Distributed adaptive neural consensus tracking control of MIMO stochastic nonlinear multiagent systems with actuator failures and unknown dead zones
Zumin Wu, Yuefei Wu, Dong Yue · International Journal of Adaptive Control and Signal Processing · 2018
Summary This paper focuses on the leader‐following consensus control problem of stochastic multiagent systems with unknown input dead‐zone nonlinearity, unknown actuator failures, and nonlinear dynamics. A distributed adaptive neural consensus tracking controller is presented for stochastic multiagent systems directions under directed graphs, which can achieve predefined synchronization error bounds. By mainly activating an auxiliary robust control component for pulling back the transient escaped from the neural active region, a multiswitching robust neuroadaptive controller in the neural approximation domain can achieve globally uniformly ultimately bounded tracking stability of multiagent systems recently. By constructing a smooth dead‐zone inverse and applying the dynamic surface control technique, distributed consensus controllers are developed to guarantee that the trajectories of synchronization error converge to a small neighborhood of the origin. Two simulation examples are provided to illustrate the effectiveness and advantage of the proposed control scheme.