Pub Date : 2024-06-13DOI: 10.1109/TCST.2024.3410138
Tongjia Zheng;Zhenyuan Yuan;Mollik Nayyar;Alan R. Wagner;Minghui Zhu;Hai Lin
Emergency evacuation describes a complex situation involving time-critical decision-making by evacuees. Mobile robots are being actively explored as a potential solution to provide timely guidance. This work studies a robot-guided crowd evacuation problem where a small group of robots is used to guide a large human crowd to safe locations. The challenge lies in how to use microlevel human-robot interactions to indirectly influence a population that significantly outnumbers the robots to achieve the collective evacuation objective. To address the challenge, we follow a two-scale modeling strategy and explore hydrodynamic models, which consist of a family of microscopic social force models that describe how human movements are locally affected by other humans, the environment, and robots, and associated macroscopic equations for the temporal and spatial evolution of the crowd density and flow velocity. We design controllers for the robots, such that they not only automatically explore the environment (with unknown dynamic obstacles) to cover it as much as possible, but also dynamically adjust the directions of their local navigation force fields based on the real-time macrostates of the crowd to guide the crowd to a safe location. We prove the stability of the proposed evacuation algorithm and conduct extensive simulations to investigate the performance of the algorithm with different combinations of human numbers, robot numbers, and obstacle settings.
{"title":"Multirobot-Guided Crowd Evacuation: Two-Scale Modeling and Control","authors":"Tongjia Zheng;Zhenyuan Yuan;Mollik Nayyar;Alan R. Wagner;Minghui Zhu;Hai Lin","doi":"10.1109/TCST.2024.3410138","DOIUrl":"10.1109/TCST.2024.3410138","url":null,"abstract":"Emergency evacuation describes a complex situation involving time-critical decision-making by evacuees. Mobile robots are being actively explored as a potential solution to provide timely guidance. This work studies a robot-guided crowd evacuation problem where a small group of robots is used to guide a large human crowd to safe locations. The challenge lies in how to use microlevel human-robot interactions to indirectly influence a population that significantly outnumbers the robots to achieve the collective evacuation objective. To address the challenge, we follow a two-scale modeling strategy and explore hydrodynamic models, which consist of a family of microscopic social force models that describe how human movements are locally affected by other humans, the environment, and robots, and associated macroscopic equations for the temporal and spatial evolution of the crowd density and flow velocity. We design controllers for the robots, such that they not only automatically explore the environment (with unknown dynamic obstacles) to cover it as much as possible, but also dynamically adjust the directions of their local navigation force fields based on the real-time macrostates of the crowd to guide the crowd to a safe location. We prove the stability of the proposed evacuation algorithm and conduct extensive simulations to investigate the performance of the algorithm with different combinations of human numbers, robot numbers, and obstacle settings.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"32 6","pages":"2194-2206"},"PeriodicalIF":4.9,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-10DOI: 10.1109/TCST.2024.3407582
Kimberly J. Chan;Joel A. Paulson;Ali Mesbah
The digital age has made embedded control a key component to user-oriented, portable, and the Internet of Things (IoT) devices. In addition, with emergent complex systems, there is a need for advanced optimization-based control strategies such as model predictive control (MPC). However, the unified implementation of these advanced strategies on hardware remains a challenge. Designing complex control policies for embedded systems is inherently an interwoven process between the algorithmic design and hardware implementation, which will require a hardware-software co-design perspective. We propose an end-to-end framework for the automated design and tuning of arbitrary control policies on arbitrary hardware. The proposed framework relies on deep learning as a universal control policy representation and multiobjective Bayesian optimization (MOBO) to facilitate iterative systematic controller design. The large representation power of deep learning and its ability to decouple hardware and software design are a central component to determining feasible control-on-a-chip (CoC) policies. Then, Bayesian optimization (BO) provides a flexible sequential decision-making framework where practical considerations, such as multiobjective optimization (MOO) concepts and categorical decisions, can be incorporated to efficiently design embedded control policies that are directly implemented on hardware. We demonstrate the proposed framework via closed-loop simulations and real-time experiments on an atmospheric pressure plasma jet (APPJ) for plasma processing of biomaterials.
