculture industry.

Keywords: Navigation, Robotics, Unmanned systems
Abstract: This paper addresses the problem of detecting radioactive material in transit using an unmanned aerial vehicle (UAV) of minimal sensing capability, where the objective is to classify the target’s radioactivity as the vehicle plans its paths through the workspace while tracking the target for a short time interval. Assuming that the prior map of the workspace is available, this paper proposes a motion planning framework that integrates a navigation function based planner with a tightly-coupled visual-inertial localization and target tracking algorithm, and generates dynamically feasible trajectories that provably converge to a moving target while avoiding obstacles. The efficacy of the proposed approach is validated through Gazebo simulations.

Keywords: Robotics, Autonomous systems, Unmanned systems
Abstract: The Mining industry considers the deployment of MAV for autonomous inspection of tunnels and shafts to increase safety and productivity. However, mines are challenging and harsh environments that have a direct effect on the degradation of high-end and expensive utilized components over time. Inspired by this effect, this article presents a low cost and modular platform for designing a fully autonomous navigating MAV without requiring any prior information from the surrounding environment. The design of the proposed aerial vehicle can be considered as a consumable platform that can be instantly replaced in case of damage or defect, thus comes into agreement with the vision of mining companies for utilizing stable aerial robots with reasonable cost. In the proposed design, the operator has access to all on-board data, thus increasing the overall customization of the design and the execution of the mine inspection mission. The MAV platform has a software core based on ROS operating on an Aaeon UP-Board, while it is equipped with a sensor suite to accomplish the autonomous navigation equally reliable when compared to a high-end and expensive platform.

Keywords: Unmanned systems, Optimisation
Abstract: Remotely operated vehicles commonly have propellers with fixed position and orientation. In this paper, we highlight the advantages of equipping remotely operated vehicles with azimuth thrusters. In particular, both energy saving and increased trajectory tracking performances can be achieved with respect to the fixed orientation case. On the other hand, managing thrusters’ orientation represents a further computational burden: the constraints are characterized by the presence of trigonometric functions, thus they require, in general, the use of onerous nonlinear solvers. Our proposal is to steer collectively the thrusters, in order to simplify both the optimization algorithm and the mechanical structure of the ROV. The proposed control allocation algorithm calculates, at first, the orientation of the propeller to minimize the energy consumption while taking into account saturation and rate limits. Then, single thrusts are calculated using a quadratic programming framework. Simulation results show the relevance of energy savings and tracking improvements.

Keywords: Unmanned systems, Robotics
Abstract: This article presents a novel C++ template transla- tion layer between the Robot Operating System (ROS) interface and a low-level control board, as a tool to be used by researchers developing robots to reduce time needed in writing code for new robots, to reduce vendor lock-in, and to increase interoperability between researchers low-level control boards. The last two named goals stem from the fact that research in automation of micro aerial vehicles has increased through the last decade and a need for standardization within the open- source community has risen if research is to remain vendor independent. A guide on how to design serial communication between low-level and high-level controllers is provided. Lastly, an implementation of the said translation layer was created to demonstrate its use.

Keywords: Distributed systems, Networked systems, Computing and communications
Abstract: This paper deals with high mobility mobile ad-hoc networks (MANETs) whose nodes need to be synchronized. Unlike existing solutions, which either use reference clock or broadcast synchronization messages, our algorithm achieves synchronization by sending zero-bit pulses over the network and is thus usable in the first steps of establishing MANETs. We develop a dynamic adaptive selection technique for choosing an exponential smoothing factor and show the impact of using a fixed value of this parameter on the performance of the algorithm. In addition to that, we demonstrate the strength of our algorithm to withstand the network topological changes during execution. We evaluate the algorithm through extensive simulation in vehicular ad-hoc networks (VANETs). The simulation results show significant performance improvement in terms of reducing the clock offset and drift over the previous works.

Keywords: Embedded control systems, Real-time control, Education and training
Abstract: A novel multiplatform control framework named BlockNet is introduced. It can be used either for simulations, soft real-time control in real experiments and integration of complex technologies (e.g neural networks, vision sensors etc.). BlockNet has been developed to provide an easy to use unique tool for local or distributed applications able to guarantee the correct execution order of block codes based on their dependencies, maintaining dynamism and portability. To the best of our knowledge such features are not currently provided at once in other frameworks. We discuss the features of BlockNet, its main structures and functionalities, providing also its effectiveness in a real control application: an earthquake simulation platform.

