This paper investigates the sliding-mode-based fixed-time distributed average tracking (DAT) problem for multiple Euler-Lagrange systems in the presence of external distur-bances. The primary objective is to devise co...This paper investigates the sliding-mode-based fixed-time distributed average tracking (DAT) problem for multiple Euler-Lagrange systems in the presence of external distur-bances. The primary objective is to devise controllers for each agent, enabling them to precisely track the average of multiple time-varying reference signals. By averaging these signals, we can mitigate the influence of errors and uncertainties arising dur-ing measurements, thereby enhancing the robustness and stabi-lity of the system. A distributed fixed-time average estimator is proposed to estimate the average value of global reference sig-nals utilizing local information and communication with neigh-bors. Subsequently, a fixed-time sliding mode controller is intro-duced incorporating a state-dependent sliding mode function coupled with a variable exponent coefficient to achieve dis-tributed average tracking of reference signals, and rigorous ana-lytical methods are employed to substantiate the fixed-time sta-bility. Finally, numerical simulation results are provided to vali-date the effectiveness of the proposed methodology, offering insights into its practical application and robust performance.展开更多
In this paper,we revisit the semi-global weighted output average tracking problem for a discrete-time multi-agent system subject to input saturation and external disturbances.The multi-agent system consists of multipl...In this paper,we revisit the semi-global weighted output average tracking problem for a discrete-time multi-agent system subject to input saturation and external disturbances.The multi-agent system consists of multiple heterogeneous linear systems as leader agents and multiple heterogeneous linear systems as follower agents.We design both the state feedback and output feedback control protocols for each follower agent.In particular,a distributed state observer is designed for each follower agent that estimates the state of each leader agent.In the output feedback case,state observer is also designed for each follower agent to estimate its own state.With these estimates,we design low gain-based distributed control protocols,parameterized in a scalar low gain parameter.It is shown that,for any bounded set of the initial conditions,these control protocols cause the follower agents to track the weighted average of the outputs of the leader agents as long as the value of the low gain parameter is tuned sufficiently small.Simulation results illustrate the validity of the theoretical results.展开更多
Progress in development of multi-agent control is reviewed.Different approaches for multiagent control,estimation,and optimization are discussed in a systematic way with particular emphasis on the graph-theoretic pers...Progress in development of multi-agent control is reviewed.Different approaches for multiagent control,estimation,and optimization are discussed in a systematic way with particular emphasis on the graph-theoretic perspective.Attention is paid to the design of multi-agent systems via Laplacian dynamics,as well as the role of the graph Laplacian spectrum,the challenges of unbalanced digraphs,and consensus-based estimation of graph statistics.Some emergent issues,e.g.,distributed optimization,distributed average tracking,and distributed network games,are also reported,which have witnessed extensive development recently.There are over 200 references listed,mostly to recent contributions.展开更多
基金supported by the National Natural Science Foundation of China(61673130).
文摘This paper investigates the sliding-mode-based fixed-time distributed average tracking (DAT) problem for multiple Euler-Lagrange systems in the presence of external distur-bances. The primary objective is to devise controllers for each agent, enabling them to precisely track the average of multiple time-varying reference signals. By averaging these signals, we can mitigate the influence of errors and uncertainties arising dur-ing measurements, thereby enhancing the robustness and stabi-lity of the system. A distributed fixed-time average estimator is proposed to estimate the average value of global reference sig-nals utilizing local information and communication with neigh-bors. Subsequently, a fixed-time sliding mode controller is intro-duced incorporating a state-dependent sliding mode function coupled with a variable exponent coefficient to achieve dis-tributed average tracking of reference signals, and rigorous ana-lytical methods are employed to substantiate the fixed-time sta-bility. Finally, numerical simulation results are provided to vali-date the effectiveness of the proposed methodology, offering insights into its practical application and robust performance.
基金supported in part by the National Natural Science Foundation of China(Nos.62022055,61973215).
文摘In this paper,we revisit the semi-global weighted output average tracking problem for a discrete-time multi-agent system subject to input saturation and external disturbances.The multi-agent system consists of multiple heterogeneous linear systems as leader agents and multiple heterogeneous linear systems as follower agents.We design both the state feedback and output feedback control protocols for each follower agent.In particular,a distributed state observer is designed for each follower agent that estimates the state of each leader agent.In the output feedback case,state observer is also designed for each follower agent to estimate its own state.With these estimates,we design low gain-based distributed control protocols,parameterized in a scalar low gain parameter.It is shown that,for any bounded set of the initial conditions,these control protocols cause the follower agents to track the weighted average of the outputs of the leader agents as long as the value of the low gain parameter is tuned sufficiently small.Simulation results illustrate the validity of the theoretical results.
基金the National Science Foundation of China under Grant Nos.61973061and 61973064Hebei Natural Science Foundation for Distinguished Young Scholars under Grant Nos.F2019501043 and F2019501126。
文摘Progress in development of multi-agent control is reviewed.Different approaches for multiagent control,estimation,and optimization are discussed in a systematic way with particular emphasis on the graph-theoretic perspective.Attention is paid to the design of multi-agent systems via Laplacian dynamics,as well as the role of the graph Laplacian spectrum,the challenges of unbalanced digraphs,and consensus-based estimation of graph statistics.Some emergent issues,e.g.,distributed optimization,distributed average tracking,and distributed network games,are also reported,which have witnessed extensive development recently.There are over 200 references listed,mostly to recent contributions.
