Pub Date : 2022-06-28DOI: 10.1109/MED54222.2022.9837285
F. Koumboulis, N. Kouvakas
Motivated by the control problem of a robot tracked vehicle, the problem of common noninteracting control with simultaneous partial output zeroing is introduced and solved for the case of multi model normal linear time invariant systems, using a regular and static measurement output feedback controller. The necessary and sufficient conditions for the solvability of the problem are established, and the general solution of the controllers is derived. The present design results are successfully applied to the two-model description of the robot tracked vehicle, through a common controller, using only measurements of the motor currents and the orientation of the vehicle. Additionally, approximate asymptotic command following is achieved. Finally, using a metaheuristic algorithm the transient behavior of the independently controlled outputs, is improved.
{"title":"A Common Noninteracting Control Design for Robot Tracked Vehicles*","authors":"F. Koumboulis, N. Kouvakas","doi":"10.1109/MED54222.2022.9837285","DOIUrl":"https://doi.org/10.1109/MED54222.2022.9837285","url":null,"abstract":"Motivated by the control problem of a robot tracked vehicle, the problem of common noninteracting control with simultaneous partial output zeroing is introduced and solved for the case of multi model normal linear time invariant systems, using a regular and static measurement output feedback controller. The necessary and sufficient conditions for the solvability of the problem are established, and the general solution of the controllers is derived. The present design results are successfully applied to the two-model description of the robot tracked vehicle, through a common controller, using only measurements of the motor currents and the orientation of the vehicle. Additionally, approximate asymptotic command following is achieved. Finally, using a metaheuristic algorithm the transient behavior of the independently controlled outputs, is improved.","PeriodicalId":354557,"journal":{"name":"2022 30th Mediterranean Conference on Control and Automation (MED)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115696922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-28DOI: 10.1109/MED54222.2022.9837165
Erfaun Noorani, C. Somarakis, R. Goyal, A. Feldman, S. Rane
AI-enabled mechanisms are deployed to guard controlled systems against sensor anomalies. We explore a two-level architecture design in which a low-level feedback controller of a linear system uses measurements from one or more potentially unreliable sensors. These observations are prone both to sensor noise but unknown additive faults. Our proposed, high-level, guard mechanism consists of a Reinforcement Learning (RL) agent that monitors available vitals of the system. In the event of a fault on the sensor components, the RL agent automatically detects, estimates the fault, localizes and takes action to cancel the fault. In addition, we develop design methodologies for efficient training of the RL agent that take advantage of system dynamics and sensor fusion schemes. We show that the associated training cost functions can be designed so that their optimal policy achieves efficient of arbitrary constant or piece-wise constant sensor faults. To illustrate our theoretical results, we consider a linearized version of a chemical process with multiple sensors, controlled by a Linear Quadratic Gaussian (LQG) Servo-Controller with Integral Action. Our simulations show that the RL-agent is successful in localizing the faulty sensors and mitigating the effects of faults in an online fashion.
{"title":"Learning-Based Diagnostics for Fault Detection and Isolation in Linear Stochastic Systems","authors":"Erfaun Noorani, C. Somarakis, R. Goyal, A. Feldman, S. Rane","doi":"10.1109/MED54222.2022.9837165","DOIUrl":"https://doi.org/10.1109/MED54222.2022.9837165","url":null,"abstract":"AI-enabled mechanisms are deployed to guard controlled systems against sensor anomalies. We explore a two-level architecture design in which a low-level feedback controller of a linear system uses measurements from one or more potentially unreliable sensors. These observations are prone both to sensor noise but unknown additive faults. Our proposed, high-level, guard mechanism consists of a Reinforcement Learning (RL) agent that monitors available vitals of the system. In the event of a fault on the sensor components, the RL agent automatically detects, estimates the fault, localizes and takes action to cancel the fault. In addition, we develop design methodologies for efficient training of the RL agent that take advantage of system dynamics and sensor fusion schemes. We show that the associated training cost functions can be designed so that their optimal policy achieves efficient of arbitrary constant or piece-wise constant sensor faults. To illustrate our theoretical results, we consider a linearized version of a chemical process with multiple sensors, controlled by a Linear Quadratic Gaussian (LQG) Servo-Controller with Integral Action. Our simulations show that the RL-agent is successful in localizing the faulty sensors and mitigating the effects of faults in an online fashion.","PeriodicalId":354557,"journal":{"name":"2022 30th Mediterranean Conference on Control and Automation (MED)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114946119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-28DOI: 10.1109/MED54222.2022.9837252
Danilo Menegatti, A. Giuseppi, A. Pietrabissa
A collision-free formation control strategy for flying in formation is presented. A linear control law is developed by means of Model Predictive Control (MPC) via the dual-mode paradigm [1]. Collision avoidance is dealt with by using Artificial Potential Functions (APFs) to keep a desired safe distance from the obstacles. The main innovation in the proposed approach is that each spacecraft independently performs the collision avoidance manoeuvres and, as a consequence, the APFs-based collision avoidance control is in charge also of the collision avoidance between two spacecraft. The optimality of the solution is discussed and numerical simulations show the effectiveness of the proposed method.
