Pub Date : 2025-02-07DOI: 10.1016/j.sysconle.2025.106043
Jun-Jun Liu , Ning Peng , Jun-Min Wang
In this paper, we apply internal model principle (IMP) and the adaptive frequency estimation strategy to achieve output tracking for a one-dimensional wave equation with velocity recirculation and unknown harmonic disturbances. The disturbances are present in all channels, and both the disturbances and the reference trajectory have an unknown sinusoidal form. We first construct an auxiliary system and a proper trajectory such that total disturbances appear only in the output of the auxiliary. As a result, we obtain a dynamic estimation of the total disturbances by constructing an internal model dynamics. An adaptive method is proposed to determine the uncertain parameters. In order to realize exponential output tracking, the proposed error-based adaptive dynamic compensator is employed. Finally, some simulation examples are carried out to validate the results.
{"title":"Adaptive output regulation for wave PDEs with a nonlocal term and unknown harmonic disturbances","authors":"Jun-Jun Liu , Ning Peng , Jun-Min Wang","doi":"10.1016/j.sysconle.2025.106043","DOIUrl":"10.1016/j.sysconle.2025.106043","url":null,"abstract":"<div><div>In this paper, we apply internal model principle (IMP) and the adaptive frequency estimation strategy to achieve output tracking for a one-dimensional wave equation with velocity recirculation and unknown harmonic disturbances. The disturbances are present in all channels, and both the disturbances and the reference trajectory have an unknown sinusoidal form. We first construct an auxiliary system and a proper trajectory such that total disturbances appear only in the output of the auxiliary. As a result, we obtain a dynamic estimation of the total disturbances by constructing an internal model dynamics. An adaptive method is proposed to determine the uncertain parameters. In order to realize exponential output tracking, the proposed error-based adaptive dynamic compensator is employed. Finally, some simulation examples are carried out to validate the results.</div></div>","PeriodicalId":49450,"journal":{"name":"Systems & Control Letters","volume":"197 ","pages":"Article 106043"},"PeriodicalIF":2.1,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143360804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-02-06DOI: 10.1016/j.sysconle.2025.106029
Pietro Lorenzetti, George Weiss
We discuss some useful properties of the solution map (flow) of a nonlinear dynamical system with a finite-dimensional state space. Then, we introduce the Perron–Frobenius semigroup, and we prove that it is a positive strongly continuous semigroup of contractions. We show that, given a nonlinear system and an invariant set, this set is an almost global attractor if and only if certain Perron–Frobenius semigroups associated to the nonlinear system are strongly stable. Unlike other works on the Perron–Frobenius semigroup from the literature, we do not require the existence of a compact and invariant state-space for the dynamical system, we allow trajectories with finite escape time, and we do not require the attractor to be locally (Lyapunov) stable. Two simple examples are used throughout the paper to illustrate the theory.
{"title":"The strong stability of the Perron–Frobenius semigroup and almost global attractivity","authors":"Pietro Lorenzetti, George Weiss","doi":"10.1016/j.sysconle.2025.106029","DOIUrl":"10.1016/j.sysconle.2025.106029","url":null,"abstract":"<div><div>We discuss some useful properties of the solution map (flow) of a nonlinear dynamical system with a finite-dimensional state space. Then, we introduce the Perron–Frobenius semigroup, and we prove that it is a positive strongly continuous semigroup of contractions. We show that, given a nonlinear system and an invariant set, this set is an almost global attractor if and only if certain Perron–Frobenius semigroups associated to the nonlinear system are strongly stable. Unlike other works on the Perron–Frobenius semigroup from the literature, we do not require the existence of a compact and invariant state-space for the dynamical system, we allow trajectories with finite escape time, and we do not require the attractor to be locally (Lyapunov) stable. Two simple examples are used throughout the paper to illustrate the theory.</div></div>","PeriodicalId":49450,"journal":{"name":"Systems & Control Letters","volume":"197 ","pages":"Article 106029"},"PeriodicalIF":2.1,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143314896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-02-06DOI: 10.1016/j.sysconle.2025.106030
Hannes Gernandt , Manuel Schaller
In this note, we consider port-Hamiltonian structures in numerical optimal control of ordinary differential equations. By introducing a novel class of nonlinear monotone port-Hamiltonian (pH) systems, we show that the primal–dual gradient method may be viewed as an infinite-dimensional nonlinear pH system. The monotonicity and the particular block structure arising in the optimality system is used to prove exponential stability of the dynamics towards its equilibrium, which is a critical point of the first-order optimality conditions. Leveraging the port-based modeling, we propose an optimization-based controller in a suboptimal receding horizon control fashion. To this end, the primal–dual gradient based optimizer-dynamics is coupled to a pH plant dynamics in a power-preserving manner. We show that the resulting model is again monotone pH system and prove that the closed-loop exhibits local exponential convergence towards the equilibrium.
