Keywords: Automotive Control Systems, Control Systems Design, Linear Systems
Abstract: The over-damped string stability criterion of a platooning system is a very strong stability condition. This condition not only addresses the stability in a stricter sense but also adequately captures the safety performance of the platooning system. The classical string stability condition simply ensures that any perturbation in the string does not amplify till its tail. However, this classical condition does not address the transient convergence effects such as over-shooting, under-shooting, or damped oscillating dynamics. Apart from fulfilling the classical string stability condition, the over-damped stability criterion also addresses the transient convergence dynamics. Indeed, this criterion fulfills all the L_p stability norms, where p ∈ [1, ∞]. In this paper, the importance of the over-damped string stability condition is illustrated. Here, we clearly demonstrate the unsafe dynamics of a platoon which only satisfies the classical string stability condition and how the safety is ensured if the platoon is over-damped string stable. Additionally, the performance of an over-damped string stable adaptive cruise control (ACC) vehicle model is compared with that of some commercially available ACC equipped vehicles from the OpenACC database.

Keywords: Distributed Systems, Linear Systems
Abstract: Given a smooth finite-dimensional state space system which is linear in the input, its input-output map can be represented by a Chen-Fliess series, namely, a weighted sum of iterated integrals of the input's component functions. The objective of this paper is to propose a generalized notion of a Chen-Fliess series for infinite-dimensional systems. The basic idea is to replace the real field of series coefficients with a ring of linear operators which act on the iterated integrals. The specific goals are to provide sufficient conditions for convergence of this generalized series and to exercise the theory on two specific examples: the transport equation and second-order hyperbolic partial differential equations. It will be shown in these examples that the generalized Chen-Fliess series under suitable conditions yields solutions that converge pointwise to the known classical solutions.

Keywords: Linear Systems, Cyber - Security
Abstract: Among several solutions to face the unprecedented increase of attacks towards Cyber Physical Systems, encryption plays a central role. In the form of a Proof of Concept, this contribution gives a new methodology for designing self-synchronizing automata, having in mind their use in symmetric cryptography, namely the Self-Synchronizing Stream Ciphers. The contribution of the paper is to recast the design as control theoretical issues. It calls for a graph-based approach and results borrowed from control theory and dynamical systems, in particular LPV systems. The design leads to not necessarily T-functions as state transition functions of the automata involved in the ciphering and deciphering sides. It is a consideration that is important for the sake of security. Another asset of the approach is that the resulting ciphers admit possibly vectorial inputs to enhance the throughput.

Keywords: System Identification and Modeling, Linear Systems, Industrial Applications
Abstract: In this paper, we investigate an estimation problem in a Transverse Dynamic Force Microscope (TDFM). The dynamics of its cantilever is considered for which an approximate finite dimensional model is obtained by using a truncated method. With this model, discrete-time estimators are proposed to estimate the parameters of the shear force between the cantilever and the specimen. Numerical simulations were conducted to show the effectiveness of the proposed methods.

Keywords: Linear Systems
Abstract: The concept of “componentwise asymptotic stability” ‎‎(abbreviated CWAS) was initially introduced as a special type ‎of stability for single-model linear systems, with continuous- or ‎discrete-time dynamics. Subsequently, the framework was ‎enlarged to encompass linear systems with interval-type ‎uncertainties. For both these classes of systems with ‎continuous-time dynamics, previous works show that an ‎essentially-nonnegative matrix, generically denoted U, can be ‎built as a CWAS testing instrument, which exploits the ‎equivalence between the statements “system is CWAS” and ‎‎“Perron-Frobenius eigenvalue of U is negative”. The current ‎article extends the aforementioned result to the general case of ‎linear systems with arbitrary polytopic uncertainties. A family ‎of essentially nonnegative matrices is constructed by ‎considering the row-representative theory and the matrices ‎associated with the polytope’s vertices; the CWAS testing ‎principle relies on the representative matrices (matrix) that ‎possess (possesses) the maximum Peron-Frobenius eigenvalue ‎‎(meaning the generalization of U’s role). An example based on ‎the operation of a mechanical system with polytopic ‎uncertainties illustrates the construction of the test matrix / ‎matrices and the applicability in CWAS analysis. The paper ‎focuses on continuous-time dynamics as corresponding to the ‎traditional mathematical scenario of differential equations ‎defined on compact sets, but the new result can be easily ‎adapted to discrete-time dynamics.‎

Keywords: Embedded Systems, Computer Architectures, Communication Systems
Abstract: The last decade brought up the tendency of turning every tool and device around us into a smart, autonomous, interconnected, and interoperable instrument. Autonomous driving initiative is on the verge of introducing selfdriving cars with a high level of safety. Aerospace industry delivers products which improves the flight efficiency and safety, helping the pilots take the best decisions. Astronauts are no longer required to go themselves on the Moon and to risk

their lives because smart interconnected robots can perform

very complex spatial missions. All of these wouldn’t be possible without the continuously development of the Embedded Computing. MCUs (Microcontroller Unit) and SoCs (Systems on a Chip) were permanently improved in terms of working frequency, number of processors and fast peripherals. But we reached a point when improving these parameters is not enough and the necessity of application-specific hardware accelerators and algorithms arose. A field of Embedded development which

we think is suitable for integrating an application-specific hardware unit is the CAN-FD communication. This paper describes integration of a CAN-FD Communication Unit into an ISA-extended RISC-V Core (RisCanFd CPU) and designing the MCU which embeds it, called RisCanFd. Our design includes also a debugging unit called UartDebugger which eases the development of programms for RisCanFd. For offering a modern development approach, a GUI application called RisCanFd_DebugIDE was written together with a dedicated assembler, RisCanFd_Assembler. This software tool offers both develop and debug perspectives.