{"title":"A Practical Multiobjective Learning Framework for Optimal Hardware-Software Co-Design of Control-on-a-Chip Systems","authors":"Kimberly J. Chan;Joel A. Paulson;Ali Mesbah","doi":"10.1109/TCST.2024.3407582","DOIUrl":"10.1109/TCST.2024.3407582","url":null,"abstract":"The digital age has made embedded control a key component to user-oriented, portable, and the Internet of Things (IoT) devices. In addition, with emergent complex systems, there is a need for advanced optimization-based control strategies such as model predictive control (MPC). However, the unified implementation of these advanced strategies on hardware remains a challenge. Designing complex control policies for embedded systems is inherently an interwoven process between the algorithmic design and hardware implementation, which will require a hardware-software co-design perspective. We propose an end-to-end framework for the automated design and tuning of arbitrary control policies on arbitrary hardware. The proposed framework relies on deep learning as a universal control policy representation and multiobjective Bayesian optimization (MOBO) to facilitate iterative systematic controller design. The large representation power of deep learning and its ability to decouple hardware and software design are a central component to determining feasible control-on-a-chip (CoC) policies. Then, Bayesian optimization (BO) provides a flexible sequential decision-making framework where practical considerations, such as multiobjective optimization (MOO) concepts and categorical decisions, can be incorporated to efficiently design embedded control policies that are directly implemented on hardware. We demonstrate the proposed framework via closed-loop simulations and real-time experiments on an atmospheric pressure plasma jet (APPJ) for plasma processing of biomaterials.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"32 6","pages":"2178-2193"},"PeriodicalIF":4.9,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-07DOI: 10.1109/TCST.2024.3403512
Andrea Serrani
The sixth IEEE Conference on Control Technology and Applications (CCTA 2022) took place at the Stazione Marittima, Trieste, Italy, from August 23 to 25, 2022, with technical workshops held on August 22, 2022. This event was conducted as a hybrid format, offering both in-person and virtual participation, marking the first hybrid conference sponsored by the IEEE Control Systems Society (CSS), since the COVID-19 pandemic. The CCTA 2022 was organized in collaboration with the Society for Instrument and Control Engineers and co-sponsored by the European Control Association. The CCTA 2022 is the premier event of the CSS focusing on advancements in systems and control technologies and applications. This peculiar focus of the conference establishes a natural connection with the IEEE Transactions on Control Systems Technology (TCST). Two initiatives were introduced in the CCTA 2022 to nourish this kindred relationship between the premier application-oriented journal and conference of the CSS. Authors of recently published papers in TCST that have not been previously presented at the CCTA were encouraged to give oral presentations of their work at the conference. Furthermore, the authors of the selected articles presented at the CCTA 2022 were invited to submit extended versions of their work for consideration in this special section of the September 2024 Issue of the TCST dedicated to the conference.
{"title":"Guest Editorial: Special Section on Invited Papers From the 2022 IEEE Conference on Control Technology and Applications (CCTA 2022)","authors":"Andrea Serrani","doi":"10.1109/TCST.2024.3403512","DOIUrl":"10.1109/TCST.2024.3403512","url":null,"abstract":"The sixth IEEE Conference on Control Technology and Applications (CCTA 2022) took place at the Stazione Marittima, Trieste, Italy, from August 23 to 25, 2022, with technical workshops held on August 22, 2022. This event was conducted as a hybrid format, offering both in-person and virtual participation, marking the first hybrid conference sponsored by the IEEE Control Systems Society (CSS), since the COVID-19 pandemic. The CCTA 2022 was organized in collaboration with the Society for Instrument and Control Engineers and co-sponsored by the European Control Association. The CCTA 2022 is the premier event of the CSS focusing on advancements in systems and control technologies and applications. This peculiar focus of the conference establishes a natural connection with the IEEE Transactions on Control Systems Technology (TCST). Two initiatives were introduced in the CCTA 2022 to nourish this kindred relationship between the premier application-oriented journal and conference of the CSS. Authors of recently published papers in TCST that have not been previously presented at the CCTA were encouraged to give oral presentations of their work at the conference. Furthermore, the authors of the selected articles presented at the CCTA 2022 were invited to submit extended versions of their work for consideration in this special section of the September 2024 Issue of the TCST dedicated to the conference.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"32 5","pages":"1538-1539"},"PeriodicalIF":4.9,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10552102","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fractional-order systems have proven to be useful to well model diffusion or propagation phenomena. Recursive or online system identification of continuous-time fractional models is explored in this article. When differentiation orders are known, only the coefficients are to be estimated: the classic recursive methods of least squares, prediction error method (PEM), and instrumental variable are adapted for fractional models. They are then compared to our new long memory PEM to prove its efficiency. When differentiation orders are unknown, which is often the case in practice, two-stage algorithms are proposed for both coefficient and differentiation order estimation. A single method of differentiation order estimation is proposed, which is then combined with the two best coefficient estimation methods (long-memory PEM and instrumental variable) to create two hybrid algorithms. The performances of these algorithms are compared through Monte Carlo simulations in order to highlight the influence of the parameter estimation in a more complex scenario. Finally, recursive identification is applied to a simulation example of a thermal lung impedance.
