4.6 Article

Fuzzy Estimator Indirect Terminal Sliding Mode Control of Nonlinear Systems Based on Adaptive Continuous Barrier Function

Journal

IEEE ACCESS
Volume 10, Issue -, Pages 34296-34305

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2022.3162331

Keywords

Sliding mode control; Control systems; Nonlinear systems; Mathematical models; Uncertainty; Power system stability; Manipulators; Finite-time stability; continuous function; sliding mode control; fuzzy estimator; adaptive control

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This paper explores the theory of control on nonlinear systems and introduces an indirect terminal sliding mode control technique based on adaptive and fuzzy rules. The proposed method improves the controller performance by using a continuous barrier function and solves the chattering problem typically seen in sliding mode control. It also guarantees the asymptotical stability of the system dynamics within finite time.
In this paper, the theory of control is considered on nonlinear systems. A closed-loop controller with a strong idea has been introduced to track system states and guarantee asymptotically stability. The proposed method is the indirect terminal sliding mode control technique based on adaptive and fuzzy rules, which has used the continuous barrier function as a new approach in its design to improve the performance of this controller. One of the significant challenges in the sliding mode control method is the chattering phenomenon due to the discontinuous sign function in the control law. In the proposed approach, the control law is obtained continuously and smoothly due to the mentioned continuous function and subsequently solves the chattering problem. Another feature of the proposed method is the asymptotical stability of the system dynamics within finite time, which is proved based on the Lyapunov function. The proposed Lyapunov function includes the function of fractional power of a sliding surface. On the other hand, the obtained control law using the sliding mode method is estimated using the fuzzy system. The adaptive approach adjusts the fuzzy law parameters and the unknown bound of external disturbance.

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