Optimised PID-AVR controller design using Artificial Swarm Intelligence Algorithm

Abstract

Power system is consist of voltage regulator to maintain constant voltage. It regulates AC or DC voltages and it is designed as feed-forward and it may include negative feedback control loop. Load at this end changes continuously which requires to restructure the power system, this is carried out through tuned controllers. proportional–integral–derivative controller is commonly used controller in AVR system. It is also called as PID controller. Despite the popularity, tuning of PID control parameter is challenge to plant operators and researches. This research work has used Artificial Swarm Intelligence Algorithm (ASI) for tuning PID AVR parameters optimally. ASI is generally refer as human swarming. This algorithm creates network of all individuals in the group and Artificial intelligence is used to tune the control parameter. It enhances the prediction accuracy and it reduces the required number of iteration as well. This research work has compared the performance of ASI with Artificial bee colony (ABC), genetic algorithm (GA) and Particle Swarm Optimization(PSO) for optimisation of tuning PID controller. Five fitness functions were used to compare performance with existing algorithm. The results show best convergence of ASI algorithm.