Keywords: Communication Systems, Real Time Applications, Embedded Systems
Abstract: The 5G technology promises that the mobile network will be used for human-centered applications. Therefore, it will also interconnect billions of smart devices autonomously, while ensuring security, coverage, and reliability. The scope of this paper is to analyze the effect of communication distance for 5G networks. Specifically, we evaluated the performance of 5G communication between an user equipment (UE) and a 5G base station (gNb) in a dense urban area from the city of Iasi, Romania, which are at different distances from each other, such as 100 m, 200 m, 300 m, and 400 m. A practical approach was chosen to perform the measurements, using SIM8200EA-M2 module for the communication with gNB. In order to see how distance can affect the performance of the 5G network, a number of performance indicators relevant to 5G communication were analyzed, such as Reference Signal Received Power (RSRP), Signal to Interference Noise Ratio (SINR), and jitter. As expected, the results illustrate a decrease of 5G performances with an increase of the distance between the UE and the gNB.

Keywords: Signal Processing, Communication Systems, Fault Diagnosis and Fault Tolerant Control
Abstract: The aim of the paper is to estimate the Renyi entropy of time-frequency images, as descriptors of the information content and change detection purposes. The Renyi entropy is estimated by two approaches. Firstly, the image is properly normalized to estimate a probability density function. This approach is called Direct. Secondly, by using a statistical model based on probabilities, given by the histogram of the image. The approach is named Indirect. The estimation approaches are evaluated on artificially generated signals, commonly used in the field of communication engineering. Both estimations have no information about spatiality. The estimated entropies could be used as features extracted from time-frequency images. A change detection criterion is promoted based on cumulative sum function applied to the estimated entropies, followed by a double statistical expectation. The experiments show an optimum working point, to maximize the change detection criterion. The decomposition of the time-frequency image and, next, the computation of the Renyi entropy on sub-images or regions of interest, seems to be an interesting solution to follow.

Keywords: Automotive Control Systems, Embedded Systems, Cyber - Security
Abstract: This paper presents a case study for designing and implementing a secure communication protocol over a Controller Area Network (CAN). The CAN based protocol uses a hybrid encryption method on a relatively simple hardware / software environment. Moreover, the blockchain technology is proposed as working solution to provide an extra secure level of the proposed system.

Keywords: Networked Control, Communication Systems, Cyber - Security
Abstract: The paper aims to analyse high-speed Multiprotocol Label Switching (MPLS) networks, specifying the basic principles of label switching, alternative routing optimization mechanisms, error recovery problems and virtual private network implementation solutions. The main goal of MPLS is to integrate IP traffic with high-speed optical networks, which are becoming increasingly accessible. On the other hand, traffic speed is only one aspect of QoS; another key dimension is the ability to recover quickly from error. Therefore, the most important task of this paper is to optimize the use of network bandwidth without using too essential information.

Keywords: Other Topics
Abstract: This paper addresses a literature review on the sewer network modelling and control topic with the scope of identifying research gaps that, through future research, would lead to improved wastewater collecting and transport systems in terms of their impact on the environment. Recently research on sewer network modelling is focusing on data-driven models instead of mathematical ones, this technique being the more suitable one to be used in the future to also model one of the important environmental problems: emerging pollutants. The current sewer network control strategies are focusing on minimizing the overflow volume or the overflow loads, however, a balance between the two objectives must be found to reduce the overall effect. Another approach that should be considered in future research is to consider the processing capacity of the treatment facilities when developing sewer network control strategies, by implementing optimal control strategies for the integrated sewer network – wastewater treatment plant system.

Keywords: Fault Diagnosis and Fault Tolerant Control, Machine Learning, Other Topics
Abstract: Online water-quality sensors installed in Wastewater Treatment Plants (WWTPs) are prone to process disturbances that generate erroneous data. Faulty sensor data can disrupt automation systems and result in sub-optimal performance of WWTPs. This paper presents a machine-learning-based system for real-time detection and the subsequent correction of faulty sensor data installed in a full-scale municipal WWTP. The fault detection system is developed by training a k-nearest neighbour (kNN) classifier with labelled historical data. The trained kNN classifier is then deployed in the WWTP's web-based Supervisory Control And Data Acquisition (SCADA) system to assess the performance in real-time. A qualitative comparison between raw and corrected sensor data demonstrates the system's potential to detect sensor faults and provide stable and reliable surrogate values.

Keywords: Control Systems Design, Industrial Applications, Other Topics
Abstract: Wastewater treatment plants are necessary to improve the quality of wastewater before it is discharged into the receiving environment, but they have the disadvantage of generating nitrous oxide emissions during the biological treatment, which is a potent Greenhouse Gas (GHG). This is a serious drawback as the reduction of greenhouse gas emissions due to anthropogenic causes is one of the main challenges to face with reference to climate change effects. In this paper we examine one potential way to reduce nitrous oxide emissions by reducing the dissolved oxygen to minimum levels. To achieve this objective, the present work proposes to use the internal recirculation flow rate of the biological treatment. This is a rather forgotten manipulated variable that, as it is intended to show, may have potential side effects to complement already existing control actions. Therefore, this additional regulation is added to a usual control strategy in wastewater treatment plants, which achieves satisfactory results in water quality and in operational costs but with high nitrous oxide emissions. The Benchmark Simulation Model No.2 Gas (BSM2G) is used as working scenario, which includes the two main nitrous oxide emission pathways: heterotrophic denitrification and ammonia oxidizing bacteria denitrification.

