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《Science Technology and Engineering》 2011-33
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System Parameter Identification Based on Improved Genetic Algorithm

SUN Lei,CHEN Shao-wei,WU Jin-lu (School of Electronic&Information,Northwestern Polytechnical University,Xi'an 710129,P.R.China)  
Traditional genetic algorithms have convergence speed and premature easily in solving specific optimization problems,in case of system parameters identification,an improved genetic algorithm is presented.By selecting reasonable replication strategy,and improving the fitness function calculation,overcomes the prematurity,the diversity of the population is ensured,avoid slow convergence which is resulted by the close fitness value in the later time.The parameters of typical second-order system transfer function by the algorithm are solved.In the case of larger SNR,the estimation is obtained to be almost no bias.Experimental results show the effectiveness of the method.
【CateGory Index】: TP18;N945.14
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