Keywords: Feedback stabilization, Linear systems, Mechatronic systems
Abstract: This article is concerned with an output feedback position control of gantry (overhead) cranes applying a parallel feed-forward compensator (PFC) that allows for a reduction of payload swinging without additional sensors or payload swing angle estimations. Performance and stability of the controlled system are achieved by defining a new output as a combination of the original output and the output of an appropriate PFC. The later provides an almost strict positive real (ASPR) condition for the augmented plant. Thus, high gain output feedback control becomes applicable. The proposed feedback control approach is successfully validated in a numerical study and in experiments on a laboratory plant.

Keywords: Linear systems, Computational methods
Abstract: For linear continuous-time positive systems the paper proposes an approach, reflecting structural constraints and positiveness in the problem of Metzlerian and strictly Metzlerian interval observers design. Every interval matrix boundary is represented by a set of linear matrix inequalities representing Metzler matrix parameter constraints and reflecting potential zero elements in a Metzler matrix structure by structural diagonal matrix variables. Combined with couple of Lyapunov inequalities, the observer Metzler matrix parameters are guaranteed and interval stability is attained. A numerical example is included to assess the feasibility of the proposed technique.

Keywords: Linear systems, Optimisation
Abstract: This paper deals with the almost exact set point regulation for Linear Time-Invariant (LTI) continuous-time polytopic systems. To this purpose, a novel robust pseudo- inversion based feedforward control is proposed. The method is based on a two Degrees of Freedom (2DoF) control scheme where the output r(t) of a pseudo-inverting feedforward filter Σff is used as input forcing a closed-loop system Σf. Σf is the feedback connection of an LTI continuous time polytopic plant Σp with an LTI robustly stabilizing controller Σc. In steady-state condition, an exact tracking is achieved endowing Σc of the internal model of constant signals. In the transient state an optimal tracking is obtained computing the transient component rt(t) of r(t) through the on-line minimization of a worst case quadratic cost functional of the transient tracking error. To improve the numerical efficiency of the optimization procedure, the transient input rt(t) is modeled as a B-spline. These functions are universal approximators which admit a par- simonious parametric representation so that the minimization of the worst case cost functional can be formulated as a robust estimation problem. In turn, this problem can be recast as a Second Order Cone Program (SOCP) which can be efficiently solved using primal and dual point methods.

Index Terms— model inversion, uncertain plants, two degrees of freedom control

Keywords: Nonlinear systems, Computational methods, Modelling and simulation
Abstract: Model order reduction of input affine nonlinear systems via trajectory piecewise linear approximation is a well known practice. This method along with its variants is known to generate efficient and accurate reduced models of large order nonlinear systems. The selection of the order of the reduced model is however a heuristic choice that comes with experience. There is no concrete measure of an optimum selection of the reduced order that would lead to approximations with high accuracy and least computational cost. This paper provides a study of few variants of trajectory piecewise linear method and effect of the choice of reduced order on the accuracy of the approximations and the computational cost. The results have been studied on a nonlinear transmission line circuit. This study provides a performance analysis that exhibits a range of acceptable values of reduced order that may be preferred for generating accurate trajectory piecewise approximations of circuits similar to that discussed in this paper.

Keywords: Sampled-data systems, Linear systems
Abstract: This paper discusses the digital control of a linear periodic object when using a generalized hold element. The solution for the problems of causal modal control and stabilization based on a discrete backward model formulation is given.on the basis of the discrete model of the system using the apparatus of determinant polynomial equations.

Keywords: Cyber-physical systems, Power systems and smart grid, Complex systems
Abstract: With the recent trends of smart cities, the development in the sector of Smart Buildings has emerged tremendously which consists of multiple layers coordinating and interacting with each other with the help of a building management system (BMS). This interaction of different layers in the smart building with the help of a communication channel leads to exposure of layers to vulnerabilities (cyber attacks) which may lead to anomalies condition. This kind of anomalies can be avoided by proper prediction of data and coordination among different layers of the building operation. However, to develop the model for prediction of data is quite time consuming and hence, the paper proposes the concept of Dynamic Mode Decomposition (DMD) for predicting data with help of past available data even in absence of system model. In this paper temperature profile of heating, ventilation, and air conditioning (HVAC) system in BMS is predicted with the help of available past data. Once the prediction of the temperature profile is achieved the machine learning algorithm is used to classify and identify the data as normal or anomalies condition. The two-fold contribution of the paper in the prediction of temperature using DMD where all system states may not be observable and classification of data using machine learning is validated considering different test scenarios and results show the effectiveness of the DMD method in the prediction of data as well as classification using a machine learning algorithm.

