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Resilient cooperative optimal output regulation for nonlinear multi-agent systems via homotopic policy iteration
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DOI：10.1007/s11071-026-12907-9.png)
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Abstract
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This paper studies the cooperative optimal output regulation (COOR) problem for strict-feedback nonlinear multi-agent systems (NMASs) under denial-of-service (DoS) attacks. First, by designing the resilient adaptive distributed observers, each follower can estimate the dynamics and state of the leader. Subsequently, the solution to the nonlinear output regulation equation is obtained by means of neural networks. Meanwhile, a homotopy-based policy iteration (PI) algorithm is proposed to learn the optimal feedback controller. Unlike the traditional PI, an admissible control policy for the original system is obtained by gradually transitioning a stable system to the original system via introducing a homotopic constant. With this design, the proposed control scheme can obtain the admissible controller for initializing the PI without model-based initialization. It is proved that the tracking errors converge to a bounded neighborhood of the origin and all signals of the closed-loop system are bounded, while the system achieves Nash equilibrium (NE). Finally, the feasibility of the proposed control scheme is demonstrated by a simulation example.
Keywords:
Cooperative optimal output regulation
Nonlinear multi-agent systems
Denial-of-service attacks
Homotopic policy iteration
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6
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1.4W
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