{"title":"Recursive System Identification of Continuous-Time Fractional Systems for All Parameter Estimation","authors":"Jean-François Duhé;Stéphane Victor;Pierre Melchior;Youssef Abdelmoumen;François Roubertie","doi":"10.1109/TCST.2024.3407580","DOIUrl":"10.1109/TCST.2024.3407580","url":null,"abstract":"Fractional-order systems have proven to be useful to well model diffusion or propagation phenomena. Recursive or online system identification of continuous-time fractional models is explored in this article. When differentiation orders are known, only the coefficients are to be estimated: the classic recursive methods of least squares, prediction error method (PEM), and instrumental variable are adapted for fractional models. They are then compared to our new long memory PEM to prove its efficiency. When differentiation orders are unknown, which is often the case in practice, two-stage algorithms are proposed for both coefficient and differentiation order estimation. A single method of differentiation order estimation is proposed, which is then combined with the two best coefficient estimation methods (long-memory PEM and instrumental variable) to create two hybrid algorithms. The performances of these algorithms are compared through Monte Carlo simulations in order to highlight the influence of the parameter estimation in a more complex scenario. Finally, recursive identification is applied to a simulation example of a thermal lung impedance.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"32 6","pages":"2037-2049"},"PeriodicalIF":4.9,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-06DOI: 10.1109/TCST.2024.3405711
Zao Fu;Carlo Cenedese;Michele Cucuzzella;Wenwu Yu;Jacquelien M. A. Scherpen
In this article, we consider a dc microgrid composed of distributed generation units (DGUs) trading energy among each other, where the energy price depends on the total current generated by all the DGUs. We then use a Cournot aggregative game to describe the self-interested interaction among the DGUs, where each DGU aims at minimizing the deviation with respect to the given reference signals and maximizing the revenue from the sale of the generated power. Thus, we design a fully distributed continuous-time equilibrium-seeking algorithm to compute the generalized Nash equilibrium (GNE) of the game. We interconnect the designed decision-making algorithm with the dynamics of the microgrid in a passive way, and, by leveraging passivity theory, we prove the convergence of the closed-loop system trajectory to a feasible operating point that is also a Nash equilibrium of the collective aggregative game. Finally, we present extensive simulation results that validate the proposed distributed optimal control scheme, showing excellent performance.
