Sampled-Data Consensus for Nonlinear Multiagent Dynamical Systems via Reliable Control

Abstract

The paper studies sampled-data consensus for nonlinear multiagent dynamical systems. A distributed linear reliable consensus protocol is designed, where probabilistic actuators with different failure rates and random network-induced delay are considered. Based on the input delay approach, a new distribution-based fault multiagent system model with random delay is proposed. By using the stochastic analysis technique and Kronecker product properties, some consensus conditions are derived in terms of linear matrix inequalities, and the solvability of derived conditions depends on not only the failure rate of the actuator but also on the probability of the delay. Finally, a numerical example is provided to demonstrate the effectiveness of the obtained theoretical results.