Keywords: Internet of Things, Machine Learning, Predictive Control
Abstract: Monitoring water consumption has multiple benefits nowadays. Big data collected from the sensors provide a consistent basis for the decision-making processes in terms of establishing the indices and criteria needed to optimize the water demand. In this study, the data provided by four distinct water consumption outlets (hot/cold water sink, toilet, and shower) from multiple households were analyzed. A clustering analysis revealed a visual overview of the consumption events from each outlet. Then, classification methods were used to predict the source of water consumption events using four algorithms based on machine learning and deep learning. The proposed methods and results are promising towards the development of a decision support system for streamlining water consumption in urban water distribution systems.

Keywords: Optimization
Abstract: The paper deals with the optimal control of a sewer network that serves a city with a population of 250,000 inhabitants. The sewer network was modeled using BSMSewer simulation environment and contains 7 tanks, corresponding to 5 wastewater collecting areas. The first 4 tanks collect domestic polluted water and rainwater from urban areas, while the tank no. 5 collects wastewater from an industrial area. Two performance indicators were considered for optimization: the volume of overflow and the discharge quality index. Four optimization methods were approached: 1. genetic algorithm-based optimization, 2. Particle Swarm Optimization (PSO) – based algorithm, 3. optimization by random generating of the solution, 4. optimization using the FminSearch method. The results were obtained by numerical simulation and were analyzed by comparison with the situation in which no control algorithm was used (all valves of the sewer network were considered fully open to the maximum value - 100% and the pumps operate to the maximum capacity).

Keywords: Nonlinear Systems, Industrial Applications, Other Topics
Abstract: This paper investigates the observability of a baker's yeast growth model, which considers the coordinated uptake of glucose and ammonium and includes the overflow metabolism specific to yeast cultures. The observability analysis is performed based on the existence of canonical forms, which is the most employed method for bioprocesses and the results are interpreted based on the condition number of the observability matrix. Two state observers are implemented, an Extended Kalman Filter and a High Gain Observer, to reconstruct the full system state from the available measurements. Simulation results are presented for two scenarios: i) biomass, glucose and ethanol concentrations are measured; ii) only biomass concentration is measured. Only for the first scenario uniform observability could be established with the employed method. Nevertheless, in both scenarios, similar estimates of all system states were provided by both observers.

Keywords: Industrial Applications, Nonlinear Systems, Linear Systems
Abstract: The paper considers the stability analysis of the surge tank in hydroelectric power plants, in the case of elastic upstream water column, i.e. with distributed parameters tunnel. The model is obtained as a special case from a rather general hydroelectric plant structure with distributed parameters of the water flow along the conduits. The stability of the linearized model is discussed using the stability of an associated system of neutral functional differential equations via the classical results on Hurwitz quasi-polynomials obtained by N. G. Cebotarev and N. N. Meyman. Application of these results leads to an improved Thoma inequality containing a safety factor larger than 1.

Keywords: Nonlinear Systems, System Identification and Modeling, Control Systems Design
Abstract: For more than twenty years monotone systems have been used to understand the properties of dynamical systems. Particularly, those involving their decomposition, long-term behavior, and reachability. More recently, monotone decompositions of a higher dimensional embedding of dynamical systems were shown to facilitate the estimation of low complexity reachable sets. This extension to monotone systems is known as emph{mixed-monotonicity} (MM) and relies on the knowledge of systems in a state space form. The main objective of this paper is to extend this property to dynamical systems described as input/output maps using the Chen-Fliess series formalism. This formalism is free of any coordinate frame and is well-suited for data-driven analysis. Therefore, the notion of input/output mixed-monotonicity (IOMM) is introduced, and it is shown that any convergent Chen-Fliess series is IOMM. Lastly, illustrative examples of simple reachability analysis are provided showing how to use this property through an appropriate map decomposition, and how IOMM relates to MM when there is an available state space model.

Keywords: Distributed Systems, Predictive Control, Nonlinear Systems
Abstract: The major part of the execution time of distributed algorithms is required for the communication between agents. This paper approaches a reduction of the communication effort by reducing the number of edges in the considered graph. This is achieved by partitioning the graph and formulating a super graph. At first, the computational and communication effort is evaluated on an abstract level independent of the distributed algorithm, before the Alternating Direction Method of Multipliers (ADMM) is applied to a system of coupled water tanks. This allows to outline the trade-off between computation and communication time and to evaluate an optimal number of partitions that minimizes the execution time. The influence of the partitioning on the convergence behavior of the distributed algorithm is studied and compared with the concept of neighbor approximation.

Keywords: Optimization, Nonlinear Systems, Adaptive Control
Abstract: In this paper we consider the problem of swinging-up and stabilization of a rotary inverted pendulum. We design switching controllers and analyse whether the performance can be improved using more controllers. We optimize both the control gains and the switching points. All the controllers are tested experimentally on a rotary inverted pendulum. Our results indicate that having a large number of switching controllers does not necessarily lead to a performance increase.

