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.