Optimization techniques based PID tunning

Abstract

This work presents a several metaheuristic methods employed to enhance the capability of traditional techniques tuning of a Proportional-Integral-Derivative (PID) controller for an Automatic Voltage Regulator (AVR) system. The presented approaches referred to as Particle Swarm optimization (PSO) algorithm, Cuckoo Search optimization (CSO) algorithm, Moth Flame optimization (MFO) algo- rithm, Water Cycle optimization (WCO) algorithm, Teaching-Learning Based optimization (TLBO) algorithm and Hill Climbing optimization (HCO) algorithm. In order to achieve optimal transient re- sponse and improved stability of the considered AVR system, a conventional and modified objective functions are employed to obtain optimized PID controller gains. After that, the step response com- pared with some approaches in literature to show the superiority of our optimized PID controllers, and the root locus, bode plot, robustness and disturbance rejection ability analysis are performed to test the stability of the optimized AVR system. According to the comparison and analysis results, the proposed optimization algorithms based PID controller improve the tracking behaviors of the AVR system, making it suitable for synchronous generator terminal voltage stability.