Swarm size and inertia weight selection of Particle Swarm Optimizer in system identification

The performance of Particle Swarm Optimizer (PSO) is not only related with the inertia weight, but also with the swarm size. In a typical second-order discrete transfer function case, an analysis about swarm size and inertia weight selection on PSO optimizing performance in system identification is given. Through simulations of different sets of the two parameters, this paper gives a selection of the two parameters witch make PSO a better performance on convergence rate and identification accuracy in system identification.