{"title":"Port-Hamiltonian structures in infinite-dimensional optimal control: Primal–Dual gradient method and control-by-interconnection","authors":"Hannes Gernandt , Manuel Schaller","doi":"10.1016/j.sysconle.2025.106030","DOIUrl":"10.1016/j.sysconle.2025.106030","url":null,"abstract":"<div><div>In this note, we consider port-Hamiltonian structures in numerical optimal control of ordinary differential equations. By introducing a novel class of nonlinear monotone port-Hamiltonian (pH) systems, we show that the primal–dual gradient method may be viewed as an infinite-dimensional nonlinear pH system. The monotonicity and the particular block structure arising in the optimality system is used to prove exponential stability of the dynamics towards its equilibrium, which is a critical point of the first-order optimality conditions. Leveraging the port-based modeling, we propose an optimization-based controller in a suboptimal receding horizon control fashion. To this end, the primal–dual gradient based optimizer-dynamics is coupled to a pH plant dynamics in a power-preserving manner. We show that the resulting model is again monotone pH system and prove that the closed-loop exhibits local exponential convergence towards the equilibrium.</div></div>","PeriodicalId":49450,"journal":{"name":"Systems & Control Letters","volume":"197 ","pages":"Article 106030"},"PeriodicalIF":2.1,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143314897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-02-05DOI: 10.1016/j.sysconle.2025.106027
Ilyasse Lamrani , Imad El Harraki , Fatima-Zahrae El Alaoui
This paper considers the problem of stabilizing a class of non-scalar coupled parabolic equations controlled by a single multiplicative control. We show that if the associated linear system is null controllable, then the solution of the considered system can be locally superexponentially stabilized towards specific trajectories, referred to as eigen-trajectories. To resolve the null controllability issue, we reformulate it as a moment problem and apply two separate sets of assumptions on the eigenvalues. Some applications are presented to illustrate the obtained results.
{"title":"Rapid stabilization of parabolic coupled system","authors":"Ilyasse Lamrani , Imad El Harraki , Fatima-Zahrae El Alaoui","doi":"10.1016/j.sysconle.2025.106027","DOIUrl":"10.1016/j.sysconle.2025.106027","url":null,"abstract":"<div><div>This paper considers the problem of stabilizing a class of non-scalar coupled parabolic equations controlled by a single multiplicative control. We show that if the associated linear system is null controllable, then the solution of the considered system can be locally superexponentially stabilized towards specific trajectories, referred to as eigen-trajectories. To resolve the null controllability issue, we reformulate it as a moment problem and apply two separate sets of assumptions on the eigenvalues. Some applications are presented to illustrate the obtained results.</div></div>","PeriodicalId":49450,"journal":{"name":"Systems & Control Letters","volume":"197 ","pages":"Article 106027"},"PeriodicalIF":2.1,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143171854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-02-04DOI: 10.1016/j.sysconle.2025.106032
Jiamin Wang , Jian Liu , Feng Xiao , Ning Xi , Lipo Mo , Yuanshi Zheng
Motivated by widespread dominance hierarchy, variations of group sizes, and feedback mechanisms in social species, we are devoted to exploring the scalable second-order consensus of hierarchical groups. More specifically, a hierarchical group consists of a collection of agents with double-integrator dynamics on a directed acyclic graph with additional reverse edges, which characterize feedback mechanisms across hierarchical layers. As the group size varies and the reverse edges appear, we investigate whether the absolute velocity protocol and the relative velocity protocol can preserve the system consensus property without tuning the control gains. It is rigorously proved that the absolute velocity protocol is able to achieve completely scalable second-order consensus but the relative velocity protocol cannot. This result theoretically reveals how the scalable coordination behavior in hierarchical groups is determined by local interaction rules. Moreover, we find a hierarchical structure in order to achieve scalable second-order consensus for networks of any size and with any number of reverse edges.
