Volume 14, Issue 4 (Journal of Control, V.14, N.4 Winter 2021)                   JoC 2021, 14(4): 81-92 | Back to browse issues page

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Valadbeigi A P, Khaki Sedigh A, Lewis F, Moarefian Poor A. Cooperative Robust Output Consensus in Continuous-Time Heterogeneous Multi-Agent Systems Using Integral Reinforcement Learning Method. JoC. 2021; 14 (4) :81-92
URL: http://joc.kntu.ac.ir/article-1-726-en.html
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Abstract:   (1475 Views)
: The Robust Cooperative Output Consensus (RCOC) in continuous time Heterogeneous Multi-Agent Systems with the directed graph is addressed. In the standard solution of the RCOC, the p-copy internal model method is used. This method requires dynamical equations of the agents and the leader. In the present paper, based on the equivalent auxiliary system method, a new auxiliary system is obtained. Then, the RCOC is transformed to a control problem. Moreover, a model-free algorithm is proposed to solve the Robust Algebraic Riccati Equation using the Integral Reinforcement Learning (IRL) method. It is shown that the proposed method satisfies the output regulation equations. A simulation example verifies the effectiveness of the proposed method.
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Type of Article: Research paper | Subject: Special
Received: 2020/01/8 | Accepted: 2020/03/15 | ePublished ahead of print: 2020/07/15 | Published: 2021/01/29

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