Journal Article

An Intelligent Robust Operator-Based Sliding Mode Control for Trajectory Tracking of Nonlinear Uncertain Systems

Pannek, Jürgen, Tong, Angxin, Deng, Quan, Liu, Ping, Zhang, Qiang

2023

Overview

This paper investigates the problem of trajectory tracking control in the presence of bounded model uncertainty and external disturbance. To cope with this problem, we propose a novel intelligent operator-based sliding mode control scheme for stability guarantee and control performance improvement in the closed-loop system. Firstly, robust stability is guaranteed by using the operator-based robust right coprime factorization method. Secondly, in order to further achieve the asymptotic tracking and enhance the responsiveness to disturbance, a finite-time integral sliding mode control law is designed for fast convergence and non-zero steady-state error in accordance with Lyapunov stability analysis. Lastly, the controller’s parameters are automatically adjusted by the proved stabilizing particle swarm optimization with the linear time-varying inertia weight, which significantly saves tuning time with a remarkable performance guarantee. The effectiveness and efficiency of the proposed method are verified on a highly nonlinear ionic polymer metal composite application. The extensive numerical simulations are conducted and the results show that the proposed method is superior to the state-of-the-art methods in terms of tracking accuracy and high robustness against disturbances.

• Publisher: MDPI AG
• Subject: Algorithms / Asymptotic methods / Closed loops / Control algorithms / Control theory / Controllers / Error analysis / Feedback control / Genetic algorithms / Intelligence / Mathematical models / Mathematical optimization / Nonlinear systems / Optimization / Particle swarm optimization / Robust control / Sliding mode control / Stability analysis / Tracking control / Trajectory control