Real-coded genetic algorithm and fuzzy logic approach for real-time tuning of proportional-integral - derivative controller in automatic voltage regulator system

Optimal tuning of proportional-integral-derivative (PID) controller parameters is necessary for the satisfactory operation of automatic voltage regulator (AVR) system. This study presents a combined genetic algorithm (GA) and fuzzy logic approach to determine the optimal PID controller parameters in AVR system. The problem of obtaining the optimal PID controller parameters is formulated as an optimisation problem and a real-coded genetic algorithm (RGA) is applied to solve the optimisation problem. In the proposed RGA, the optimisation variables are represented as floating point numbers in the genetic population. Further, for effective genetic operation, the crossover and mutation operators which can deal directly with the floating point numbers are used. The proposed approach has resulted in PID controller with good transient response. The optimal PID gains obtained by the proposed GA for various operating conditions are used to develop the rule base of the Sugeno fuzzy system. The developed fuzzy system can give the PID parameters on-line for different operating conditions. The suitability of the proposed approach for PID controller tuning has been demonstrated through computer simulations in an AVR system.