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.
@article{bwmeta1.element.bwnjournal-article-amcv19i4p619bwm,
author = {Ruiyun Qi and Mietek A. Brdys},
title = {Indirect adaptive controller based on a self-structuring fuzzy system for nonlinear modeling and control},
journal = {International Journal of Applied Mathematics and Computer Science},
volume = {19},
year = {2009},
pages = {619-630},
zbl = {1300.93100},
language = {en},
url = {http://dml.mathdoc.fr/item/bwmeta1.element.bwnjournal-article-amcv19i4p619bwm}
}
Ruiyun Qi; Mietek A. Brdys. Indirect adaptive controller based on a self-structuring fuzzy system for nonlinear modeling and control. International Journal of Applied Mathematics and Computer Science, Tome 19 (2009) pp. 619-630. http://gdmltest.u-ga.fr/item/bwmeta1.element.bwnjournal-article-amcv19i4p619bwm/
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