{"title":"Model Predictive Control for Collision-free Spacecraft Formation with Artificial Potential Functions","authors":"Danilo Menegatti, A. Giuseppi, A. Pietrabissa","doi":"10.1109/MED54222.2022.9837252","DOIUrl":"https://doi.org/10.1109/MED54222.2022.9837252","url":null,"abstract":"A collision-free formation control strategy for flying in formation is presented. A linear control law is developed by means of Model Predictive Control (MPC) via the dual-mode paradigm [1]. Collision avoidance is dealt with by using Artificial Potential Functions (APFs) to keep a desired safe distance from the obstacles. The main innovation in the proposed approach is that each spacecraft independently performs the collision avoidance manoeuvres and, as a consequence, the APFs-based collision avoidance control is in charge also of the collision avoidance between two spacecraft. The optimality of the solution is discussed and numerical simulations show the effectiveness of the proposed method.","PeriodicalId":354557,"journal":{"name":"2022 30th Mediterranean Conference on Control and Automation (MED)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116054638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-28DOI: 10.1109/MED54222.2022.9837145
S. D. Takloo, A. Farhadi, A. Khaki‐Sedigh
This paper is concerned with state tracking as well as reference tracking of noisy nonlinear dynamic systems over Additive White Gaussian Noise (AWGN) channel, which is subject to transmission noise imperfection and transmission power constraint. In order to address these problems, in this paper we implement a suitable linearization method. Using this method, we linearize the nonlinear dynamic system around working points and for linearized systems, we present proper encoder and decoder for tracking the state trajectory of nonlinear dynamic systems at the end of communication link when sensor measurements are sent through the AWGN channel subject to imperfection and constraint. The satisfactory performance of the proposed state and reference tracking techniques are illustrated via computer simulations by applying these techniques on the unicycle model, which is an abstract representation for the nonlinear dynamics of autonomous vehicles.
{"title":"Control and Measurement of Nonlinear Dynamic Systems over AWGN Channel with Application in Tele-operation of Autonomous Vehicles","authors":"S. D. Takloo, A. Farhadi, A. Khaki‐Sedigh","doi":"10.1109/MED54222.2022.9837145","DOIUrl":"https://doi.org/10.1109/MED54222.2022.9837145","url":null,"abstract":"This paper is concerned with state tracking as well as reference tracking of noisy nonlinear dynamic systems over Additive White Gaussian Noise (AWGN) channel, which is subject to transmission noise imperfection and transmission power constraint. In order to address these problems, in this paper we implement a suitable linearization method. Using this method, we linearize the nonlinear dynamic system around working points and for linearized systems, we present proper encoder and decoder for tracking the state trajectory of nonlinear dynamic systems at the end of communication link when sensor measurements are sent through the AWGN channel subject to imperfection and constraint. The satisfactory performance of the proposed state and reference tracking techniques are illustrated via computer simulations by applying these techniques on the unicycle model, which is an abstract representation for the nonlinear dynamics of autonomous vehicles.","PeriodicalId":354557,"journal":{"name":"2022 30th Mediterranean Conference on Control and Automation (MED)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128241241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-28DOI: 10.1109/MED54222.2022.9837125
Laura Sopegno, P. Livreri, M. Stefanovic, K. Valavanis
The paper focuses on developing, tuning, and testing a controller for a two-stage finless rocket during its boost phase that is based on the Linear Quadratic Regulator (LQR) optimal control method. This is accomplished by deriving and adopting a simplified rigid body rocket model that represents accurately its physical properties and the corresponding aerodynamic forces acting on the rocket system during the flight phase. The launcher is commanded through the control input thrust gimbal angle δ to the desired altitude using the implemented LQR-based controller. Emphasis is given to the Thrust Vector Control (TVC) system, and to the minimization of the drift caused by wind gust disturbance phenomena, which may result in a sideway motion of the rocket, and, consequently, in deviating from its desired trajectory; this is addressed, and it is overcome by considering the output parameters expressed in terms of the pitch angle, pitch rate (or angular body rate) and drift. The linearized state-space model is validated for analysis and design compensation of the pitch control logic of the ascent flight control system. The derived algorithm is, then, implemented in a Matlab/Simulink setting to demonstrate that the LQR controller provides closed-loop dynamic tracking, while the tuning of the LQR controller through the weighting matrices Q and R allows for simulating and testing how the variation of the gain directly impacts the performance of the closed-loop system and, in turn, the controller.
