Event-based finite-time sliding mode consensus tracking control for multiagent systems with actuator failures

This paper investigates the finite-time sliding mode control problem for multiagent systems with actuator failures and external disturbances. Given the presence of unknown nonlinear terms in the controlled multiagent systems, a radial basis function neural network is employed to ensure system robustness. To achieve consensus tracking of sliding mode dynamics within a finite-time, a finite-time integral sliding manifold is proposed. An adaptive law is designed to estimate the unknown fault coefficient, and then a distributed event-triggered adaptive sliding mode fault-tolerant control protocol is developed to deal with external disturbances and actuator faults in multiagent systems, which can effectively reduce the communication bandwidth and enhance reliability against actuator faults. To verify the effectiveness of the proposed control method, a numerical example is provided.