Convex Optimization-Based Adaptive Fuzzy Control for Uncertain Nonlinear Systems With Input Saturation Using Command Filtered Backstepping

• Published in: IEEE transactions on fuzzy systems Vol. 31; no. 6; pp. 2086 - 2091
• Main Authors: Liu, Jiapeng, Wang, Qing-Guo, Yu, Jinpeng
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive control; Backstepping; Closed loops; command filter; Continuity (mathematics); Convex functions; convex optimization; Convexity; Feedback control; Fuzzy control; Fuzzy logic; fuzzy logic system (FLS); Lyapunov methods; Nonlinear control; Nonlinear systems; Optimization; Stability analysis; System performance; Tracking control; Uncertainty
• ISSN: 1063-6706; 1941-0034
• DOI: 10.1109/TFUZZ.2022.3216103

This article presents a modified command filter backstepping tracking control strategy for a class of uncertain nonlinear systems with input saturation based on the convex optimization method and the adaptive fuzzy logic system (FLS) control technique. First, the effect of complex uncertainties is eliminated by introducing n command filters and a single FLS. Then, the update laws of FLS weights are designed based on the convex optimization technique. Next, a new piecewise continuous function is employed to deal with the input saturation problem. The closed-loop system performance is also analyzed using the Lyapunov stability theorem and the Lasalle invariant principle. Finally, the simulation and experimental results are presented to show the effectiveness of our controller.