Adaptive Fuzzy Control of Nonlinear Systems with Unmodeled Dynamics and Input Saturation Using Small-Gain Approach

Qi Zhou; Hongyi Li; Chengwei Wu; Lijie Wang; Choon Ki Ahn

doi:10.1109/TSMC.2016.2586108

Adaptive Fuzzy Control of Nonlinear Systems with Unmodeled Dynamics and Input Saturation Using Small-Gain Approach

Qi Zhou, Hongyi Li, Chengwei Wu, Lijie Wang, Choon Ki Ahn

Research output: Contribution to journal › Article › peer-review

283 Citations (Scopus)

Abstract

This paper investigates the problem of adaptive fuzzy state-feedback control for a category of single-input and single-output nonlinear systems in nonstrict-feedback form. Unmodeled dynamics and input constraint are considered in the system. Fuzzy logic systems are employed to identify unknown nonlinear characteristics existing in systems. An appropriate Lyapunov function is chosen to ensure unmodeled dynamics to be input-to-state practically stable. A smooth function is introduced to tackle input saturation. In order to overcome the difficulty of controller design for nonstrict-feedback system in backstepping design process, a variables separation method is introduced. Moreover, based on small-gain technique, an adaptive fuzzy controller is designed to guarantee all the signals of the resulting closed-loop system to be bounded. Finally, two illustrative examples are given to validate the effectiveness of the new design techniques.

Original language	English
Article number	7572123
Pages (from-to)	1979-1989
Number of pages	11
Journal	IEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume	47
Issue number	8
DOIs	https://doi.org/10.1109/TSMC.2016.2586108
Publication status	Published - 2017 Aug

Bibliographical note

Funding Information:
Manuscript received February 5, 2016; revised April 27, 2016; accepted June 19, 2016. Date of publication September 20, 2016; date of current version July 17, 2017. This work was supported in part by the National Natural Science Foundation of China under Grant 61622302, Grant 61573070, Grant 61673072, and Grant 61304003, in part by the Natural Science Foundation of Liaoning Province under Grant 2015020049, in part by the Program for New Century Excellent Talents in University under Grant NCET-13-0696, in part by the Program for Liaoning Innovative Research Team in University under Grant LT2013023, and in part by the Program for Liaoning Excellent Talents in University under Grant LJQ20141126. This paper was recommended by Associate Editor Y.-J. Liu. (Corresponding author: Hongyi Li.) Q. Zhou is with the School of Automation, Guangdong University of Technology, Guangzhou 510006, China and also with the College of Information Science and Technology, Bohai University, Jinzhou 121013, China (e-mail: [email protected]).

Publisher Copyright:
© 2013 IEEE.

Keywords

Adaptive control
backstepping
fuzzy logic systems
nonstrict-feedback system
small gain approach

ASJC Scopus subject areas

Software
Control and Systems Engineering
Human-Computer Interaction
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/TSMC.2016.2586108

Cite this

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title = "Adaptive Fuzzy Control of Nonlinear Systems with Unmodeled Dynamics and Input Saturation Using Small-Gain Approach",

abstract = "This paper investigates the problem of adaptive fuzzy state-feedback control for a category of single-input and single-output nonlinear systems in nonstrict-feedback form. Unmodeled dynamics and input constraint are considered in the system. Fuzzy logic systems are employed to identify unknown nonlinear characteristics existing in systems. An appropriate Lyapunov function is chosen to ensure unmodeled dynamics to be input-to-state practically stable. A smooth function is introduced to tackle input saturation. In order to overcome the difficulty of controller design for nonstrict-feedback system in backstepping design process, a variables separation method is introduced. Moreover, based on small-gain technique, an adaptive fuzzy controller is designed to guarantee all the signals of the resulting closed-loop system to be bounded. Finally, two illustrative examples are given to validate the effectiveness of the new design techniques.",

keywords = "Adaptive control, backstepping, fuzzy logic systems, nonstrict-feedback system, small gain approach",

author = "Qi Zhou and Hongyi Li and Chengwei Wu and Lijie Wang and Ahn, {Choon Ki}",

note = "Funding Information: Manuscript received February 5, 2016; revised April 27, 2016; accepted June 19, 2016. Date of publication September 20, 2016; date of current version July 17, 2017. This work was supported in part by the National Natural Science Foundation of China under Grant 61622302, Grant 61573070, Grant 61673072, and Grant 61304003, in part by the Natural Science Foundation of Liaoning Province under Grant 2015020049, in part by the Program for New Century Excellent Talents in University under Grant NCET-13-0696, in part by the Program for Liaoning Innovative Research Team in University under Grant LT2013023, and in part by the Program for Liaoning Excellent Talents in University under Grant LJQ20141126. This paper was recommended by Associate Editor Y.-J. Liu. (Corresponding author: Hongyi Li.) Q. Zhou is with the School of Automation, Guangdong University of Technology, Guangzhou 510006, China and also with the College of Information Science and Technology, Bohai University, Jinzhou 121013, China (e-mail: [email protected]). Publisher Copyright: {\textcopyright} 2013 IEEE.",

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N2 - This paper investigates the problem of adaptive fuzzy state-feedback control for a category of single-input and single-output nonlinear systems in nonstrict-feedback form. Unmodeled dynamics and input constraint are considered in the system. Fuzzy logic systems are employed to identify unknown nonlinear characteristics existing in systems. An appropriate Lyapunov function is chosen to ensure unmodeled dynamics to be input-to-state practically stable. A smooth function is introduced to tackle input saturation. In order to overcome the difficulty of controller design for nonstrict-feedback system in backstepping design process, a variables separation method is introduced. Moreover, based on small-gain technique, an adaptive fuzzy controller is designed to guarantee all the signals of the resulting closed-loop system to be bounded. Finally, two illustrative examples are given to validate the effectiveness of the new design techniques.

AB - This paper investigates the problem of adaptive fuzzy state-feedback control for a category of single-input and single-output nonlinear systems in nonstrict-feedback form. Unmodeled dynamics and input constraint are considered in the system. Fuzzy logic systems are employed to identify unknown nonlinear characteristics existing in systems. An appropriate Lyapunov function is chosen to ensure unmodeled dynamics to be input-to-state practically stable. A smooth function is introduced to tackle input saturation. In order to overcome the difficulty of controller design for nonstrict-feedback system in backstepping design process, a variables separation method is introduced. Moreover, based on small-gain technique, an adaptive fuzzy controller is designed to guarantee all the signals of the resulting closed-loop system to be bounded. Finally, two illustrative examples are given to validate the effectiveness of the new design techniques.

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Adaptive Fuzzy Control of Nonlinear Systems with Unmodeled Dynamics and Input Saturation Using Small-Gain Approach

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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