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New Results in Cooperative Adaptive Optimal Output Regulation

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Abstract

This paper investigates the cooperative adaptive optimal output regulation problem of continuous-time linear multi-agent systems. As the multi-agent system dynamics are uncertain, solving regulator equations and the corresponding algebraic Riccati equations is challenging, especially for high-order systems. In this paper, a novel method is proposed to approximate the solution of regulator equations, i.e., gradient descent method. It is worth noting that this method obtains gradients through online data rather than model information. A data-driven distributed adaptive suboptimal controller is developed by adaptive dynamic programming, so that each follower can achieve asymptotic tracking and disturbance rejection. Finally, the effectiveness of the proposed control method is validated by simulations.

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Authors and Affiliations

  1. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, 110819, China

    Yuchen Dong & Weinan Gao

  2. Department of Electrical and Computer Engineering, Tandon School of Engineering, New York University, Brooklyn, NY, 11201, USA

    Zhong-Ping Jiang

Authors
  1. Yuchen Dong
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  2. Weinan Gao
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  3. Zhong-Ping Jiang
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Corresponding author

Correspondence to Weinan Gao.

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The authors declare no conflict of interest.

Additional information

The work was supported in part by the National Natural Science Foundation of China under Grant No. 62373090 and the U.S. National Science Foundation under Grant No. CNS-2227153.

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Dong, Y., Gao, W. & Jiang, ZP. New Results in Cooperative Adaptive Optimal Output Regulation. J Syst Sci Complex 37, 253–272 (2024). https://doi.org/10.1007/s11424-024-3429-0

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  • DOI: https://doi.org/10.1007/s11424-024-3429-0

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