Keywords: Modelling and simulation, Process control, Computational methods
Abstract: Abstract—This work focuses on the development of a computational fluid dynamic (CFD) model of a batch atomic layer deposition (ALD) process and an associated run-to-run control scheme. Specifically, a cylindrical furnace reactor is analyzed for a SiO2 thin-film ALD using BTBAS and ozone as precursors. First, a high-fidelity 2D axisymmetric multiscale CFD model for an industrial-scale furnace ALD system is developed in ANSYS Fluent to characterize the gas-phase development and the surface deposition, which is based on the previously constructed database using the kinetic Monte-Carlo (kMC) algorithm. After the validation of the multiscale CFD model, it is utilized to investigate a wide range of operating conditions, from which a regression model is developed to describe the input-output relationship between the inlet feed flow rate and the half-cycle time. Next, a run-to-run (r2r) control scheme is formulated, which uses the post-batch feedback information to adjust the operating conditions using the regression relationship and an exponentially weighted moving average (EWMA) algorithm. Finally, the multiscale CFD model and the r2r controller are integrated to generate a closed-loop system via a message passing interface (MPI) and a data synchronization scheme to evaluate the performance of the r2r controller.

Keywords: Neural networks, Robotics, Image processing
Abstract: The productivity of crop farming keeps diminishing at an alarming rate due to infestation of weeds and pests. Deep learning is becoming as the approach for identifying weeds on farmlands. However, training weed data sets with deep learning classification alone trains the whole images consisting of the weed and its background (soil) without categorically telling which particular item in the image is a weed. This makes utilising this classification approach for precision agriculture difficult. We present an alternative approach, which involves incorporating a pre-trained network in this case ResNet-50 and YOLO v2 object detector for weed detection/classification on farmlands. Thus, weeds can precisely be located, identified (type), sprayed with the appropriate herbicide or removed with the appropriate mechanism. This sums up weeding process in precision agriculture.

Keywords: Optimisation
Abstract: The resource allocation problem in case of emergency management represents a serious theme especially in the last years, when the occurrence of industrial disasters has become more frequent. Special attention has to be given to the emergency management in case of maritime or port accidents which involve hazardous material above all in MED cities where the seaport are part of the urban areas. The main challenge in emergency management is to define the optimal allocation of the available resources in timing and space in order to tackle, to mitigate and to recover effectively the hazardous event. In this paper, an optimal allocation problem has been formalized as a mathematical programming problem. The proposed model takes into account the dynamic of the first responders’ availability at each node and the dynamic behavior of the hazard event to be faced. The problem minimizes the objective function that is the combination of resource allocation, damages, and transfer costs. The resources refer to extinguishing powers which may be generated by the firefighters teams of the fire stations available at each node of the network in a cooperative emergency management prospective. The model has been tested on a case study that concerns the simultaneous occurrence of two hazardous materials accidents in two ports located in Northern Italy.

Keywords: Automotive control, Signal processing, Modelling and simulation
Abstract: This paper introduces a method for estimating the temperature of the rotor of an Induction Machine (IM) based on a feed-forward neural network used as an observation function within a particle filter. The temperature of the stator case is measured and the information is used as an input to a feed-forward network. The state transition function is a thermal model with first-order dynamics. The set-point temperature is computed out of the rotor current, stator current and angular speed. Experimental data is used from a real IM test bench and the results prove the applicability and good performances.

Keywords: Nonlinear control, Nonlinear systems, Systems biology
Abstract: In the present paper, we propose a strategy to control the crop-production of a network of agricultural plots. The network is composed of rangeland and cropland subsystems that are connected to each other through the livestock that is a vector of nutrient from rangeland to cropland. The objective is to reach a given crop production (at the scale of the whole network) while ensuring a minimal production in each of the cropland plot. To take into account the saturation constraints on the control inputs (that are the rangeland removal rates and the manure distribution coefficients), we use a method based on a time-scale transformation. After designing the control law, we apply it on a simple numerical example to highlight the results.