{"title":"Distributed Control of Islanded DC Microgrids: A Passivity-Based Game Theoretical Approach","authors":"Zao Fu;Carlo Cenedese;Michele Cucuzzella;Wenwu Yu;Jacquelien M. A. Scherpen","doi":"10.1109/TCST.2024.3405711","DOIUrl":"10.1109/TCST.2024.3405711","url":null,"abstract":"In this article, we consider a dc microgrid composed of distributed generation units (DGUs) trading energy among each other, where the energy price depends on the total current generated by all the DGUs. We then use a Cournot aggregative game to describe the self-interested interaction among the DGUs, where each DGU aims at minimizing the deviation with respect to the given reference signals and maximizing the revenue from the sale of the generated power. Thus, we design a fully distributed continuous-time equilibrium-seeking algorithm to compute the generalized Nash equilibrium (GNE) of the game. We interconnect the designed decision-making algorithm with the dynamics of the microgrid in a passive way, and, by leveraging passivity theory, we prove the convergence of the closed-loop system trajectory to a feasible operating point that is also a Nash equilibrium of the collective aggregative game. Finally, we present extensive simulation results that validate the proposed distributed optimal control scheme, showing excellent performance.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"32 6","pages":"2207-2222"},"PeriodicalIF":4.9,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10551425","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-06DOI: 10.1109/tcst.2024.3400571
Rudolf Reiter, Rien Quirynen, Moritz Diehl, Stefano Di Cairano
{"title":"Equivariant Deep Learning of Mixed-Integer Optimal Control Solutions for Vehicle Decision Making and Motion Planning","authors":"Rudolf Reiter, Rien Quirynen, Moritz Diehl, Stefano Di Cairano","doi":"10.1109/tcst.2024.3400571","DOIUrl":"https://doi.org/10.1109/tcst.2024.3400571","url":null,"abstract":"","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"8 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-21DOI: 10.1109/tcst.2024.3400570
Eunjeong Hyeon, Priyash Misra, Dominik Karbowski
{"title":"A Large-Scale Analysis to Optimize the Control and V2V Communication Protocols for CDA Agreement-Seeking Cooperation","authors":"Eunjeong Hyeon, Priyash Misra, Dominik Karbowski","doi":"10.1109/tcst.2024.3400570","DOIUrl":"https://doi.org/10.1109/tcst.2024.3400570","url":null,"abstract":"","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"30 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141152472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-30DOI: 10.1109/TCST.2024.3393211
Javier A. Gallegos;Francisco Rubio;Javier Pereda;Felipe Núñez
Modularity, understood as the property that allows a complex system to be decomposed into well-defined compartments, is a distinctive element in modern engineering systems. Modularity increases scalability, facilitates mass production, and simplifies maintenance. Nonetheless, modular systems may exhibit complex dynamics, and the establishment of their structural properties can be challenging. In this brief, observability and observer-based control for a class of modular nonlinear systems are analyzed, with particular focus on the modular multilevel power converter. Analytical conditions to verify observability are given, a separation principle that enables observer-based control is formulated, and an experimental validation on a pilot-scale converter is conducted to corroborate the analytical findings.
{"title":"Observability and Observed-Based Control for a Class of Output Modular Systems With Application to Modular Multilevel Power Converters","authors":"Javier A. Gallegos;Francisco Rubio;Javier Pereda;Felipe Núñez","doi":"10.1109/TCST.2024.3393211","DOIUrl":"10.1109/TCST.2024.3393211","url":null,"abstract":"Modularity, understood as the property that allows a complex system to be decomposed into well-defined compartments, is a distinctive element in modern engineering systems. Modularity increases scalability, facilitates mass production, and simplifies maintenance. Nonetheless, modular systems may exhibit complex dynamics, and the establishment of their structural properties can be challenging. In this brief, observability and observer-based control for a class of modular nonlinear systems are analyzed, with particular focus on the modular multilevel power converter. Analytical conditions to verify observability are given, a separation principle that enables observer-based control is formulated, and an experimental validation on a pilot-scale converter is conducted to corroborate the analytical findings.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"32 6","pages":"2418-2427"},"PeriodicalIF":4.9,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140831215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We address the problem of coverage of a given environment by a team of quadrotor unmanned aerial vehicles (UAVs) with limited sensing capabilities. The objective is to develop a control strategy for spreading the UAVs across the environment for monitoring purposes. We do not assume the availability of a central controller for UAV coordination, and the UAVs cooperate by exchanging information via a communication network. By considering possible cyberattacks acting on the UAV network, we propose a resilient distributed control scheme such that the UAVs locally compute their position set points to achieve an overall coverage configuration despite the malicious behaviors of some attacked UAVs. By relying on the Voronoi diagram-based coverage technique, we first address possible attack scenarios that can deteriorate a covering mission. Then, we consider a generalized Voronoi diagram-based coverage scheme that shows resilience against cyberattack scenarios. We also design an adaptive control strategy ensuring the convergence of the UAVs to a desired coverage configuration, whereas the UAV parameters (inertial matrix, drag coefficient, and so on) are not known. Mathematical analysis, simulation, and real-world experimental results show the effectiveness of the proposed distributed resilient control scheme.
