一种辨识Wiener-Hammerstein模型的新方法

New method for identification of Wiener-Hammerstein model

针对非线性Wiener-Hammerstein模型,提出利用粒子群优化算法对非线性模型进行辨识的新方法.该方法的基本思想是将非线性系统的辨识问题转化为参数空间上的优化问题;然后采用粒子群优化算法获得该优化问题的解.为了进一步增强粒子群优化算法的辨识性能,提出利用一种混合粒子群优化算法.最后,仿真结果验证了该方法的有效性和可行性.

For nonlinear Wiener-Hammerstein model, a method for nonlinear system identification is proposed by using particle swarm optimization （PSO） algorithm. The basic idea of the method is that the problems of nonlinear system identification is changed into optimization problems in parameter space and the PSO is then adopted to solve the optimization problem. In order to enhance the performance of the PSO identification, a hybrid particle swarm optimization （HPSO） algorithm is also adopted. Finally, simulation results show the effectiveness and the feasibility of the proposed method.