Fuzzy gain scheduling: controller and observer design based on Lyapunov method and convex optimization

Addresses model-based fuzzy control. A constructive and automated method for the design of a gain-scheduling controller is presented. Based on a given Takagi-Sugeno fuzzy model of the plant, the controller is designed such that stability and prescribed performance of the closed loop are guaranteed....

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Bibliographic Details
Published in:IEEE transactions on fuzzy systems 2003-06, Vol.11 (3), p.285-298
Main Authors: Korba, P., Babuska, R., Verbruggen, H.B., Frank, P.M.
Format: Article
Language:English
Subjects:
Automatic control
Design engineering
Design methodology
Design optimization
Error correction
Errors
Fuzzy
Fuzzy control
Fuzzy logic
Fuzzy set theory
Fuzzy systems
Linear matrix inequalities
Lyapunov method
Mathematical models
Optimization
Stability
State estimation
Takagi-Sugeno model
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Summary:Addresses model-based fuzzy control. A constructive and automated method for the design of a gain-scheduling controller is presented. Based on a given Takagi-Sugeno fuzzy model of the plant, the controller is designed such that stability and prescribed performance of the closed loop are guaranteed. These properties are valid in a wide working range around an equilibrium without restrictions to slowly varying trajectories. The synthesis is based on linear matrix inequalities and convex optimization techniques. If required, a fuzzy state estimator and an extended controller can be included, providing a zero steady-state error in the presence of disturbances and modeling errors. The proposed method has been applied to a control of a laboratory liquid-level process. Hence, the performance has been evaluated in simulations as well as in real-time control.
ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2003.812680