Design of PID Controller Using Hybrid Particle Swarm Optimization

This study attempts to propose a hybrid particle swarm optimization (PSO) based on grey relational analysis and the mutation strategy. In the proposed hybrid PSO, the determination of the algorithm parameters (the inertia weight and the acceleration coefficients) for a particle is depended upon the grey relational grade of that particle. The algorithm parameters are varying over the generations. Also they may differ from different particles. Besides, a mutation strategy is introduced to speed up the search process of the proposed PSO algorithm. Finally, the hybrid PSO algorithm is applied to optimize the parameters of the proportional-integral-derivative (PID) controller. Simulation and experiment results are compared with the standard PSO algorithm and genetic algorithm to demonstrate the search performance of the proposed method.