信息与控制2012，Vol.41Issue(3)：384-390,7.DOI:10.3724/SP.J.1219.2012.00384
Hammerstein模型的改进新型神经动力学辨识方法及其在混合建模中的应用
Hammerstein Model Identification Method Based on the New Improved Neural Dynamics and Its Application to Hybrid Modeling
摘要
Abstract
The matrix format of multi-input multi-output Hammerstein model is deduced, and a kind of the new improved neural dynamics algorithm is proposed. The algorithm can be used to identify many groups of unknown Hammertein model parameters, which improves accuracy and convergence rate. Firstly, the parameters'convergence of the new improved neural dynamics algorithm is analyzed. Then a new hybrid model based on Hammerstein model is deduced to build an error model between actual system and mechanism system. The hybrid model has good compensating effect. Since the new neural dynamics method can adjust Hammerstein model parameters online, the hybrid model can be used to simulate dynamic behavior of complex processes in a large scale exactly. The rationality and efficiency of the presented method are demonstrated by simulation experiment.关键词
Hammerstein模型/神经动力学/非线性/混合模型Key words
Hammerstein model/ neural dynamics/ nonlinear/ hybrid model分类
信息技术与安全科学引用本文复制引用
王双剑,楚纪正..Hammerstein模型的改进新型神经动力学辨识方法及其在混合建模中的应用[J].信息与控制,2012,41(3):384-390,7.基金项目
国家863计划资助项目 (2007AA04Z191). （2007AA04Z191）
