Abstract
This work presents a digital adaptive control method, where the controller is designed using a self-tuning structure. Parametric models are identified off line for several differently selected operating points of the plant to form a Local Model Network (LMN), and saved as a look-up table in a microcomputer real time control. During working, a supervisor identifies the actual condition of operation and uses a set of logic fuzzy rules to estimate a plant model as a function of the рrе-identified models for the nearest selected operating points. Then, using this plant model, the controller is designed. This method is employed in the design of a Power System Stabilizer (PSS) and the control obtained for a test with two severe faults showed good performance for this PSS, when compared to a conventional (non adaptive) one.
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