{"title":"Scalable second-order consensus of hierarchical groups","authors":"Jiamin Wang , Jian Liu , Feng Xiao , Ning Xi , Lipo Mo , Yuanshi Zheng","doi":"10.1016/j.sysconle.2025.106032","DOIUrl":"10.1016/j.sysconle.2025.106032","url":null,"abstract":"<div><div>Motivated by widespread dominance hierarchy, variations of group sizes, and feedback mechanisms in social species, we are devoted to exploring the scalable second-order consensus of hierarchical groups. More specifically, a hierarchical group consists of a collection of agents with double-integrator dynamics on a directed acyclic graph with additional reverse edges, which characterize feedback mechanisms across hierarchical layers. As the group size varies and the reverse edges appear, we investigate whether the absolute velocity protocol and the relative velocity protocol can preserve the system consensus property without tuning the control gains. It is rigorously proved that the absolute velocity protocol is able to achieve completely scalable second-order consensus but the relative velocity protocol cannot. This result theoretically reveals how the scalable coordination behavior in hierarchical groups is determined by local interaction rules. Moreover, we find a hierarchical structure in order to achieve scalable second-order consensus for networks of any size and with any number of reverse edges.</div></div>","PeriodicalId":49450,"journal":{"name":"Systems & Control Letters","volume":"197 ","pages":"Article 106032"},"PeriodicalIF":2.1,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143172466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-02-03DOI: 10.1016/j.sysconle.2025.106023
Fan Zhang , Cui-Li Jin , Weiguo Xia , Xi-Ming Sun , He Bai
In this paper, we propose a novel cooperative pointing control framework for multi-robot systems subject to one target. The existing approach exploits the geometric relations among neighboring robots and the target to design cooperative pointing controllers, which involves intricate geometric analysis and hinders us from applications in complex environments. Herein, all the robots and the target are stationary within the same plane, and their deployment is arbitrary. Besides, each robot knows its own global position. Without loss of generality, we assume that, two leader robots already point at the target and the three of them are not collinear. This setup in fact determines the target’s position implicitly, which but is unknown to the two leader robots as well as others. We thus design a distributed estimator to yield an asymptotic estimate of the target’s position at each robot, which gives the asymptotic estimate of the desired orientation angle for each non-leader robot. However, the estimate of the desired orientation angle follows specific geometric relations from the estimate of the target’s position that cannot be equal to the position of the corresponding robot. A state-dependent switching strategy is employed to enable the distributed target estimator to stay away from this singularity. Through tracking the estimate of the desired orientation angle, each non-leader robot regulates its own orientation angle to point to the target asymptotically. Finally, numerical simulations are presented to illustrate the validity of this framework.
{"title":"Cooperative pointing control of multi-robot systems via distributed target estimation","authors":"Fan Zhang , Cui-Li Jin , Weiguo Xia , Xi-Ming Sun , He Bai","doi":"10.1016/j.sysconle.2025.106023","DOIUrl":"10.1016/j.sysconle.2025.106023","url":null,"abstract":"<div><div>In this paper, we propose a novel cooperative pointing control framework for multi-robot systems subject to one target. The existing approach exploits the geometric relations among neighboring robots and the target to design cooperative pointing controllers, which involves intricate geometric analysis and hinders us from applications in complex environments. Herein, all the robots and the target are stationary within the same plane, and their deployment is arbitrary. Besides, each robot knows its own global position. Without loss of generality, we assume that, two leader robots already point at the target and the three of them are not collinear. This setup in fact determines the target’s position implicitly, which but is unknown to the two leader robots as well as others. We thus design a distributed estimator to yield an asymptotic estimate of the target’s position at each robot, which gives the asymptotic estimate of the desired orientation angle for each non-leader robot. However, the estimate of the desired orientation angle follows specific geometric relations from the estimate of the target’s position that cannot be equal to the position of the corresponding robot. A state-dependent switching strategy is employed to enable the distributed target estimator to stay away from this singularity. Through tracking the estimate of the desired orientation angle, each non-leader robot regulates its own orientation angle to point to the target asymptotically. Finally, numerical simulations are presented to illustrate the validity of this framework.</div></div>","PeriodicalId":49450,"journal":{"name":"Systems & Control Letters","volume":"197 ","pages":"Article 106023"},"PeriodicalIF":2.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143171858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-02-03DOI: 10.1016/j.sysconle.2025.106026
Shuaichen Geng , Yaning Lin , Weihai Zhang
This paper studies the Stackelberg–Nash strategy for the discrete-time mean-field stochastic systems with two followers. First, utilizing two pairs of generalized difference Riccati equations, a non-zero sum mean-field stochastic difference game is solved for two followers and the Nash equilibrium solution is obtained. Then, the leader settles the optimization problem of a mean-field forward-backward stochastic difference equation. Necessary and sufficient condition for the solvability is put forward. Moreover, feedback representation of Stackelberg–Nash strategy is obtained by introducing new state and costate variables. Finally, two examples are given to verify the effectiveness of the proposed results.
