Adaptive NN Resilient Consensus Control of Nonlinear Heterogeneous Agents Under Switching Network With DoS Attacks

Abstract

This paper investigates the distributed resilient consensus control problem for a class non-linear heterogeneous multiagent systems under unreliable communication environment, which includes time-varying interaction network and intermittent denial of service (DoS) attacks. In order to handle heterogeneous nonlinear unknown dynamics in each agent subsystem, a novel distributed adaptive neural networks (NNs) control approach is developed exploiting the neighborhood information. By introducing the topology-dependent Lyapunov function and adaptive switching control mechanism, we show that the uniformly bound convergence of the consensus errors can be guaranteed by the proposed topology average dwell time constraints. A simulation example is provided to validate the effectiveness of the proposed resilient control algorithm.

Keywords

• Nonlinear multi-agent systems
• resilient consensus control
• switching topology networks
• denial-of-service attacks
• adaptive NNs approach