On-line Identification Method of Continuous-Time Nonlinear Systems Using Radial Basis Function Network Model Adjusted by Genetic Algorithm(<Special Section>Nonlinear Theory and its Applications)
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概要
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This paper deals with an on-line identification method based on a radial basis function (RBF) network model for continuous-time nonlinear systems. The nonlinear term of the objective system is represented by the RBF network. In order to track the time-varying system parameters and nonlinear term, the recursive least-squares (RLS) method is combined in a bootstrap manner with the genetic algorithm (GA). The centers of the RBF are coded into binary bit strings and searched by the GA, while the system parameters of the linear terms and the weighting parameters of the RBF are updated by the RLS method. Numerical experiments are carried out to demonstrate the effectiveness of the proposed method.
- 社団法人電子情報通信学会の論文
- 2004-09-01
著者
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Takata Hitoshi
Department Of Electrical And Electronics Engineering Kagoshima University
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Hachino Tomohiro
Department Of Electrical And Electronics Engineering Kagoshima University
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Takata Hitoshi
Department Of Computer Science Kyushu Institute Of Technology
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