<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>In this paper, a unified nonlinear modeling and control scheme is presented. A self-structuring Takagi-Sugeno (T-S) fuzzy model is used to approximate the unknown nonlinear plant based on I/O data collected on-line. Both the structure and the parameters of the T-S fuzzy model are updated by an on-line clustering method and a recursive least squares estimation (RLSE) algorithm. The rules of the fuzzy model can be added, replaced or deleted on-line to allow a more flexible and compact model structure. The overall controller consists of an indirect adaptive controller and a supervisory controller. The former is the dominant controller, which maintains the closed-loop stability when the fuzzy system is a good approximation of the nonlinear plant. The latter is an auxiliary controller, which is activated when the tracking error reaches the boundary of a predefined constraint set. It is proven that global stability of the closed-loop system is guaranteed in the sense that all the closed-loop signals are bounded and simulation examples demonstrate the effectiveness of the proposed control scheme.</p></abstract>

In this paper, a unified nonlinear modeling and control scheme is presented. A self-structuring Takagi-Sugeno (T-S) fuzzy model is used to approximate the unknown nonlinear plant based on I/O data collected on-line. Both the structure and the parameters of the T-S fuzzy model are updated by an on-line clustering method and a recursive least squares estimation (RLSE) algorithm. The rules of the fuzzy model can be added, replaced or deleted on-line to allow a more flexible and compact model structure. The overall controller consists of an indirect adaptive controller and a supervisory controller. The former is the dominant controller, which maintains the closed-loop stability when the fuzzy system is a good approximation of the nonlinear plant. The latter is an auxiliary controller, which is activated when the tracking error reaches the boundary of a predefined constraint set. It is proven that global stability of the closed-loop system is guaranteed in the sense that all the closed-loop signals are bounded and simulation examples demonstrate the effectiveness of the proposed control scheme.

Indirect adaptive controller based on a self-structuring fuzzy system for nonlinear modeling and control

College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, P. R. China

Department of Electronic, Electrical and Computer Engineering, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK

Department of Control Systems Engineering, Faculty of Electrical and Control Engineering, Gdańsk University of Technology, ul. Narutowicza 11/12, 80-952 Gdańsk, Poland

International Journal of Applied Mathematics and Computer Science

In this paper, a unified nonlinear modeling and control scheme is presented. A self-structuring Takagi-Sugeno (T-S) fuzzy model is used to approximate the...

Indirect adaptive controller based on a self-structuring fuzzy system for nonlinear modeling and control

Published Online: Dec 31, 2009

Page range: 619 - 630

DOI: https://doi.org/10.2478/v10006-009-0049-8

Keywords
fuzzy control, self-structuring fuzzy model, on-line modeling, stability

This content is open access.

Indirect adaptive controller based on a self-structuring fuzzy system for nonlinear modeling and control

Published Online: Dec 31, 2009

Page range: 619 - 630

DOI: https://doi.org/10.2478/v10006-009-0049-8

Keywordsfuzzy control, self-structuring fuzzy model, on-line modeling, stability

This content is open access.

Keywords
fuzzy control, self-structuring fuzzy model, on-line modeling, stability