Adaptive Cooperative Tracking Control of Multi-Agent Systems With Unknown Actuators Hysteresis

Abstract

This paper considers cooperative tracking control of nonlinear multi-agent systems with actuators hysteresis over digraphs. Each agent is modeled by a higher-order nonlinear system in strict-feedback form with the generalized Prandtl–Ishlinskii hysteresis input and unknown time-varying virtual control coefficients. An online adaptive law is introduced for compensating the unknown hysteresis effect. A special Nussbaum-type function is developed to handle unknown time-varying virtual control coefficients. A switching mechanism is utilized to combine the neural networks approximation with an extra robust term, which can take over the authority outside the neural active region. In this sense, the globally uniformly ultimately bounded stability is guaranteed by the proposed distributed adaptive control law. Moreover, all agents ultimately synchronize to the leader node with bounded residual errors. Simulation results justify the proposed algorithm.