Adaptive finite-time direct fuzzy control for a nonlinear system with an unknown control gain based on an observer

An adaptive fuzzy output tracking control scheme is presented for a class of strict-feedback systems with an unknown control gain in this paper. An ideal controller that can achieve finite-time stabilization of the filtered tracking error system is approximated by an ideal fuzzy logic system. The actual fuzzy function is used as the controller to estimate the ideal fuzzy system via on-line adjustment of system parameters. A tau-observer ( i.e., the control error observer) is designed to manage the unknown fuzzy control error. Unlike previous studies, new parameter adaptive laws are constructed in this study, and derivative calculations in the filtered tracking error system are not required. An adaptive direct fuzzy controller based on a tau-observer is thus proposed. The practical finite-time stabilization of the output tracking error and the boundedness of all states in the closed-loop system are also ensured. Finally, the effectiveness of the proposed control criterion is verified via two simulation examples. (C) 2022 Elsevier Inc. All rights reserved.

Automated summary

This paper presents an adaptive fuzzy output tracking control scheme for a class of strict-feedback systems with an unknown control gain. An ideal controller that achieves finite-time stabilization of the filtered tracking error system is approximated by an ideal fuzzy logic system. The actual fuzzy function is used as the controller to estimate the ideal fuzzy system through online adjustment of system parameters. A tau-observer is designed to handle the unknown fuzzy control error. Unlike previous studies, new parameter adaptive laws are constructed without requiring derivative calculations in the filtered tracking error system. Thus, an adaptive direct fuzzy controller based on a tau-observer is proposed. The practical finite-time stabilization of the output tracking error and the boundedness of all states in the closed-loop system are ensured. Finally, the effectiveness of the control criterion is verified through two simulation examples.