{"title":"Stackelberg–Nash solution to the mean-field stochastic difference game with two followers","authors":"Shuaichen Geng , Yaning Lin , Weihai Zhang","doi":"10.1016/j.sysconle.2025.106026","DOIUrl":"10.1016/j.sysconle.2025.106026","url":null,"abstract":"<div><div>This paper studies the Stackelberg–Nash strategy for the discrete-time mean-field stochastic systems with two followers. First, utilizing two pairs of generalized difference Riccati equations, a non-zero sum mean-field stochastic difference game is solved for two followers and the Nash equilibrium solution is obtained. Then, the leader settles the optimization problem of a mean-field forward-backward stochastic difference equation. Necessary and sufficient condition for the solvability is put forward. Moreover, feedback representation of Stackelberg–Nash strategy is obtained by introducing new state and costate variables. Finally, two examples are given to verify the effectiveness of the proposed results.</div></div>","PeriodicalId":49450,"journal":{"name":"Systems & Control Letters","volume":"197 ","pages":"Article 106026"},"PeriodicalIF":2.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143171857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-02-02DOI: 10.1016/j.sysconle.2025.106028
Elnaz Firouzmand, H.A. Talebi, Iman Sharifi
This paper develops a resilient hierarchical control structure for cyber–physical systems (CPSs) using an extended resilient approximate simulation function. Data transmission through wireless communication channels in CPSs is vulnerable to cyber-attacks. Furthermore, these systems may be modeled using linear dynamics with high-state dimensions. Hence, the control synthesis problem for concrete systems is computationally challenging. The extended resilient approximate simulation function introduced in this paper enables the use of an abstract system for computationally efficient controller design. This function is mathematically defined as the sum of the resilient approximate simulation function between the abstract model and the unknown input observer (UIO), and the simple approximate simulation function between the UIO and the concrete system. Accordingly, the controller can first be designed for the abstract system and then refined for the concrete system by introducing an appropriate interface controller. This controller constitutes an observer-based robust control law based on to guarantee the desired performance despite external disturbances and includes an adaptive compensator to mitigate the effect of attacks on the simulation relation. The applicability of the presented approach is demonstrated through two case studies: load frequency control in a power system and frequency regulation in an isolated area of the New England 39-Bus Test System.
{"title":"Resilient abstraction-based hierarchical control of linear systems","authors":"Elnaz Firouzmand, H.A. Talebi, Iman Sharifi","doi":"10.1016/j.sysconle.2025.106028","DOIUrl":"10.1016/j.sysconle.2025.106028","url":null,"abstract":"<div><div>This paper develops a resilient hierarchical control structure for cyber–physical systems (CPSs) using an extended resilient approximate simulation function. Data transmission through wireless communication channels in CPSs is vulnerable to cyber-attacks. Furthermore, these systems may be modeled using linear dynamics with high-state dimensions. Hence, the control synthesis problem for concrete systems is computationally challenging. The extended resilient approximate simulation function introduced in this paper enables the use of an abstract system for computationally efficient controller design. This function is mathematically defined as the sum of the resilient approximate simulation function between the abstract model and the unknown input observer (UIO), and the simple approximate simulation function between the UIO and the concrete system. Accordingly, the controller can first be designed for the abstract system and then refined for the concrete system by introducing an appropriate interface controller. This controller constitutes an observer-based robust control law based on <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> to guarantee the desired performance despite external disturbances and includes an adaptive compensator to mitigate the effect of attacks on the simulation relation. The applicability of the presented approach is demonstrated through two case studies: load frequency control in a power system and frequency regulation in an isolated area of the New England 39-Bus Test System.</div></div>","PeriodicalId":49450,"journal":{"name":"Systems & Control Letters","volume":"197 ","pages":"Article 106028"},"PeriodicalIF":2.1,"publicationDate":"2025-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143171856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-02-01DOI: 10.1016/j.sysconle.2024.105983
Yanhua Yang, Jie Mei, Guangfu Ma
In this paper, the bipartite consensus problem of a class of unknown uncertain multi-agent systems (MASs) under a signed graph is investigated via a filter-based model-free reinforcement learning (RL) based fully distributed control scheme. First, considering the completely unknown dynamics of the agents, a novel filter-based model-free RL algorithm is proposed to learn the stabilizable feedback gain matrix via the online input–output data. Then, fully distributed algorithm with adaptive control gains is designed such that all agents reach bipartite consensus in the presence of dynamic uncertainties. Finally, a numerical simulation is illustrated to demonstrate the correctness and effectiveness of the proposed control scheme.