{"title":"Linear Quadratic Regulator: A Simple Thrust Vector Control System for Rockets","authors":"Laura Sopegno, P. Livreri, M. Stefanovic, K. Valavanis","doi":"10.1109/MED54222.2022.9837125","DOIUrl":"https://doi.org/10.1109/MED54222.2022.9837125","url":null,"abstract":"The paper focuses on developing, tuning, and testing a controller for a two-stage finless rocket during its boost phase that is based on the Linear Quadratic Regulator (LQR) optimal control method. This is accomplished by deriving and adopting a simplified rigid body rocket model that represents accurately its physical properties and the corresponding aerodynamic forces acting on the rocket system during the flight phase. The launcher is commanded through the control input thrust gimbal angle δ to the desired altitude using the implemented LQR-based controller. Emphasis is given to the Thrust Vector Control (TVC) system, and to the minimization of the drift caused by wind gust disturbance phenomena, which may result in a sideway motion of the rocket, and, consequently, in deviating from its desired trajectory; this is addressed, and it is overcome by considering the output parameters expressed in terms of the pitch angle, pitch rate (or angular body rate) and drift. The linearized state-space model is validated for analysis and design compensation of the pitch control logic of the ascent flight control system. The derived algorithm is, then, implemented in a Matlab/Simulink setting to demonstrate that the LQR controller provides closed-loop dynamic tracking, while the tuning of the LQR controller through the weighting matrices Q and R allows for simulating and testing how the variation of the gain directly impacts the performance of the closed-loop system and, in turn, the controller.","PeriodicalId":354557,"journal":{"name":"2022 30th Mediterranean Conference on Control and Automation (MED)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128379492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-28DOI: 10.1109/MED54222.2022.9837158
F. Bateman, F. Niel
Centrality measures evaluate the importance of vertices in a graph. In a multi-agent framework i.e. robots swarm, computing these indicators may be useful in identifying a leader. As a first step, the paper deals with a centrality measure based on the analysis of the eigenvector associated with the largest eigenvalue of the Laplacian matrix. For the studied class of graphs, this centrality measure highlights the most connected vertex which is also associated with the largest binding energy. The results are established for complement of trees. For these highly connected graphs, the most popular centrality measures make hard to distinguish an important vertex. On the contrary, the proposed indicator distinctly highlights this vertex. As a second step, for a network of autonomous agents, the leader identification problem based on this centrality measure is solved in a decentralized way. All the agents cooperate to appoint their leader. The calculations are conducted in the frequency domain and are based on maximum-consensus functions.
