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

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 e...

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Published inIEEE transactions on fuzzy systems Vol. 31; no. 6; pp. 2086 - 2091
Main Authors Liu, Jiapeng, Wang, Qing-Guo, Yu, Jinpeng
Format Journal Article
LanguageEnglish
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
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Abstract 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.
AbstractList 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.
Author Yu, Jinpeng
Liu, Jiapeng
Wang, Qing-Guo
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  organization: School of Automation and Electrical Engineering, Qingdao University, Qingdao, China
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SubjectTerms 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
Title Convex Optimization-Based Adaptive Fuzzy Control for Uncertain Nonlinear Systems With Input Saturation Using Command Filtered Backstepping
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Volume 31
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