Radial-base-function, Genetic-Algorithm and fuzzy logic approach for real-time tuning of PID Controller in AVR System

摘要

Optimal tuning of proportional-integral-derivative (PID) controller parameter is necessary for thematic factory operation of an automatic voltage regulator (AVR) system. This study presents a novel combined genetic algorithm (GA), radial-basis function network (RBF) identification and fuzzy logic control approaches to determine the optimal PID controller parameters in AVR system. The problem of obtaining the optimal AVR and PID controller parameters is formulated as an optimization problem and RBF tuning by GA is applied to solve the optimization problem. The proposed approach has resulted in AVR and PID controller with a good response. Whereas, RBF tuning by GA for various operating conditions are used to develop the rule base of the Sugeno fuzzy system and design fuzzy PID controller (GRBFF-PID) of AVR system to improve the system response. The GRBFF-PID controller is found to possess excellent features of easy implementation, stable convergence characteristic, good computational efficiency and high-quality solution. Our simulation provides high response of an AVR system compared to the real-code genetic algorithm (RGA), a linear-quadratic regulator (LQR) method and GA. We assert that GRBFF-PID is highly efficient and robust in improving the system response of an AVR system.