Design of Adaptive Fuzzy-PI Control with the Aid of Rough Set Theory and Its Application to a HVDC System

Abstract

In this paper, the application of fuzzy set theory, genetic algorithms and rough set theory techniques to the control of the High Voltage Direct Current (HVDC) system is studied. A fuzzy adaptive control scheme with the aid of rough set theory via genetic algorithms (GAs) finding the center scaling-factors in place of the classical control is proposed. On the one hand, genetic algorithm gets optimal parameters of an accurate domain model, which tunes the scaling factors of fuzzy adaptive control but is hardly established in a nonliner system. On the other hand, fuzzy adaptive control deals with the dynamics and complexity of responses from a HVDC system in the operation points, by adjusting its control parameters with the aid of rough tuner adaptively. Our study includes a brief introduction to fuzzy sets, fuzzy control and rough set algorithms, both theory and application. We also evaluate the performance of fuzzy adaptive control by simulation in the paper. The focus of our experiments is on the constant current control in HVDC system. The result shows there are many improvements offered by the fuzzy control scheme based on rough set theory in comparison with the conventional HVDC control scheme.