Adaptive Optimal Consensus Control for Nonlinear Uncertain Multiagent Systems Under DoS Attacks
针对间歇性拒绝服务攻击下领导者动态未知且跟随者存在不确定性的非线性多智能体系统，提出一种基于学习的自适应分布式观测器和单评判器最优一致性跟踪控制方案，无需标识网络即可实现有界一致跟踪。
This article addresses the optimal control problem for nonlinear multiagent systems (MASs) with an uncertain nonlinear leader subject to intermittent Denial-of-Service (DoS) attacks. The main challenge is estimating the leader's dynamics when the uncertain nonlinear dynamics of the leader are unknown to all followers and communication between subsystems is intermittently disrupted by attacks. Furthermore, the uncertainty in the followers' dynamics adds complexity, making it difficult to eliminate reliance on the identifier network. To overcome these challenges, we develop a learning-based adaptive distributed observer to estimate the leader's dynamics under attacks. Based on this observer, a single-critic optimal consensus tracking control scheme is proposed to solve the leader-follower consensus problem in uncertain MASs without requiring an identifier network. It is proven that all system signals are uniformly ultimately bounded (UUB), and consensus tracking is achieved. The effectiveness of the proposed method is validated through a simulation example.