[1] Shah J V,Poon Chi-Sang.Linear independence of internal representations in multilayer perceptrons[J]. IEEE Trans. on Neura1 Networks (S1550-4859), 1999, 10(1): 10-18. [2] Mohammad Reza Bakhtiarizadeh,Mohammad Moradi- Shahrbabak, Mansour Ebrahimi, etal. Neural network and SVM classifiers accurately predict lipid binding proteins, irrespective of sequence homology[J]. Journal of Theoretical Biology (S0022-5193), 2014, 356(9): 213-222. [3] Wai R, Shih L.Adaptive fuzzy-neural-network design for voltage tracking control of a DC-DC boost converter[J]. IEEE Trans Power Electron (S0885-8993), 2012, 27(4): 2104-2115. [4] Liang Qi, Hongbo Shi.Adaptive position tracking control of permanent magnet synchronous motor based on RBF fast terminal sliding mode control[J]. Neurocomputing (S0925-2312), 2013, 115(9): 23-30. [5] 韩力群. 人工神经网络教程 [M]. 北京: 北京邮电大学出版社, 2006. (Han Liqin.Artificial neural network tutorial [M]. Beijing, China: Beijing University of Posts and Telecommunications Press, 2006.) [6] 高隽. 人工神经网络原理及仿真实例 [M]. 2版. 北京:机械工业出版社, 2007. (Gao Jun.Principle of artificial neural network and its simulation [M]. Second Edition. Beijing, China: China machine Press, 2007.) [7] 刘金琨. 智能控制[M]. 2版. 北京: 电子工业出版社, 2009. (Liu Jinkun.Intelligent control [M]. Second Edition. Beijing, China: Publishing House of Electronics Industry, 2009.) [8] 韩宇光, 曹军, 朱良宽. 刨花板热压控制系统BP神经网络整定PID控制 [J]. 自动化技术与应用, 2011, 30(12): 8-10. (HAN Yuguang, CAO Jun, ZHU Liangkuan.Particleboard Hot Press Control Based on BP Neural Networks PID Method [J]. Techniques of Automation and Applications Techn Autom Appl.., 2011, 30(12): 8-10.) [9] 林青松, 姚玉菲, 王军晓. 智能PID参数自整定技术在伺服系统中的应用[J]. 自动化仪表, 2011, 32(2): 59-62. (Lin Qingsong, Yao Yufei, Wang Junxiao.Application of I ntelligent PID Parameters Auto-tuning Technology in Servo System[J]. PROCESS AUTOMATION INSTRUMENTATION, 2011, 32(2): 59-62.) [10] Man Chuntao, Yang Xu, Zhang Liyong.A New learning algorithm for RBF neural networks[C]//Systems and Control in Aerospace and Astronautics. USA. IEEE, 2008:1-4. [11] 李小凡. 基于RBF神经网络整定的PID控制器设计[J]. 兵工自动化, 2009, 28(1): 45-46. (LI Xiaofan.Design of PID Controller Based on RBF Neural Network[J]. Ordnance Industry Automation, 2009, 28(1): 45-46.) [12] 杨小辉, 徐颖强, 李世杰, 等. 广义回归神经网络(GRNN)在AMT挡位判别中的应用[J]. 机械设计与制造, 2009 (5): 72-74. (YANG Xiaohui, XU Yingqiang, LI Shiji, et al.GRNN in application of discriminant AMT gear-shift[J]. Machinery Design & Manufacture, 2009 (5): 72-74.) [13] 徐富强, 郑婷婷,方葆青. 基于广义回归神经网络(GRNN) 的函数逼近[J].巢湖学院学报, 2010, 12(6):11-16. (Xu Fuqiang, Zheng Tingting, Fang Baoqing.Function Approximation Based on General Regression Neural Nerwork (GRNN)[J]. Journal of Chaohu Colleg, 2010, 12(6):11-16. [14] 徐耀群, 孙明. 混沌神经网络及其应用 [M]. 哈尔滨:黑龙江大学出版社, 2012. (Xu Yaoqun, Sun Ming.Chaotic neural network and its application [M]. Haerbin, China: Heilongjiang University press, 2012.) [15] 刘加存, 梅其祥, 李春辉. 基于频分神经网络和预测控制的PID参数整定研究[J]. 系统仿真学报, 2014, 26(5): 1176-1179. (Liu Jiacun,Mei Qixiang,Li Chunhui.Research of PID Tuning Based on Frequency_Divide Neural Network and Model Predictive Control[J]. Journal of System Simulation, 2014, 26(5): 1176-1179.) [16] 张怀相, 原魁, 邹伟. 基于迭代学习控制的PID控制器设计[J]. 系统工程与电子技术, 2006, 18(8): 1225-1228. (Zhang Huaixiang, Yuan Kui, Zou Wei.Design of PID controller based on iterative learning control[J]. Systems Engineering and Electronics, 2006, 18(8): 1225-1228.) [17] 杨友林. 基于神经网络的PID参数自整定控制及其Matlab仿真研究[J]. 甘肃联合大学学报(自然科学版), 2011, 25(4): 61-63. (Yang Youlin.The Research of Parameter Self-Tuning PID Controller based on Neural Network and Matlab Simulation[J]. Journal of Gansu Lianhe University(Natural Sciences), 2011, 25(4): 61-63.) |