{"title":"Resilient Coverage by Teams of Quadrotor UAVs: Theory and Experiments","authors":"Hamed Rezaee;Erica Salvato;Gianfranco Fenu;Thomas Parisini","doi":"10.1109/TCST.2024.3389350","DOIUrl":"10.1109/TCST.2024.3389350","url":null,"abstract":"We address the problem of coverage of a given environment by a team of quadrotor unmanned aerial vehicles (UAVs) with limited sensing capabilities. The objective is to develop a control strategy for spreading the UAVs across the environment for monitoring purposes. We do not assume the availability of a central controller for UAV coordination, and the UAVs cooperate by exchanging information via a communication network. By considering possible cyberattacks acting on the UAV network, we propose a resilient distributed control scheme such that the UAVs locally compute their position set points to achieve an overall coverage configuration despite the malicious behaviors of some attacked UAVs. By relying on the Voronoi diagram-based coverage technique, we first address possible attack scenarios that can deteriorate a covering mission. Then, we consider a generalized Voronoi diagram-based coverage scheme that shows resilience against cyberattack scenarios. We also design an adaptive control strategy ensuring the convergence of the UAVs to a desired coverage configuration, whereas the UAV parameters (inertial matrix, drag coefficient, and so on) are not known. Mathematical analysis, simulation, and real-world experimental results show the effectiveness of the proposed distributed resilient control scheme.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"32 6","pages":"2009-2022"},"PeriodicalIF":4.9,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140799396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This brief addresses the global regulation of torque-driven flexible joint robots with input constraints. It is reported a nonlinear control scheme with bounded actions that guarantees global asymptotic stability despite input saturation, matched and unmatched disturbances, and parametric uncertainties. The control system has a double loop in a cascade configuration, where the outer loop has an integral (I) action driven by the joint deflection error. In addition, the inner loop has a nonlinear proportional-integral-derivative (PID-type) structure. Hence, an I-PID-type controller is obtained. The design methodology is based on a linear change of coordinates of the joint deflection and motor errors that allows the conclusion of global asymptotic stability via Lyapunov theory and the Barbashin–Krasovskii theorem. Sufficient conditions are explicitly stated and given in the form of matrix inequalities. Real-time experiments on a two-degrees-of-freedom flexible joint manipulator confirm the viability of the proposed controller, which exhibits better performance than the other two control algorithms.
{"title":"Global Regulation of Flexible Joint Robots With Input Saturation by Nonlinear I-PID-Type Control","authors":"Jerónimo Moyrón;Javier Moreno-Valenzuela;Jesus Sandoval","doi":"10.1109/TCST.2024.3391129","DOIUrl":"10.1109/TCST.2024.3391129","url":null,"abstract":"This brief addresses the global regulation of torque-driven flexible joint robots with input constraints. It is reported a nonlinear control scheme with bounded actions that guarantees global asymptotic stability despite input saturation, matched and unmatched disturbances, and parametric uncertainties. The control system has a double loop in a cascade configuration, where the outer loop has an integral (I) action driven by the joint deflection error. In addition, the inner loop has a nonlinear proportional-integral-derivative (PID-type) structure. Hence, an I-PID-type controller is obtained. The design methodology is based on a linear change of coordinates of the joint deflection and motor errors that allows the conclusion of global asymptotic stability via Lyapunov theory and the Barbashin–Krasovskii theorem. Sufficient conditions are explicitly stated and given in the form of matrix inequalities. Real-time experiments on a two-degrees-of-freedom flexible joint manipulator confirm the viability of the proposed controller, which exhibits better performance than the other two control algorithms.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"32 6","pages":"2385-2393"},"PeriodicalIF":4.9,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140799461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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