{"title":"Adaptive leaderless consensus of MIMO multi-agent systems with unknown dynamics and nonlinear dynamic uncertainties","authors":"Yanhua Yang, Jie Mei, Guangfu Ma","doi":"10.1016/j.sysconle.2024.105983","DOIUrl":"10.1016/j.sysconle.2024.105983","url":null,"abstract":"<div><div>In this paper, the bipartite consensus problem of a class of unknown uncertain multi-agent systems (MASs) under a signed graph is investigated via a filter-based model-free reinforcement learning (RL) based fully distributed control scheme. First, considering the completely unknown dynamics of the agents, a novel filter-based model-free RL algorithm is proposed to learn the stabilizable feedback gain matrix via the online input–output data. Then, fully distributed algorithm with adaptive control gains is designed such that all agents reach bipartite consensus in the presence of dynamic uncertainties. Finally, a numerical simulation is illustrated to demonstrate the correctness and effectiveness of the proposed control scheme.</div></div>","PeriodicalId":49450,"journal":{"name":"Systems & Control Letters","volume":"196 ","pages":"Article 105983"},"PeriodicalIF":2.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143183246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-02-01DOI: 10.1016/j.sysconle.2024.105987
Rui Xu, Hua Chen, Yao Tang, Xinyuan Long
In this paper, a model-free predictive iterative learning control (MFPILC) is proposed for a class of nonlinear and nonaffine single-input multiple-output (SIMO) discrete-time multi-agent systems with randomly varying trial lengths, input time-varying delay and nonrepetitive external disturbances to deal with the safety-critical consensus control problem. First, the agent dynamics are transformed into a novel dynamic linearization data model along the iteration axis containing the upper and lower bound of the unknown input time delay with an unknown system parameter pseudo gradient (PG). A steepest-descent estimation algorithm updated along the iterative learning axis is applied to deal with the unknown PG and the unknown non-repetitive external disturbances. Further, the predictive compensation mechanisms are proposed to address the problem of data loss caused by the varying trial lengths at each iteration of the MASs. Therefore, a predictive iterative learning consensus control method is designed for MASs based on consensus error and data compensation mechanisms. Moreover, a new model-free predictive iterative learning safety-critical consensus control combined with a discrete-time iterative learning control barrier function (ILCBF) is presented to ensure the output safety of nonlinear MASs. Finally, simulation results further verify the effectiveness of the proposed method.
{"title":"Model-free predictive iterative learning safety-critical consensus control for multi-agent systems with randomly varying trial lengths","authors":"Rui Xu, Hua Chen, Yao Tang, Xinyuan Long","doi":"10.1016/j.sysconle.2024.105987","DOIUrl":"10.1016/j.sysconle.2024.105987","url":null,"abstract":"<div><div>In this paper, a model-free predictive iterative learning control (MFPILC) is proposed for a class of nonlinear and nonaffine single-input multiple-output (SIMO) discrete-time multi-agent systems with randomly varying trial lengths, input time-varying delay and nonrepetitive external disturbances to deal with the safety-critical consensus control problem. First, the agent dynamics are transformed into a novel dynamic linearization data model along the iteration axis containing the upper and lower bound of the unknown input time delay with an unknown system parameter pseudo gradient (PG). A steepest-descent estimation algorithm updated along the iterative learning axis is applied to deal with the unknown PG and the unknown non-repetitive external disturbances. Further, the predictive compensation mechanisms are proposed to address the problem of data loss caused by the varying trial lengths at each iteration of the MASs. Therefore, a predictive iterative learning consensus control method is designed for MASs based on consensus error and data compensation mechanisms. Moreover, a new model-free predictive iterative learning safety-critical consensus control combined with a discrete-time iterative learning control barrier function (ILCBF) is presented to ensure the output safety of nonlinear MASs. Finally, simulation results further verify the effectiveness of the proposed method.</div></div>","PeriodicalId":49450,"journal":{"name":"Systems & Control Letters","volume":"196 ","pages":"Article 105987"},"PeriodicalIF":2.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143183241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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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