1.School of Automation, Northwestern Polytechnical University, Xi’an 710000, China; 2. School of Information and Control Engineering, Liaoning Shihua University, Fushun 113000, China.
[1]Xu Y R,Ford J,Becker E,et al.A BP-neural network improvement to hop-counting for localization in wireless sensor networks[M]//Tools and Applications with Artificial Intelligence.Berlin:Springer Berlin Heidelberg,2009:11-23. [2]徐林,张宇献,王建辉,等.基于多值编码GA-BP混合算法的板形板厚综合预测控制[J].东南大学学报:自然科学版,2005,35(11):132-136.(Xu Lin,Zhang Yu-xian,Wang Jian-hui,et al.Predictive control of strip flatness and gauge complex control based on hybrid GA-BP algorithm with multi-encoding[J].Journal of Southeast University:Natural Science Edition,2005,35(11):132-136.) [3]Pendharkar P C.A comparison of gradient ascent,gradient descent and genetic-algorithm-based artificial neural networks for the binary classification problem[J].Expert Systems,2007,24(2):65-86. [4]侯媛彬,杜京义,汪梅.神经网络[M].西安:西安电子科技大学出版社,2007:15-25.(Hou Yuan-bin,Du Jing-yi,Wang Mei.Neural network [M].Xi′an:Xi′an Electronic and Science University Press,2007:15-25.) [5]周德俭,吴斌.智能控制[M].重庆:重庆大学出版社,2005:88-98.(Zhou De-jian,Wu Bin.Intelligent control[M].Chongqing:Chongqing University Press,2005:88-98.) [6]董海鹰.智能控制理论及应用[M].北京:中国铁道出版社,2006:122-142.(Dong Hai-ying.Intelligent control theory and application [M].Beijing:China Railway Press,2006:122-142.) [7]Zhang B L,Wang J G.The analysis and simulation of first-order inverted pendulum control system based on Lqr[C]// 3rd International Symposium on Information Processing.Washington D C,2010:447-449. [8]Yu J,Fang J.Inverted pendulum RBF neural network PID controller design[C]// IEEE 2014 International Symposium on Computer,Consumer and Control (IS3C).Taichung,2014:560-562.