Keywords: Control Systems Design, Nonlinear Systems, Optimization
Abstract: This paper considers the design of observer based guaranteed cost control of time-delay nonlinear systems represented by TS fuzzy models. We consider that both the states and the inputs are affected by time varying delay, which is assumed to be known. We propose conditions for observer and controller design with the aim that the closed-loop is asymptotically stable and the cost is minimized. The conditions are bilinear and we solve them in two steps. We also give different possibilities for minimizing the cost function along with a performance comparison between them. The results are validated on a numerical example.

Keywords: Software Engineering, Distributed Systems, Cloud Computing
Abstract: Automating repetitive steps in the development process of any product is an engineering desideratum. Every software product has an early development stage consisting of creating components that allow the use of a set of predefined resources. We show that this stage can be automated, with a positive impact on implementation time and the prevention of possible logical or operational errors due to the human factor.

We consider that by simply describing the entities (resources) that are to be used in the development process in a technical way, the whole source code with the implementations of CRUD operations on the previously defined resources will be obtained. The source code can be used as a starting point, reducing the time spent on repetitive details, which are usually standardized but rarely automated.

The solution is to streamline the development process of RESTful APIs, and the method chosen to make this possible is automatic generation of software components. The proposed method is based on template-based code generation (TBCG) -- creating templates that involve aggregating the code to be generated (static parts) with a high-level language (dynamic parts) that allows various operations, such as decision making, statement repetition and data transformation.

Keywords: Software Engineering
Abstract: Key classes are the most important classes of an object-oriented software system. They are usually described in project documentations or executive summaries representing the backbone of the software system. Key classes are vital in software re-engineering tasks especially in the context where poor or no documentation is maintained with the project. Thus, detecting key classes becomes an important issue. Several methods for key classes detection were reported: static code analysis, dynamic code analysis, machine learning. In a static code analysis approach the model of a weighted graph is used to represent the relations between classes like: inheritance, interface realization, field usage, return type usage etc. On the weighted graph model we run a link analysis algorithm to rank the classes in their order of importance, thus detecting the top 20 most important ones. We intend to assess the importance of class relations by generating all possible weights combinations of 0 and 1 for each class relation in the weighted graph construction. We experiment our approach on 14 analyzed systems of different sizes regarding the number of classes and from domains, like games, web servers, utilities, etc.

Keywords: Computer Science Education and Training, Signal Processing
Abstract: This paper presents a training information system for studying biomedical cardiological data. The software system examines cardiological data obtained in real conditions (electrocardiographic, photoplethysmographic, and Holter data). The interactive system is oriented toward upgrading the training of students in medicine and health care, providing an opportunity to create a preliminary experience for future medical professionals in working with different types of cardiological data. The use of photoplethysmographic and Holter data is discussed in more detail. The presented system provides an opportunity to conduct research and studies on the interaction between the heart and the functioning of the human organism. The article shows the results obtained in the analysis of cardiac data registered in healthy subjects and patients with cardiovascular disease. Graphical results (Spectrogram and Global Power Spectral Density) from the study of healthy subjects compared with the graphic results of subjects with arrhythmia are presented and discussed.

Keywords: Software Engineering
Abstract: Due to benefits such as cost savings and accuracy, automated translation of UML models to executable code is becoming more popular. However, important issues in this field include maintainability and efficiency of the produced code, as well as evaluating the consistency of UML models. This paper describes a mechanism for automatically translating UML models into code in a specific programming languages For automatic code creation, the program UML to Code employs UML class diagrams for structural reference. The program creates code structure based on the class diagram. The code generating tool is experimentally validated using a case study. The resulting code is compatible with UML models, functional, efficient and intelligible, according to the results.

Keywords: Cloud Computing, Other Topics
Abstract: Because of the low detection accuracy of low-rate Distributed Denial of Service (LDDoS) attacks in Software Defined Networks (SDN) in cloud environments, there is a lack of unified frameworks for the data plane, and control plane. To solve the problems of detection and defense against Low- rate DDoS attacks, a unified detection framework for Low-rate DDoS is proposed. The benefit behind SDN is centralizing on the controller the management of the network and the ability to use a custom application for controlling the ingress traffic. The controller issues relevant policies to block the attack flow and secure the availability of services.

Keywords: Databases and Data Mining, Computer Science Education and Training, Human - Computer Interface
Abstract: The article presents a prototype social media network dedicated to the medical staff of Romania, from the architectural and functional points of view. The medical social media network is implemented as a web application for the time being, followed by the future implementation of a mobile application as well. This network allows for the medical staff in Romania to register, log in and virtually connect, with the purpose of sharing special medical cases or getting advised opinions for setting diagnostics. Any doctor in Romania will be able to create an account, add their information about their medical department/specialty in which they activate, their former studies, obtained diplomas/specializations, former or current occupied positions, resume etc. They will have the possibility to create posts, in the form of text, accompanied by medical images if needed. Oher users will be able to comment on the added posts. Each post or comment is considered a document, stored in the database. One of the most useful functionalities of the web application is the possibility of search - simple, based on the name of a doctor; or advanced - which implies searching in posts and comments using information retrieval algorithms. The web application is based on a MongoDB database, using MongoDB Atlas search, that is an embedded full-text search, build on Apache Lucene. The medical social media network is now in the testing phase, being utilized by a group of doctors from a private clinic in Romania. The feedback gathered from this usage is taken into consideration to improve and further develop the application.

