DocumentCode
2366308
Title
An LMI Approach to Fuzzy Pole Cluster for Regulating Wind Energy Conversion System
Author
Besheer, A.H. ; Emara, H.M. ; Aziz, M.M.A.
Author_Institution
Environ. Studies & Res. Inst., Monofiya Univ., El Sadat
fYear
2006
fDate
6-10 Nov. 2006
Firstpage
4367
Lastpage
4372
Abstract
This paper addresses the design of fuzzy state feedback controller that has not only the ability to stabilize the fuzzy model/system but also to control the transient behaviour and closed loop pole location for wind energy conversion system which present interesting control demands and exhibits intrinsic non-linear characteristics. The proposed fuzzy controller is employed to regulate indirectly the power flow in the DC link by regulating the DC current. First, a Takagi-Sugeno fuzzy model is employed to represent a non-linear system. Then a model-based fuzzy controller design utilizing the concept of parallel-distributed compensation is developed. Additional constraints on the closed loop pole location are satisfied. Satisfactory time response and closed loop damping are achieved by forcing the closed loop poles into a suitable sub-region of the left half plane. These conditions are expressed in terms of linear matrix inequalities (LMIs), which can be solved very efficiently using convex optimization techniques. The design techniques are applied to a dynamic model of wind energy conversion system to illustrate the feasibility of the proposed solution
Keywords
closed loop systems; compensation; control system synthesis; convex programming; electric current control; feedback; fuzzy control; linear matrix inequalities; nonlinear control systems; pole assignment; power station control; wind power; wind power plants; DC current regulation; LMI approach; Takagi-Sugeno fuzzy model; closed loop damping; closed loop pole location; convex optimization techniques; fuzzy pole cluster; fuzzy state feedback controller; linear matrix inequalities; nonlinear system; parallel-distributed compensation; power flow; transient behaviour; wind energy conversion system; Damping; Fuzzy control; Fuzzy systems; Load flow; Nonlinear control systems; Power system modeling; State feedback; Takagi-Sugeno model; Time factors; Wind energy;
fLanguage
English
Publisher
ieee
Conference_Titel
IEEE Industrial Electronics, IECON 2006 - 32nd Annual Conference on
Conference_Location
Paris
ISSN
1553-572X
Print_ISBN
1-4244-0390-1
Type
conf
DOI
10.1109/IECON.2006.347522
Filename
4153123
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