Event-Triggered Adaptive Output Feedback Control for a Class of Uncertain Nonlinear Systems With Actuator Failures

This paper investigates the event-triggered adaptive output feedback control problem for a class of uncertain nonlinear systems in the presence of actuator failures and unknown control direction. By utilizing the adaptive backstepping technique, an event-based output feedback controller is developed together with a time-variant event-triggered rule. In this design, the radial basis function neural network algorithms are first introduced to identify the unknown terms of the systems. Then, a new state observer with adaptive compensation is designed to estimate the state vector. The overall control strategy guarantees that the output signal tracks the reference signal and all the signals of the closed-loop systems are bounded. Unlike the existing methods, the proposed control scheme can handle the coupling term incurred by the loss of effectiveness fault of the actuator, the event-triggered rule, and unknown control direction. Finally, an example is performed to demonstrate the validity of the proposed strategy.