Keywords: Robotics, Manufacturing Systems, Hybrid Systems
Abstract: The main contribution of this paper is the modeling and control for a complex autonomous system (CAS). It is equipped with a visual sensor to operate precision positioning in a technology executed on a laboratory mechatronics line. The technology allows the retrieval of the workpieces which do not pass the quality test. Another objective of this paper is to present the implementation of an assisting technology digital twin based for a processing/reprocessing mechatronics line (P/RML). The P/RML has four workstations. The assisting technology is based on the complex autonomous system (CAS) composed of one autonomous robotic system (ARS), one robotic manipulator (RM) and one mobile visual servoing system (MVS). The MVS is involved in picking, transporting and placing processes of the workpieces and it aims to increase the precision of the RM operations based on the look and move principle, because the initial and final positions of the CAS can slightly deviate in the workspace, which leads to an increase in the probability of the errors to occur during the processes of catching and releasing the pieces. The reprocessing feature of the system is performed for the processed pieces that do not pass the quality test. To be reprocessed these workpieces are transferred by the CAS to the first station. The control of this complex process is presented. For this flexible manufacturing process a digital twin control is intended to be designed.

Keywords: Industrial Applications, Robotics, Real Time Applications
Abstract: The paper presents digital twin multi-functional technology for flexible production on an assembly, disassembly and repair (A/D/RML) mechatronics line assisted by a complex autonomous system (CAS). The real world consists of A/D/RML a mechatronic line (ML) with six workstations (WS) connected to a flexible cell (FC) equipped with an industrial robotic manipulator (IRM). The multifunctionality of the system is given by the three actions, assembly, disassembly and repair (the flexibility is due to the assembly of different types of products). After disassembly or repair, CAS picks up and transports the disassembled components to the appropriate storage positions for reuse. The technology works synchronously with signals from various sensors and a mobile visual servo system (VSS eye-in-hand). The virtual representation serving as a digital counterpart consists of task assignment, scheduling and A/D/RML synchronisation with integrated robotic systems. The virtual world also includes hybrid modeling and simulation with synchronized hybrid Petri nets (SHPN), VSS eye-in-hand modeling and implementation, simulation in MobileSim and graphical user interface (GUI) for real-time control monitoring, so that the whole system becomes fully automated.

Keywords: Robotics, Intelligent Systems, Computer Vision
Abstract: The correct measurement of the 3D coordinates for the workspace of different applications is a determining factor for several types of applications. This paper discusses the possibility of using the experience gained in applications such as those mentioned below as a basis for the development of applications in the field of construction. An example of an application is represented by driving mobile robots that navigate while avoiding obstacles. The mobile robot can be an intelligent wheelchair that allows the movement of people with special needs. An intelligent control system for such a mobile system can use the 3D coordinates of the workspace provided by a LIDAR sensor. Another example is the driving of mobile robots with the detection, recognition, and enforcement of the meaning of traffic signs on the route necessary for travel. In these applications, artificial intelligence techniques can be used to process the information provided by scanners and the information from digital images, respectively. Another source of information for defining a 3D workspace is the ZED camera system. From the point of view of the team that proposes this work, the approach of a scanning application for the construction field had to capitalize on the experience gained in implementing 3D scanning applications from other fields, to make the necessary adaptations, and to add the specific new and necessary elements.

Keywords: Robotics, Optimization, Embedded Systems
Abstract: This paper presents a new Simultaneous Localisation And Mapping (SLAM) method which takes into account all measurements provided by a 2D LiDAR sensor and generates a Constraint Satisfaction Problem (CSP). Interval methods are used to solve the CSP in a guaranteed way. The approach proposed in this paper does not make any assumptions about the probability distribution of the measurements and does not require any probabilistic methods for feature detection. The SLAM problem is solved in a guaranteed way by purely using only interval methods

Keywords: Control Systems Design, Manufacturing Systems, Robust Control
Abstract: In the flexible manufacturing environment some processes that until now did not need a close loop control need to be controlled so that the precision of the task permits the continuing of the manufacturing. As the processes are optimized and the manufacturing consists of multiple parallel processes, there is a need of assuring that a product is at a certain location at a certain time. In the control of a task, usually, the output of the system is measured in a timely manner at a certain sampling time. This is usually not possible in the manufacturing processes as a product position is given based on events, by sensors placed at certain locations. Certain event-based PID controllers were proposed and implemented in other control areas but in this controllers the event triggering is given by the error passing a certain level. This kind of controller cannot be implemented given the necessity of high frequency measurement of product position. In this paper we propose an PID event-base controller that uses as triggering event the activation of one of the manufacturing process sensors by the product. As the sensors are placed only in key positions the number of activations is limited. Based on these sensors the PID controller determines the necessary control signals between the key locations

Keywords: Control Systems Design, Real Time Applications, Robotics
Abstract: The purpose of this paper is to outline the development of a robust and low-cost semi-autonomous, remotely operated unmanned surface vessel (USV) used as a platform for environmental remediation technologies. By defining the shape as a catamaran, the first practical purpose is to build the collection mechanism in form of a cage to collect floating waste from rivers and lakes - in particular, plastic recipients that accumulate at the surface of the water. The unit was named „GreenCat” deriving from the purpose and the shape. Preliminary hull shape numerical investigation studies enabled carefully managed manufacturing processes resulting in a reduced manufacturing time. Based on hydrodynamic numerical simulations it is suggested that 6 km/h is an optimal travel speed. The electronic equipment was fitted and tested using two different controllers, manoeuvred by using both a radio command and a touch screen. Full-scale tests showed an autonomy of more than 60 minutes on one LiFePO04 - 12.8V- 50Ah accumulator. The hull was designed to fit several accumulators making it possible to increase the autonomy to an estimated 8 hours. The data collected from the LiDAR system provided key information for the next level of autonomy, where obstacles can be avoided and the USV can charge automatically in a charging dock.

