Identification of MIMO Hammerstein-Wiener System

摘要：

　　A new approach to identification of multi-input multi-output(MIMO)Hammerstein-Wiener system is presented.The output nonlinear block consists of several single-input single-output(SISO)blocks,one of which is dead zone and saturation nonlinearity.The hinging hyperplane(HH)model expresses the character.The MIMO input nonlinear block is described by multi layer feed forward neural networks.The transfer function matrix indicates the MIMO linear dynamics block.According to the prior structure knowledge,the identification problem is transformed to constrained optimization using prediction error method(PEM).The interior-point method(IPM)is adopted to solve the nonlinear programming.Finally,the simulation examples illustrate the performance and validate the effectiveness of the proposed algorithm.

关键词： Hammerstein-Wiener Hinging hyperplane Neural networks IPM and PEM

作者: Jing Bai Zhizhong Mao Feng Yu Yajun Wang

作者单位: College of Information Science and Engineering,Northeastern University,Shenyang 110004,China;College College of Information Science and Engineering,Northeastern University,Shenyang 110004,China College of Information Science and Engineering,Northeastern University,Shenyang 110004,China;College

会议类型: 国际会议

会议名称: 第26届中国控制与决策会议(2014 CCDC)

会议地点: 长沙

会议语种:英文

页码: 1186-1190

在线出版日期: 2014-05-31（万方平台首次上网日期，不代表论文的发表时间）