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.
Autorzy
Informacje dodatkowe
- Kategoria
- Publikacja w czasopiśmie
- Typ
- artykuł w czasopiśmie wyróżnionym w JCR
- Język
- angielski
- Rok wydania
- 2009