Keywords: Control Systems Design, System Identification and Modeling, Nonlinear Systems
Abstract: In this paper, the design and validation of 20 Control System (CS) structures for the level control cof Vertical Three Tank Systems (V3TSs) is presented. At first a TP model and four linear models are derived for a V3TS. Next, five CS structures are designed for each model consisting in a Tensor Product (TP) controller and four state feedback controllers tuned using linear matrix inequalities and the parallel distributed compensation technique. Finally, in order to ensure zero steady–state control error, the five CS structures were included in Cascade Control System (CCS) structures with Proportional–Integral–Derivative (PID) controller in the outer control loop. All CS structures were tested in the same experimental scenario and a comparative analysis was also conducted by computing two performance indices, namely the mean square error and the settling time. The experimental results have shown that, unlike the TP–based CS structures, the CCS structures with PID controller in the outer control loop ensure better performance in terms of zero steady–state control error.

Keywords: Adaptive Control, Control Systems Design, Fault Diagnosis and Fault Tolerant Control
Abstract: This paper treats the problem of actuator fault detection observer for positive switched systems via average dwell time approach in discrete time case. With consideration of robustness conditions, the generated residual is sensitive to faults while robust against unknown input. This paper proposes a novel mixed L_/L_1 actuator fault detection observer design approach for positive switched systems. Besides, sufficient conditions are derived as linear programming. Numerical example is used to illustrate the effectiveness of the proposed method.

Keywords: Control Systems Design, Robust Control, Linear Systems
Abstract: This article presents a Permanent Magnet Synchronous Motor (PMSM) control system which retains its performance for a significant variation of the parameters and load torque which represent disturbance for the control system. Classically, the PMSM control system is built in the form of a Field Oriented Control (FOC) control structure built around PI speed and current controllers. We present the design stages and the numerical simulations performed in Matlab/Simulink, which prove the superiority of the robust control, by comparison with the classic FOC-type control structure. Because the Reinforcement Learning Twin-Delayed Deep Deterministic Policy Gradient (RL-TD3) agent is the most suitable for machine learning for process control, we synthesize a robust controller whose control quantities ud and uq are adjusted by a properly created and trained RL-TD3 agent. Using this robust combined controller plus RL-TD3 agent, superior performance is achieved in terms of response time and speed ripple.

Keywords: Control Systems Design, System Identification and Modeling, Linear Systems
Abstract: DC/DC converters are used to adapt different voltage levels between power sources and loads. The buck converter, also known as step-down converter, is a very common converter type. This converters allows the reduction of the input voltage. We suggest an alternative topology, where the reactive lumped elements of the buck converter are replaced by a transmission line. This results in a distributed converter model with new properties. We discuss the analysis, simulation and implementation of such a converter.

Keywords: Control Systems Design, Nonlinear Systems, Adaptive Control
Abstract: ‎This paper investigates the motion tracking problem for piezoelectric actuators (PEAs) using a sampled-data control method known as sampled-data model-free adaptive control (SMFAC)‎. ‎The fundamental architecture of the proposed scheme is based on input-output data‎, ‎and the sampling period is an integral part of the design‎. ‎PEA with the Bouc-Wen hysteresis model is first considered to obtain a sampled-data nonlinear model using the integral mean value theorem and the discrete-time Euler approximation‎. ‎Then‎, ‎a sampled-data control rule subject to input rate constraint is constructed by applying a sampled-data extended state observer (SESO) and a sampled-data parameter estimation technique‎. ‎The SESO is used to estimate the unknown residual nonlinearity and external disturbances‎. ‎The convergence of the tracking error is proven through theoretical analysis‎. ‎Experimental results confirm the adequate performance of the proposed scheme‎.

Keywords: Adaptive Control, Control Systems Design, Biomedical Engineering
Abstract: The treatment of brain tumor requires advanced strategies depending on the severity of tumors. For instance, in case of malignant tumors surgery is not advisable since these tumors are attached very closely with the sensitive tissues of brain, rather chemotherapy treatment is suggested. In this work, two nonlinear controllers have been designed to determine the amount of chemotherapy to remove the tumor cells and retain suitable quantity of healthy and immune cells: the adaptive super-twisting sliding mode and the adaptive terminal sliding mode controllers. System stability and convergence have been verified by the use of Lyapunov stability theory. The performance of the controllers has been verified by the use of MATLAB software on the basis of different control parameters. Adaptive terminal sliding mode controller appears more appealing for its convergence and the reduced chattering, allowing at the same time a reduced amount of drug.

Keywords: Control Systems Design, Manufacturing Systems, Modeling, Simulation and CAD Tools
Abstract: Continuous manufacturing represents a flow production method in which the processed materials are in continuous movement between the interconnected operating units involved in the production process. This method has been adopted in many industries, e.g., electrical components, automotive or food production due to increased needs and higher quality of the resulting products. Continuous manufacturing is a first step towards transforming industrial processes into cyber-physical systems (CPSs). In case of pharma industry, recent studies revealed the benefits of transforming batch production into continuous manufacturing, related to product quality, lower fabrication costs and reduced production times. Among the advantages of continuous manufacturing, regardless of industry, is an increase in efficiency, enabled by maximum automation through the interconnection of operation units. As such, this paper proposes a control strategy based on Linear Quadratic Regulator (LQR) with Integral action (LQI) for the production of pharmaceutical tablets. Moreover, the control architecture has been extended by using an observer to estimate the unknown states of the system. The simulation results obtained on a Matlab/Simulink-based pilot plant and the performance analysis prove that this method is suitable for the dry granulation process.

