详细信息

Global Bipartite Output Consensus of Discrete-Time Heterogeneous Linear Systems Subject to Input Saturation: A Model-Free Approach  ( SCI-EXPANDED收录 EI收录)  

文献类型:期刊文献

英文题名:Global Bipartite Output Consensus of Discrete-Time Heterogeneous Linear Systems Subject to Input Saturation: A Model-Free Approach

作者:Fu, Zhuofan[1];Feng, Xinjun[1];Zhao, Zhiyun[1];Yang, Wen[1]

机构:[1]East China Univ Sci & Technol, Key Lab Smart Mfg Energy Chem Proc, Minist Educ, Shanghai 200237, Peoples R China

年份:2025

卷号:12

期号:1

起止页码:812

外文期刊名:IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS

收录:;EI(收录号:20242916703115);WOS:【SCI-EXPANDED(收录号:WOS:001449684200023)】;

基金:This work was supported by the National Natural Science Foundation of China under Grant 61703162, Grant 62336005, and Grant 62122026.

语种:英文

外文关键词:Mathematical models; Multi-agent systems; Heuristic algorithms; Synchronization; Topology; Feedforward systems; Control systems; Discrete-time heterogeneous linear systems; global bipartite output consensus; input saturation; model-free approach

摘要:In this article, we propose a model-free approach for solving the bipartite output consensus problem of discrete-time heterogeneous multiagent systems subject to input saturation over a weighted directed network. We propose both a distributed reference generator and a control law based on the low-gain approach for each follower agent in the system. We show that all the control laws together achieve semiglobal bipartite output consensus. Furthermore, we present a Q-learning algorithm to obtain both the low-gain parameter and the feedback gain matrix in the control law. We also present an online output-tracking-error-based updating algorithm to obtain the feedforward gain matrix in the control law. Thus, these control laws no more rely on the dynamics of linear systems. We show that the input saturation during the online updating algorithm does not affect the convergence of the algorithm. The control laws calculated from the model-free algorithms can prevent input saturation from occurring, and thus, the heterogeneous multiagent systems achieve global bipartite output consensus. Finally, we provide a numerical example for validating the theoretical results.

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