Event-based adaptive fuzzy tracking control for nonlinear systems with input magnitude and rate saturations

Abstract

In this paper, an event-based adaptive fuzzy tracking control strategy for a class of uncertain nonlinear systems with limited control input and its rate of change is proposed. The unknown nonlinear function of the considered system is approximated by a fuzzy logic system (FLS). Furthermore, an event-triggered control method is developed to save the computing resources, in which the controller parameters are adaptively adjusted by a fuzzy controller. Moreover, it is proved by designing the Lyapunov function that the event-based controller can ensure that all signals of the controlled system are bounded. In addition, the tracking error can converge to a preset domain. Meanwhile, two practical simulations are given to demonstrate the effectiveness of the proposed method.

Keywords:

• Event-triggered strategy
• uncertain nonlinear systems
• adaptive fuzzy control
• input and rate saturations
• parameter self-tuning

Data availability statement

The data that support the findings of this study are available from the corresponding author, Changyin Sun, upon reasonable request.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work is supported part by the National Key R&D Program of China under Grant 2021ZD0112700, and part by the National Natural Science Foundation of China under Grant 62173251.