The fuzzy parameter varying (FPV) system is a mathematical model proposed to handle nonlinear time-varying dynamical systems encountered in engineering, which has some essential advantages in handling time-varying models. In this article, a new relaxation approach is proposed for the analysis and controller design of the FPV system. Different from the current results on the FPV system, the proposed approach employs the fuzzy Lyapunov function and full block S-procedure to reduce the conservatism in analysis. Furthermore, the relaxation technique proposed in this article can be also used in solving controller synthesis problem effectively. As a result, a design procedure of non-PDC output feedback gain-scheduling controller is provided to ensure asymptotic stability of the closed-loop FPV system. A numerical example is provided to illustrate the proposed method.
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ASME 2018 Dynamic Systems and Control Conference
September 30–October 3, 2018
Atlanta, Georgia, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-5189-0
PROCEEDINGS PAPER
Stability Analysis and Controller Design for Fuzzy Parameter Varying Systems Based on Fuzzy Lyapunov Function
Xiaojun Ban,
Xiaojun Ban
Harbin Institute of Technology, Harbin, China
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Hongyang Zhang,
Hongyang Zhang
Harbin Institute of Technology, Harbin, China
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Fen Wu
Fen Wu
North Carolina State University, Raleigh, NC
Search for other works by this author on:
Xiaojun Ban
Harbin Institute of Technology, Harbin, China
Hongyang Zhang
Harbin Institute of Technology, Harbin, China
Fen Wu
North Carolina State University, Raleigh, NC
Paper No:
DSCC2018-8996, V001T01A005; 10 pages
Published Online:
November 12, 2018
Citation
Ban, X, Zhang, H, & Wu, F. "Stability Analysis and Controller Design for Fuzzy Parameter Varying Systems Based on Fuzzy Lyapunov Function." Proceedings of the ASME 2018 Dynamic Systems and Control Conference. Volume 1: Advances in Control Design Methods; Advances in Nonlinear Control; Advances in Robotics; Assistive and Rehabilitation Robotics; Automotive Dynamics and Emerging Powertrain Technologies; Automotive Systems; Bio Engineering Applications; Bio-Mechatronics and Physical Human Robot Interaction; Biomedical and Neural Systems; Biomedical and Neural Systems Modeling, Diagnostics, and Healthcare. Atlanta, Georgia, USA. September 30–October 3, 2018. V001T01A005. ASME. https://doi.org/10.1115/DSCC2018-8996
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