Adaptive reduced parameters fault-tolerant tracking control for stochastic multiagent systems with simplified memory event-triggered strategy

The memory event-based finite-time bipartite tracking control scheme is presented for the stochastic nonlinear multiagent systems. The actuator is affected by Bouc-Wen hysteresis and actuator faults simultaneously, and to guarantee the tracking performance, an adaptive finite-time bipartite controller, which reduces online estimation parameters, is constructed for the stochastic systems. A simplified memory event-triggered mechanism is proposed under the backstepping framework for the first time. Furthermore, the released data are used to set the event-triggered threshold condition, which avoids the problem of trigger instability caused by actuator faults and Bouc-Wen Hysteresis. Disturbance observers are applied to compensate the impact of input hysteresis and system disturbances. According to the Lyapunov theory, it is shown that all signals of the closed-loop systems are semiglobal practical finite-time stable in probability. Meanwhile, the bipartite control performance is obtained. Finally, a practical example and a numerical simulation are provided to attest the validity of the proposed bipartite tracking control strategy.