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

Abstract

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.

Event‐triggered practical finite‐time output feedback stabilization of a class of uncertain nonlinear systems

“…Remark Different from the finite‐time output feedback control design, and the event‐triggered control schemes, there exist both the event‐triggered errors and the observer errors in this article. In the last step, we have to deal with the event‐triggered errors and the observer errors simultaneously, which makes the control design not a straightforward matter.…”

“…Subsequently, the theoretical result about event‐triggered output feedback control for uncertain nonlinear systems was presented in the work of Xing et al by designing a state estimation filter. Moreover, Zhang and Yang investigated the problem of event‐triggered adaptive output feedback control for a class of uncertain nonlinear systems in the presence of actuator failures and unknown control direction. Nevertheless, it is worth pointing out that the aforementioned schemes only guarantee the boundedness of all the signals of the systems.…”

Event‐triggered control for a class of strict‐feedback nonlinear systems

“…The global convergence of the systems is guaranteed by applying Lyapunov analyses and the theories of real variable functions. This is different from using fuzzy logic systems or neural networks technology in related works to obtain only semiglobal bounded results, and it is also superior to the globally bounded results obtained in other works A new method of designing event‐triggered mechanism is proposed.…”

“…Remark Some comparisons with related literature are presented to explain the differences or less conservativeness of the assumption. In the works of Li and Yang and Zhang and Yang, the nonlinear functions are approximated by fuzzy logic systems or adaptive neural networks, which led to the estimation residuals remaining in the design process and did not make without any restrictions on the state vectors. This limitation also occurs in the work of Li and Yang, thus the states of the systems are only guaranteed to be bounded, instead of convergence.…”

“…Furthermore, the same result was obtained by using the output feedback method in the work of Xing et al However, the event‐triggered mechanism was presented for the controller‐to‐actuator channels, it depends on the difference between the controller and the continuously transmitted counterpart rather than on the difference between the state vectors and the continuously transmitted counterparts. It can be seen that the measures were proposed to reduce the amount of communication in the sensor‐to‐controller channels in the works of Li and Yang and Zhang and Yang . Nevertheless, the nonlinearities of the systems in these works were approximated by adaptive neural network‐based or fuzzy‐based control schemes, which led to the estimation residuals remaining in the design process and affected the final convergence of the systems.…”