Predefined-Time Fuzzy Adaptive Optimal Secure Consensus Control for Multiagent Systems With Unknown Follower Dynamics
Haitao Wang, Qingshan Liu, Ju H. Park
Abstract
This article investigates the secure leader–following consensus of multiagent systems with unknown follower dynamics under two types of denial-of-service attacks: connectivity-maintained and connectivity-broken attacks. A predefined-time resilient distributed observer to achieve predefined-time observation of the leader's state is constructed by incorporating a time-varying piecewise function with an online update at the initial instant. During the connectivity-maintained intervals, all agents can achieve predefined-time observation of the leader. During the connectivity-broken intervals, agents that have direct or indirect access to the leader's state can still accomplish the predefined-time observation. Since the leader state observation cannot be ensured for all agents during the connectivity-broken intervals, a new persistent dwell-time switching model is introduced to describe the switching between the two types of attacks, and novel sufficient conditions are derived to ensure that all agents can observe the leader's state based on multiple Lyapunov function approach. Furthermore, a predefined-time sliding mode controller combining the resilient distributed observer and fuzzy reinforcement learning strategy is proposed to ensure leader–following consensus. Finally, the effectiveness of the proposed method is validated through simulations and comparisons using a distributed multiple robot arm system.