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A robust system stabilizer configuration using artificial neural network based on linear optimal control (student paper competition)

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3 Author(s)
M. Z. Youssef ; Dept. of Electr. & Comput. Eng., Queen's Univ., Kingston, Ont., Canada ; P. K. Jain ; E. A. Mohamed

An efficient configuration of an adaptive power system stabilizer (PSS) based on the artificial neural network (ANN) and the linear optimal control (LOC) is presented in this paper. The proposed PSS combines the advantages of conventional stabilizer (CPSS), optimizing LOC strategy and the quick response of ANN. The ANN was trained using the data generated by the optimal control stabilizer (LOC-PSS). Different PSSs are presented for performance comparison. MATLAB simulations prove that the proposed PSS significantly improves the dynamic response of the power system over various loading conditions, and different disturbances.

Published in:

Electrical and Computer Engineering, 2003. IEEE CCECE 2003. Canadian Conference on  (Volume:1 )

Date of Conference:

4-7 May 2003