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《Science Technology and Engineering》 2008-08
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Vibration Reduction Method of Neural Network-Fuzzy Control Based on Genetic Algorithm

NING Xiang-liang, HUANG Dong-yang, TAN Ping1, ZHOUFu-lin1( Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, P. R. China;Earthquake Engineering Research Test Center, Guangzhou University1, Guangzhou 510405, P. R. China)  
Using genetic algorithmto optimize the control rules to overcome the difficulty of acquisition of empir-ical rules for fuzzy logic controller, a weight-sum-approach method is employed here to realize the multi-objectiveoptimal control. In order to reduce time delay, BP neural network is employed here to predict the inputs of fuzzylogic controller also. Trough the analysis of76-story wind-excited Benchmark model, the result shows that the neu-ral network-fuzzy control (NN-FLC) method performs closely as the LQG under ideal condition; but in the case ofuncertainty in stiffness of structures, the stability and robustness of this control method have been demonstrated, itperforms much better than LQG.
【Fund】: 国家自然科学基金项目(50608021);; 国家教育部博士点专项基金(20061078001)资助
【CateGory Index】: TU352.1
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