{"title":"Centrality Measure Based on the Laplacian Matrix Spectral Radius Eigenvector Application to the Identification of a Leader","authors":"F. Bateman, F. Niel","doi":"10.1109/MED54222.2022.9837158","DOIUrl":"https://doi.org/10.1109/MED54222.2022.9837158","url":null,"abstract":"Centrality measures evaluate the importance of vertices in a graph. In a multi-agent framework i.e. robots swarm, computing these indicators may be useful in identifying a leader. As a first step, the paper deals with a centrality measure based on the analysis of the eigenvector associated with the largest eigenvalue of the Laplacian matrix. For the studied class of graphs, this centrality measure highlights the most connected vertex which is also associated with the largest binding energy. The results are established for complement of trees. For these highly connected graphs, the most popular centrality measures make hard to distinguish an important vertex. On the contrary, the proposed indicator distinctly highlights this vertex. As a second step, for a network of autonomous agents, the leader identification problem based on this centrality measure is solved in a decentralized way. All the agents cooperate to appoint their leader. The calculations are conducted in the frequency domain and are based on maximum-consensus functions.","PeriodicalId":354557,"journal":{"name":"2022 30th Mediterranean Conference on Control and Automation (MED)","volume":"1202 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129653709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-28DOI: 10.1109/MED54222.2022.9837269
R. Lamouchi, M. Amairi, T. Raïssi, M. Aoun
In this paper, zonotopic fault detection methodology is proposed for a class of discrete-time Linear Parameter Varying (LPV) systems with sensor faults. The disturbances and measurement noise are assumed to be unknown but bounded by zonotope. First, a fault detection observer is designed based on L∞ performance to attenuate the effects of the uncertainties and to improve the accuracy of the proposed residual framers. Then, the fault sensitivity is taken into account by measuring $mathcal{H}_$ performance and zonotopic residual evaluation is presented. Finally, the effectiveness of the proposed method is demonstrated by a numerical example.
{"title":"Robust Fault Detection based on Zonotopic Observers for Linear Parameter Varying Systems","authors":"R. Lamouchi, M. Amairi, T. Raïssi, M. Aoun","doi":"10.1109/MED54222.2022.9837269","DOIUrl":"https://doi.org/10.1109/MED54222.2022.9837269","url":null,"abstract":"In this paper, zonotopic fault detection methodology is proposed for a class of discrete-time Linear Parameter Varying (LPV) systems with sensor faults. The disturbances and measurement noise are assumed to be unknown but bounded by zonotope. First, a fault detection observer is designed based on L∞ performance to attenuate the effects of the uncertainties and to improve the accuracy of the proposed residual framers. Then, the fault sensitivity is taken into account by measuring $mathcal{H}_$ performance and zonotopic residual evaluation is presented. Finally, the effectiveness of the proposed method is demonstrated by a numerical example.","PeriodicalId":354557,"journal":{"name":"2022 30th Mediterranean Conference on Control and Automation (MED)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130412659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-28DOI: 10.1109/MED54222.2022.9837280
Syed Saad Saif, Kerem Aras, A. Giuseppi
Automated Optical Inspection (AOI) is among the most common and effective quality checks employed in production lines. This paper details the design of a Deep Learning solution that was developed for addressing a specific quality control in a Printed Circuit Board Assembly (PCBA) manufacturing process. The developed Deep Neural Network exploits transfer learning and a synthetic data generation process to be trained even if the quantity of the data samples available is low. The overall AOI system was designed to be deployed on low-cost hardware with limited computing capabilities to ease its deployment in industrial settings.
{"title":"Automated Optical Inspection for Printed Circuit Board Assembly Manufacturing with Transfer Learning and Synthetic Data Generation","authors":"Syed Saad Saif, Kerem Aras, A. Giuseppi","doi":"10.1109/MED54222.2022.9837280","DOIUrl":"https://doi.org/10.1109/MED54222.2022.9837280","url":null,"abstract":"Automated Optical Inspection (AOI) is among the most common and effective quality checks employed in production lines. This paper details the design of a Deep Learning solution that was developed for addressing a specific quality control in a Printed Circuit Board Assembly (PCBA) manufacturing process. The developed Deep Neural Network exploits transfer learning and a synthetic data generation process to be trained even if the quantity of the data samples available is low. The overall AOI system was designed to be deployed on low-cost hardware with limited computing capabilities to ease its deployment in industrial settings.","PeriodicalId":354557,"journal":{"name":"2022 30th Mediterranean Conference on Control and Automation (MED)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126994727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-28DOI: 10.1109/MED54222.2022.9837148
E. D. Santis, F. Liberati, A. Giorgio
In this paper we consider the problem of controlling a service area hosting stations for the provisioning of the electric vehicles fast charging service, having the support of an electric energy storage system and local power production from renewables. Key aspects motivating the work are the hard temporal constraint imposed by drivers requiring the fast charging service and the impact high aggregated power withdrawal has on the economic viability of the investment for the service area operator; consequently key control requirements include a congestion level driven tracking of the charging power demand and the flattening of power flow at the point of connection of the service area to the electricity grid, while keeping stable ESS operation. These opposing control objectives, together with the uncertain nature of the power demand and production, brings to the formulation of a stochastic model predictive control problem, based on a continuous/finite-time optimal control problem, for which the explicit form of solution is determined. Simulations are presented to validate the proposed approach.