Keywords: Machine Learning, Computer Vision, Other Topics
Abstract: The paper addresses the detection of floating and underwater marine mines from images recorded from cameras (taken from drones, submarines, ships, boats). Due to the lack of image data sets, images were taken from the Internet and using the technique of augmentation and synthetic image generation (by overlapping images with different types of mines over water backgrounds) 2 data sets were built (for me floating and for me underwater). The networks were trained and compared 3 types of Deep Learning networks Yolov5, SSD and EfficientDet (Yolov5, SSD for floating mines and Yolov5 and EfficientDet for underwater mines). Networks were also tested in the context of an IoT device (RaspberryPi 4, RPi camera).

Keywords: Databases and Data Mining, Machine Learning, Theory of Algorithms
Abstract: This paper examines the effect of lockdown measures on population mobility during the COVID-19 pandemic in Romania. Many countries, including Romania, have adopted quarantine and isolation for infected people trying to stop the virus transmission and the rapid escalation of the number of cases, which has put great pressure on hospitals. These measures have slowed down the economy leading to the loss of jobs with a massive impact on people's psychology by increasing panic or anxiety. Mobility data is used as a measurement representation of the social distancing and therefore, combining mobility data sets with COVID-19 related data might support the analysis between the virus effects and mobility and, correspondingly, the population mobility impact on virus transmission. It is undeniable that the imposed restrictions have influenced the business environment, our aim being to investigate the relationship between the number of COVID-19 cases, the virus reproduction rate and the changes in mobility towards retail outlets and workplaces.

Keywords: Computer Vision, Machine Learning
Abstract: In this paper we are analyzing the sensitivity of deep semantic segmentation networks output with respect to input image augmentations. Our goal is to introduce a new method for measuring the sensitivity of deep neural networks doing semantic segmentation and thus determine how stable these networks are when image alterations are encountered during real life image capturing. To achieve our goal, we construct a sensitivity analysis model and apply it to some commonly used semantic segmentation CNN architectures (PSPNet, ICNet, DeepLabV3) across a couple types of image degradations. Extrapolating the results we obtain would allow for estimating various CNN models performance for new domains comprised by images of lower quality (captured with different types of camera or light conditions). Our specific experiments for semantic segmentation task revealed that DeepLabV3 is more stable to input image degradations than PSPNet and ICNet. However, for some object classes even DeepLabV3 is seriously affected by the input noise.

Keywords: Machine Learning, Real Time Applications, Other Topics
Abstract: Still in the inception of Web 3.0, the present study stands as an important incursion into the future of the Internet and displays how different technologies, Social Media and Cryptocurrencies, can influence each other and the world around them in these new, exciting, times. This paper seeks to find if there is a relationship between Twitter Sentiment and Bitcoin price. To this end, data is collected and preprocessed to construct a dataset consisting of two time series, one for Twitter Sentiment regarding Bitcoin and one for Bitcoin Price. The relationship between the two is studied through a Vector Autoregressive model. The results show that each exerts influence on the other. Twitter Sentiment is quicker to absorb the information, while Bitcoin Price takes longer to intake the most recent events. Future avenues of study are identified, with topic analysis of Bitcoin discourse being highlighted due to its potential to unlock new knowledge.

Keywords: Machine Learning, Computer Vision, Other Topics
Abstract: People with Alzheimer's are at risk for malnutrition, overeating and dehydration because short-term memory loss can be confusing. They need a caregiver to make sure they adhere to the main meals of the day and are properly hydrated. The purpose of this paper is to present the need for a developed surveillance system that has the role of regaining their independence through artificial intelligence. The system is based on a unique concept that involves the use of artificial intelligence to recognize human activity in video. The system identifies the times when the monitored person is feeding or hydrating and reminds them by sound messages that they forgot to eat, drink or eat too much. It also allows for the remote supervision and management of the nutrition program by a caregiver. The paper includes the study, search, training and use of models and algorithms specific to the field of artificial vision in order to classify images, detect objects in images and recognize human activity in video. The study shows that artificial intelligence used to help people with Alzheimer's is a new concept, but a real help for both them and their caregivers

Keywords: Machine Learning, Intelligent Systems, Optimization
Abstract: Neural networks have demonstrated their potential for solving a wide range of real-world problems. While capable of learning correlations and relationships among complex datasets, neural network training and validation are often tedious and time-consuming, especially for large, high-dimensional datasets, given that sufficient models should be run through the validation pipeline so as to adequately cover the hyperparameter space. In order to address this problem, we propose a weight adjustment method for improving training times when searching for the optimal neural network architecture by incorporating a knowledge transfer step into the corresponding pipeline. This involves learning weight features from a trained model and using them to improve the training times of a subsequent one. Considering a sequence of candidate neural networks with different hyperparameter values, each model, once trained, serves as a source of knowledge for the next one, resulting in improved overall training times. We test our approach on dataset of various sizes, where we obtain reduced total training times, especially when small learning rates are used for finely-tuned convergence.

