Finite-time consensus control for multi-agent systems with full-state constraints and actuator failures

Abstract

Aiming at a class of uncertain nonlinear multi-agent systems (MASs) with full-state constraints and actuator failures, a finite-time consensus control method is developed. Full-state constraints and actuator failures are ubiquitous in practical engineering applications. Violation of constraints would drastically affect the performance of MASs, even arise security problems. It is challenging to guarantee the performance of the MASs when undergoing actuator failures. To tackle these problems, an adaptive consensus control method is established by applying the Backstepping technique and Barrier Lyapunov functions (BLFs) to ensure the performance of the MASs with full-state constraints no matter actuator failures occur. Simultaneously, for the uncertain nonlinear MASs, a finite-time neural network (NN) consensus control scheme is established to ensure system's signals are synchronized in finite time. Moreover, an event-triggered control strategy is constructed to relieve the communication pressure of each agent. Finally, numerical and practical examples are employed to verify the effectiveness of the proposed control strategy.

Keywords: Actuator failures; Consensus control; Finite-time convergence; Full-state constraints; Multi-agent systems (MASs); Neural network.