Nonlinear System Identification Using Particle Swarm Optimization
KE Jing, QIAN Ji-xin ( Institute of Systems Engineering, Zhejiang University, Hangzhou 310027, China )
A nonlinear system identification method using particle swarm optimization is proposed. The problems of nonlinear system identification can be viewed as optimization problems in parameter space, and then the particle swarm optimization algorithm is used to search the parameter space concurrently and efficiently as to find the optimal estimation of the system parameters. The feasibility of the proposed method is demonstrated by the identification of a Hammerstein model.
【CateGory Index】： TP18