Event-triggered adaptive fuzzy tracking control for stochastic nonlinear systems

In this paper, the problem of event-triggered mechanism based adaptive fuzzy tracking control is studied for strict-feedback stochastic nonlinear systems. The fuzzy logic systems are introduced to approximate the unknown nonlinear terms. A novel event-triggered tracking controller is designed by incorporating the backstepping design approach with the method of fuzzy control. The newly designed controller not only ensures that the output signal tracks the given reference signal within a sufficiently small neighborhood of the origin, but also ensures that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded in the sense of the four-moment. Meanwhile, an event-triggered control mechanism is introduced to reduce the communication burden from the controller to the actuator. Finally, simulation results demonstrate the effectiveness of the designed controller.