[1]张先鹤[1],詹习生[1].CMAC与非线性PID复合控制器在机器人中的应用[J].河北工业科技,2007,24(3):155-158.
[2]Xu Guozheng, Song Aiguo,Li Huijun. Adaptive Im-pedance Control for Upper- limb Rehabilitation Ro-bot Using Evolutionary Dynamic Recurrent FuzzyNeural Network[JJ. Journal of Intelligent and Ro-botic Systems: Theory and Applications, 2011, 62(3/4):501-525.
[3]Liu Dongsheng,Ju Chunhua. Application of An Im-proved BP Neural Network in Business Forecasting[C]//Proceedings of the World Congress on Intelli-gent Control and Automation. Dalian, 2006 : 2700 -2704.
[4]Radulovic J, Rankovic V. Feedforward Neural Net-work and Adaptive Network — based Fuzzy Infer-ence System in Study of Power Lines [J].ExpertSystems with Applications,2010,37(1):165-170.
[5]Guo Beitao, Liu Hongyi, Luo Zhong, et al. AdaptivePID Controller Based on BP Neural Network[C]//2009 International Joint Conference on Artificial In-telligence. Hainan, 2009 : 148-150.
[6]Gao Shuangxi,Cao Shufu,Zhang Ying. Research onPID Control Based on BP Neural Network and ItsApplication[C]//20l0 2nd International Asia Con-ference on Informatics in Control,Automation andRobotics. Wuhan,2010:91-94.
[7]Li Xiaozhong,Li Qiu. A Parameter Adjustment Al-gorithm of BP Neural Network[C3//Proceedings of2008 3rd International Conference on IntelligentSystem and Knowledge Engineering. Xiamen, 2008:892-895.
[8]Lazzus? Juan A. Autoignition Temperature Predic-tion Using An Artificial Neural Network with Parti-cle Swarm Optimization[J3. International Journal ofThermophysics,2011,32(5) : 1-17.
[9]Yin Fei,Mao Huajie,Hua Lin. A Hybrid of BackPropagation Neural Network and Genetic Algorithmfor Optimization of Injection Molding Process Pa-rameters [J]. Materials and Design,2011, 32 ( 6 ):3457-3464.
[10]Shen Changyu, Wang Lixia, Li Qian. Optimizationof Injection Molding Process Parameters UsingCombination of Artificial Neural Network and Ge-netic Algorithm Method CJ].Journal of MaterialsProcessing Technology,2007 ,183(2/3) :412-418.
[11]Lee Z J,Ying K C, Chen S C,et al. ApplyingPSO—based BPN for Predicting the Yield Rate ofDRAM Modules Produced Using Defective ICs[J].International Journal of Advanced Manufac-turing Technology.2010,49(9/12):987-999.
[12]Upenda J,Gupta C P,Singh G K,et al. PSO andANN _ based Fault Classification for ProtectiveRelaying [ J]. IET Generation, Transmission andDistribution,2010,4(10) :1197-1212.
[13]Baczynski D. Application of Particle Swarm Opti-mization Algorithm in Process of Artificial NeuralNetworks Training for Short Term Forecasting[J].Rynek Energii,2010(4) :52-56.
[14]Elragal,Hassan M. Improving Neural NetworksPrediction Accuracy Using Particle Swarm Opti-mization Combiner [ J ].International Journal ofNeural Systems,2009,19(5) : 387-393.
[15]刘金琨.先进PID控制及MATLAB仿真[M].北京:电子工业出版社,2006.
[16]Kenned Y J, Eberhart R C. Particle Swarm Optimi-zation [C]//Proceedings of IEEE InternationalConference on Neural Networks. Perth, WA, 1995 :1942-1948.
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