{"title":"Optimal Control of a Grid-connected Service Area for Plug-in Electric Vehicles Fast Charging under uncertain Power Demand","authors":"E. D. Santis, F. Liberati, A. Giorgio","doi":"10.1109/MED54222.2022.9837148","DOIUrl":"https://doi.org/10.1109/MED54222.2022.9837148","url":null,"abstract":"In this paper we consider the problem of controlling a service area hosting stations for the provisioning of the electric vehicles fast charging service, having the support of an electric energy storage system and local power production from renewables. Key aspects motivating the work are the hard temporal constraint imposed by drivers requiring the fast charging service and the impact high aggregated power withdrawal has on the economic viability of the investment for the service area operator; consequently key control requirements include a congestion level driven tracking of the charging power demand and the flattening of power flow at the point of connection of the service area to the electricity grid, while keeping stable ESS operation. These opposing control objectives, together with the uncertain nature of the power demand and production, brings to the formulation of a stochastic model predictive control problem, based on a continuous/finite-time optimal control problem, for which the explicit form of solution is determined. Simulations are presented to validate the proposed approach.","PeriodicalId":354557,"journal":{"name":"2022 30th Mediterranean Conference on Control and Automation (MED)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121145849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-28DOI: 10.1109/MED54222.2022.9837250
R. Tornese, Edoardo Polimeno, Claudio Pascarelli, Stefania Buccoliero, L. Carlino, Emanuele Sansebastiano, L. Sebastiani
Real-time simulators are useful tools for the development and validation of complex systems such as naval ships, aircraft or land vehicles, requiring over time more rigorous testing and integration as these systems become more and more complex. Hardware-in-the-loop simulation (HILS) is a well established technique used for a rapid and economical validation of both hardware and software sections of the developed architecture. This paper describes the design and execution of a hardware-in-the-loop simulator developed to test a maritime autonomous collision avoidance system (CAS) as well as some notable test cases to study the behaviour of the model. The HILS system is composed by a programmable logic controller (PLC) linked to two personal computers, one responsible for hosting the Linux system running the ROS Path Planner, the other for simulating the current scenario and the ship model.
{"title":"Hardware-in-the-loop testing of a maritime autonomous collision avoidance system","authors":"R. Tornese, Edoardo Polimeno, Claudio Pascarelli, Stefania Buccoliero, L. Carlino, Emanuele Sansebastiano, L. Sebastiani","doi":"10.1109/MED54222.2022.9837250","DOIUrl":"https://doi.org/10.1109/MED54222.2022.9837250","url":null,"abstract":"Real-time simulators are useful tools for the development and validation of complex systems such as naval ships, aircraft or land vehicles, requiring over time more rigorous testing and integration as these systems become more and more complex. Hardware-in-the-loop simulation (HILS) is a well established technique used for a rapid and economical validation of both hardware and software sections of the developed architecture. This paper describes the design and execution of a hardware-in-the-loop simulator developed to test a maritime autonomous collision avoidance system (CAS) as well as some notable test cases to study the behaviour of the model. The HILS system is composed by a programmable logic controller (PLC) linked to two personal computers, one responsible for hosting the Linux system running the ROS Path Planner, the other for simulating the current scenario and the ship model.","PeriodicalId":354557,"journal":{"name":"2022 30th Mediterranean Conference on Control and Automation (MED)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121292763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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