Event and Learning-Based Resilient Formation Control for Multiagent Systems Under DoS Attacks
Abstract
This article presents a novel event and learning-based resilient formation control strategy for heterogeneous multiagent systems subjected to denial-of-service (DoS) attacks and uncertainties. It involves a decoupled cyber-layer and physical system layer design that enables a distributed and model-free approach. In the cyber-layer, the design is an event-triggered resilient observer for a reference exosystem estimation under DoS attacks using dual adaptive laws and an optimal algorithm. This approach eliminates the need for global information of the communication topology and enhances system resilience under attacks. In the physical system layer, the design is a model-free formation output controller for heterogeneous agents based on off-policy reinforcement learning. The incorporation of a new rank condition improves the convergence performance. Experiments using unmanned ground vehicles are conducted for scanning a physical area to verify the effectiveness and resilience of the proposed control strategy.
