K.S. Al-Olimat, G. Girman, E.J. Kurtz, and H.J. Swarthout III (USA)
-- Adaptive control, fuzzy logic, minimum variance, multiple models, synchronous machine, self tuning, stabilizer.
-- In this paper, a self-tuning regulator (STR) with multiple identification models and a minimum variance controller that uses fuzzy logic evaluation will be presented. The STR will use recursive least squares algorithms with different order identification models to best model the plant at any given moment, and an error minimization algorithm will select the one model that has the least identification error in comparison to the plant output. The parameters of that model will then be scaled using fuzzy logic evaluation to drive the error between the output and reference towards zero as quickly as possible. This controller design is applied to a synchronous machine in order to control the speed. The overall improved performance of the control system using this design is verified through simulations when compared to existing stabilizer as well as classical STR assemblies.
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