Optimal LQG Controller for Variable Speed Wind Turbine Based on Genetic Algorithms | Zendy

René Barrera-Cárdenas | Zendy; Marta Molinas | Zendy

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Optimal LQG Controller for Variable Speed Wind Turbine Based on Genetic Algorithms

Author(s) -

René Barrera-Cárdenas,

Marta Molinas

Publication year - 2012

Publication title -

energy procedia

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.474

H-Index - 81

ISSN - 1876-6102

DOI - 10.1016/j.egypro.2012.03.021

Subject(s) - linear quadratic gaussian control , control theory (sociology) , optimal projection equations , linear quadratic regulator , weighting , kalman filter , controller (irrigation) , optimal control , engineering , turbine , optimal design , mathematics , computer science , mathematical optimization , control (management) , medicine , artificial intelligence , biology , agronomy , radiology , mechanical engineering , statistics

Linear Quadratic Gaussian (LQG) control methodology shows useful properties of good performance and robust-ness in controller design applied to wind turbine. Typically, in the design procedure LQG method is necessary to select weighting matrices in order to solve the Algebraic Riccati Equations and then get the matrices Kalman Filter gain and optimal state-feedback. In order to optimize a LQG control applied to Double-Fed Induction Generator in wind power system, a Genetic Algorithms (GA) adapted to get the best values of the element of weighting matrices is proposed in this paper. The performance indices ISE and ITSE are a good alternative to obtain the tness function to design LQG controllers with GA. The simulation results show the high effectiveness of this optimal design method

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