Adaptive fuzzy dynamic event-triggered control of uncertain nonlinear systems with sensor faults

In this paper, an adaptive fuzzy dynamic event-triggered control strategy is developed for uncertain nonlinear systems (UNS) in the presence of sensor faults, unknown dynamics and limited communication resource by using backstepping technique. A dynamic event-triggered mechanism is equipped in the sensor side and controller side, which contributes dual-channel event-triggered strategy. Setting event-triggered mechanism at sensor side generates a challenge to the backstepping technique implement as the discontinuous state and output signals received at the controller lead to nondifferential virtual control law. This challenge problem would become even more obvious when the sensor faults are taken into account. To better deal with this problem, we construct a fuzzy state observer to estimate all states only based on fault output triggering information. Therefore, the estimated states deriving from state observer are continuous and can be employed to construct output feedback control strategy. Such operation can guarantee the existence of the first derivative of the virtual control law. Moreover, repeated differentiation operation about virtual control law in the backstepping procedure is avoided by introducing first-order filter. The proposed dynamic event-triggered control solution can greatly promote the network resource utilization and enhance system robustness for sensor faults. We prove all signals of the UNS are bounded and Zeno behavior do occur. Simulation studies exhibit the availability of the presented dual-channel event-triggered approach.