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

被引：61

作者：

Korba, P ^{[1
]}

Babuska, R

Verbruggen, HB

Frank, PM

机构：

[1] ABB Switzerland Ltd, CH-5405 Baden, Switzerland

[2] Delft Univ Technol, Delft Ctr Syst & Control, NL-2628 CD Delft, Netherlands

[3] Univ Duisburg, Dept Measurement & Control, Fac Elect Engn, D-47048 Duisburg, Germany

来源：

IEEE TRANSACTIONS ON FUZZY SYSTEMS | 2003年 / 11卷 / 03期

关键词：

fuzzy gain-scheduling; linear matrix inequality (LMI); model-based fuzzy control; performance; quasi-linear parameter varying systems; stability; Takagi-Sugeno (TS) fuzzy models;

D O I：

10.1109/TFUZZ.2003.812680

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper 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.

引用

页码：285 / 298

页数：14

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