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《Journal of Zhejiang University(Engineering Science)》 2010-01
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Adaptive algorithm for recursive identification of Hammerstein systems

CHEN Kun1,LIU Yi 1,2 ,WANG Hai-qing1,SONG Zhi-huan1,LI Ping1(1.Institute of Industrial Process Control,State Key Laboratory of Industrial Control Technology,Zhejiang University,Hangzhou 310027,China;2.Institute of Process Equipment and Control Engineering,Zhejiang University of Technology,Hangzhou 310032,China)  
A new on-line adaptive sparse,recursive identification algorithm of Hammerstein models based on output predictive error was proposed to solve the problems of the least squares support vector regression methods,such as lacking of sparsity and difficult to get a recursive form.The proposed method changes the recursive form,and adaptively chooses the strategy of sparseness/recursion/re-initialization according to the output predictive error.The error accumulation or even divergence problems are avoided and therefore the sparseness and accuracy are improved.The simulation illustrated that compared with the general recursive method,the proposed adaptive algorithm has sparse formulation and simplifies the model while keeping the identification accuracy.Also,the approach is robust and efficient,and it can meet the requirement of online identification.
【Fund】: 国家“863”高技术研究发展计划资助项目(2009AA04Z126);; 国家自然科学基金资助项目(20776128)
【CateGory Index】: TP301.6
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