Semiglobal Suboptimal Output Regulation for Heterogeneous Multi-Agent Systems With Input Saturation via Adaptive Dynamic Programming

This article considers the semiglobal cooperative suboptimal output regulation problem of heterogeneous multi-agent systems with unknown agent dynamics in the presence of input saturation. To solve the problem, we develop distributed suboptimal control strategies from two perspectives, namely, model...

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Veröffentlicht in:IEEE transaction on neural networks and learning systems Jg. 35; H. 3; S. 1 - 9
Hauptverfasser: Wang, Bingjie, Xu, Lei, Yi, Xinlei, Jia, Yao, Yang, Tao
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States IEEE 01.03.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:2162-237X, 2162-2388, 2162-2388
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Zusammenfassung:This article considers the semiglobal cooperative suboptimal output regulation problem of heterogeneous multi-agent systems with unknown agent dynamics in the presence of input saturation. To solve the problem, we develop distributed suboptimal control strategies from two perspectives, namely, model-based and data-driven. For the model-based case, we design a suboptimal control strategy by using the low-gain technique and output regulation theory. Moreover, when the agents' dynamics are unknown, we design a data-driven algorithm to solve the problem. We show that proposed control strategies ensure each agent's output gradually follows the reference signal and achieves interference suppression while guaranteeing closed-loop stability. The theoretical results are illustrated by a numerical simulation example.
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ISSN:2162-237X
2162-2388
2162-2388
DOI:10.1109/TNNLS.2022.3191673