A particle swarm optimization, fuzzy PID controller with generator automatic voltage regulator

Abstract

The role of an intelligent control system with a certain stage of autonomy is prerequisite for effective operation. We designed a particle swarm optimization, fuzzy proportional integral derivative (PSOFPID) controller using MATLAB for a set point voltage and frequency. The projected controller intended to ease the frequency and the terminal potential difference constantly under any operating conditions and loads which can be attained in the wanted range via the rule of the generation system. PSOFPID used to carry out the AVR system auctions main voltage control. The existing algorithm was based on particle swarm optimization (PSO), and Sugeno fuzzy logic (SFL). It required optimal tuning for thematic factory operation of the generation system. The newly developed controller combined the PSO and fuzzy logic control (FLC) to determine the optimal PID controller of generator parameters in the AVR system. The PSOFPID controller was used as a hybrid full control system for the voltage and frequency. Optimal PID gains obtained by a combined PSO and SFL for various operating conditions of PSO (β and know about birds’ no.) were employed to develop the principle subject of the Sugeno fuzzy system. The hybrid controller arranged the control signal based on communication and thereby decreases the voltage error and the swaying in the terminal voltage and frequency control process. An outstanding potential and frequency control presentation was achieved when the projected hybrid controller was broken on the AVR system in synchronous generator to improve the transient response.