Keywords: Machine Learning, Computer Vision, Intelligent Systems
Abstract: Single image super-resolution algorithms aim to increase the resolution of an input image without deteriorating its visual perception. With a strong ability to understand the structure of an image, convolutional neural networks (CNNs) are successfully applied to this problem. Previous studies have shown that human perception is mainly influenced by variations in luminance. In this regard, this paper introduces two CNNs that operate only on the luminance channel, at low computational costs. Each model provides an end-to-end mapping between a low-resolution (LR) and a high-resolution (HR) map. Because upsampling is integrated into CNN, the design allows the control of HR image quality. In addition, the neural architectures can be configured with many layers operating with small LR feature maps, to provide fast run-time image processing. The approach is exemplified in two cases: generate the HR map or a residual map for the luminance channel; the residual map should be added to the map upsampled by interpolation. Besides having improved time performance, the two models can produce HR images with high NIQE scores, as shown experimentally.

Keywords: Control Systems Design, Modeling, Simulation and CAD Tools, Robotics
Abstract: The paper presents the control system of two medical instruments used in percutaneous cancer treatment. One instrument is designed for radiofrequency ablation and the other one for brachytherapy. The instruments may be attached to various robots capable of providing 5 Degrees of Freedom. Two robotic solutions are used for exemplifying this capability, namely the Kuka iiwa robot and the PARA-BRACHYROB. The developed control system is capable to communicate with both robots using MATLAB environment and different communication protocols to establish the connections between the robot control units.

Keywords: Nonlinear Systems, Robotics, Control Systems Design
Abstract: This paper deals with the trajectory tracking control problem of a serial four-link manipulator in order to design a controller which globally stabilizes the desired motion of the robot without velocity measurements. We use the dynamic model of the manipulator described by Euler-Lagrange equations. The output position dynamic feedback controller has been proposed on the base of Lyapunov functions method. We exploit the periodicity property of the manipulator dynamic equations with respect to the rotational angles of the robot links. More precisely, we obtain the solution to the global trajectory tracking control problem in a cylindrical phase space. Global attractivity and uniform asymptotic stability properties of the closed-loop system are achieved. Simulation results are provided to show the quality of the controller.

Keywords: Manufacturing Systems, Robust Control, Networked Control
Abstract: This paper addresses a preliminary study of perishable inventory management (PIM). The aim is the development of a robust and efficient control algorithm tacking into account the stock deterioration and its replenishment subject to a delay from a remote supply source and reacting significantly faster to the consumer’s demand, which is considered as unknown disturbance. Here, instead of model-based control strategies, through a continuous, local identification of the level variations a model-free control that does not need any prior knowledge of the supply chain behaviors is proposed. The control policy not only explicitly takes account the transportation losses which could appear between the suppliers and the final customers, but also accounts for decay of goods stored in warehouse (perishing inventories) and prevents from exceeding the facilities capacities.

Keywords: Robotics, Intelligent Systems, Automotive Control Systems
Abstract: This paper deals with the implementation and an assessment of loop-closing techniques for an EKF-SLAM. Here, especially the minimization of uncertainties of the vehicle pose and of the global map are in the scope of interest. Therefore, different approaches of loop-closing are integrated in the framework of an extended Kalman Filter implementation for the SLAM problem. In particular, the detection of a loop closure as well as its impact on the accuracies of both robot pose and global map will be presented. Experimental results are obtained from a Turtlebot3 robot operating in a lab environment.

Keywords: Robotics, Discrete Event Systems
Abstract: This work considers the problem of decomposing a global motion specification given to a team of robots into parts that can be individually followed by agents, without any need of communication among them. The specification is given as a co-safe Linear Temporal Logic (LTL) formula over some regions of interest from a known and static environment. The main contribution is an algorithmic method for distributing the specification, while identifying necessary sequencing relations among some regions to be visited. Each of these sequences has to be assigned to a robot, and the concurrent movement of the agents accomplishes the global imposed mission.

Keywords: Robotics
Abstract: The significant evolution of perception over humanoid robots had led to a great development of applications in different areas. The most engaging interactions between humans and robots involve visual and auditive communication which can be achieved using cameras due to their rich sensory information. The main focus of the Pepper robot is to amuse users and make their daily routines better. The objective of the application would be to observe Pepper's behavior in the scenario of a humanoid-robot appointment system and to develop a corresponding optimal approach.

Keywords: Robotics, Nonlinear Systems, Biologically Inspired Systems
Abstract: This paper deals with the issue of autonomous indoors navigation related to Unmanned Aerial Vehicles. Here, we simulated two hexarotors: a fully-actuated one that maintains level its attitude, and therefore that of the visual sensors; and an under-actuated one. Both vehicles were meant to fly forwards in a tunnel while reacting to the irregularities of the terrain, adopting a bee-like behavior based on a nonlinear optic flow regulation. The dynamic models are provided by means of the Newton-Euler equations, nonetheless, the unit quaternion representation is used for a suitable treatment of the rotational motion. The attitude stabilization depends on the knowledge of the quaternion itself, moreover, and due to the non-linearities related to the translational optic flows, visual guidance relies on the implementation of adaptive integral sliding mode controllers to accomplish a triple direct regulation (forward, side and lift commands). We compared both vehicles performance using detailed numerical simulations, validating the concept that a fully actuated hexarotor permits to improve the optic flow based navigation task.