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System identification method for Hammerstein model based on improved differential evolution algorithm


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System identification method for Hammerstein model based on improved differential evolution algorithm
Xiong Weili12Chen Minfang2Wang Xiao2Xu Baoguo2
1.Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education); 2.School of Internet of Things Engineering,Jiangnan University,Wuxi 214122,China
differential evolution algorithm adequate variation nonlinear system identification Hammerstein model
For the nonlinear system of Hammerstein model,a method for nonlinear system identification is proposed based on the differential evolution algorithm(DE).The problem of nonlinear system identification is transformed into an optimization problem in parameter space.In order to enhance the performance of the DE identification,this paper proposes an adaptive mutation differential evolution algorithm(MDE).The parameter of the Hammerstein model in early stage can keep the individuals diversifying to avoid premature convergence.The mutation rate is gradually reduced so as not to damage the optimal solution.The MDE algorithm is more accurate than the DE,and the MDE algorithm has the higher nonlinear recognition ability.


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Last Update: 2013-08-31