Event-triggered adaptive prescribed-time control for nonlinear systems with uncertain time-varying parameters

The problem of event-based adaptive prescribed-time control for a class of nonlinear systems with uncertain time-varying parameters is considered in this paper. The existence of uncertain time-varying parameters makes the system in question intrinsically different from that in prescribed-time stabilization or event-triggered control. Moreover, the existing prescribed-time control methods require the real-time continuous control input. For this reason, a novel event-based adaptive prescribed-time control strategy is presented by skillfully utilizing a key scaling technique and a new event-triggering mechanism. It is proved that the proposed event-triggering mechanism can enlarge the trigger time interval and effectively reduce the number of trigger moments compared with the existing event-triggered control methods. An important stability criterion is proposed based on the defined prescribed-time adjustment function. Furthermore, the proposed control algorithm can effectively reduce the computational burden and save the control effort. Finally, a numerical simulation verifies the effectiveness of the proposed prescribed-time control algorithm.