Abstract
The objective of this paper is to develop an adaptive intelligent controller for STATCOM installed in multimachine system to damp inter area low frequency oscillations over wide operating range using wide area signals. The paper highlights the hybrid tunable controller where the performance of well designed Takagi-Sugeno fuzzy controller is enhanced by using the same training data that is used for designing a neural controller. Based on back propagation algorithm and method of least square estimation the fuzzy inference rule base is tweaked according to the data from which they are modeled. Thus leading to better system identification and providing better control characteristics. Based on eigenvalue sensitivity the wide area signals are selected as input to the hybrid controller. The effectiveness of the proposed controller is tested on IEEE 12 bus benchmark system and is compared with the conventional fuzzy and neural controller where all the controller are fed with selected wide area signals.
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