An Identification Approach of Hammerstein Model

摘要：

An identification method of Hammerstein model is investigated in this paper. First of all, the key term separation technique is introduced. Next, an auxiliary model is established. Accordingly, the identification problem of the Hammerstein model is cast as nonlinear function optimization problem over parameter space. Then, the estimation values of the parameters of the model are obtained based on particle swarm optimization (PSO) algorithm. In order to further enhance the precision and stability of the identification algorithm, a modified particle swarm optimization (MPSO) algorithm is applied to search the parameter space to find the optimal parametric estimation values of the model. Finally, simulation experiments show that the proposed algorithm is effective and reasonable.

关键词： Hammerstein model Parameter identification Key term separation principle Auxiliary model Particle swarm optimization (PSO) algorithm

作者: Feng Wang Keyi Xing Xiaoping Xu Huixia Liu

作者单位: State Key Laboratory for Manufacturing Systems Engineering and Systems Engineering Institute, Xi’an State Key Laboratory for Manufacturing Systems Engineering and Systems Engineering Institute, Xi’an School of Sciences, Xi’an University of Technology, Xi’an, 710054, China

会议类型: 国际会议

会议名称: The 22nd China Control and Decision Conference(2010年中国控制与决策会议)

会议地点: 徐州

会议语种:英文

页码: 607-612

在线出版日期: 2010-05-26（万方平台首次上网日期，不代表论文的发表时间）