Adaptive Polar Fuzzy logic based Load Frequency Controller
Performance of a Fuzzy logic controller is dependent on sufficient and accurate knowledge base. As the number of rules in a knowledge base increases, its complexity increases which in turn affects the computation time and memory requirements. To overcome these problems, a Polar Fuzzy logic controller is proposed. The aim of the Polar Fuzzy Controller (PFC) is to restore the frequency and tie-line power in a smooth way to its nominal value in the shortest possible time if any load disturbance is applied to any area of power system. In this paper, the PFC is made adaptive using a Genetic algorithm-fuzzy system (GAF) approach. Performance of the simple PFC and adaptive PFC using GAF is compared with fuzzy and conventional PI controllers on a three area system.
ga genetic algorithm gaf adaptive ga with fuzzy system rcga real coded ga pfc polar fuzzy controller flc fuzzy logic controller l m h low medium and high linguistic value fam fuzzy associative memory pc crossover probability pm mutation probability p population number pmax maximum number of population g generation number gmax maximum number of generations lfc load frequency control