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Indirect adaptive controller based on a self-structuring fuzzy system for nonlinear modeling and control
Abstract
In this paper, a unified nonlinear modeling and control scheme is presented. A self-structuring Takagi-Sugeno (T-S) fuzzymodel is used to approximate the unknown nonlinear plant based on I/O data collected on-line. Both the structure and theparameters 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 andcompact model structure. The overall controller consists of an indirect adaptive controller and a supervisory controller. Theformer is the dominant controller, which maintains the closed-loop stability when the fuzzy system is a good approximationof the nonlinear plant. The latter is an auxiliary controller, which is activated when the tracking error reaches the boundaryof a predefined constraint set. It is proven that global stability of the closed-loop system is guaranteed in the sense that allthe closed-loop signals are bounded and simulation examples demonstrate the effectiveness of the proposed control scheme.
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- Category:
- Articles
- Type:
- artykuł w czasopiśmie wyróżnionym w JCR
- Published in:
-
International Journal of Applied Mathematics and Computer Science
no. 19,
pages 619 - 630,
ISSN: 1641-876X - Language:
- English
- Publication year:
- 2009
- Bibliographic description:
- Qi R., Brdyś M.: Indirect adaptive controller based on a self-structuring fuzzy system for nonlinear modeling and control// International Journal of Applied Mathematics and Computer Science. -Vol. 19, nr. 4 (2009), s.619-630
- Verified by:
- Gdańsk University of Technology
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