首页> 外文会议>Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on >A method identifying the parameters of Bounc-Wen hysteretic nonlinear model based on genetic algorithm
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A method identifying the parameters of Bounc-Wen hysteretic nonlinear model based on genetic algorithm

机译:基于遗传算法的Bounc-Wen磁滞非线性模型参数辨识方法

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The Bounc-Wen model (Wen, 1976) is a typical hysteretic nonlinear model, and its parameter identification is very important. Existing identification methods depend heavily on the given initial values of the parameters. Based on the advantages of genetic algorithms (GA), this paper builds the fitness function corresponding to the problem and adopts the crossover and mutation between the gene code strings of the same variables, improving the convergence rate of GA. The example proves that this method is feasible.
机译:Bounc-Wen模型(Wen,1976年)是典型的滞后非线性模型,其参数识别非常重要。现有的识别方法在很大程度上取决于给定的参数初始值。基于遗传算法的优点,建立了与问题对应的适应度函数,并采用了相同变量的基因代码串之间的交叉变异,提高了遗传算法的收敛速度。算例表明该方法是可行的。

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