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内蒙古自治区呼和浩特市赛罕区大学西街235号 邮编: 010021
作者机构:School of Mechanical & Vehicular Engineering Beijing Institute of Technology Beijing 10081China Beijing Key Laboratory (Measurement and Control of Mechanical and Electrical System) Beijing Information Science & Technology University Beijing 100081China
出 版 物:《机械工程前沿》 (FRONTIERS OF MECHANICAL ENGINEERING IN CHINA)
年 卷 期:2010年第5卷第4期
页 面:418-422页
核心收录:
学科分类:08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程]
基 金:the Key Laboratory of Modern Measurement & Control Technology (Beijing Information Science & Technology University),Ministry of Education and National Natural Science Foundation of China(50975020) Key Project of Science and Technique Development Plan Supported by Beijing Municipal Commission of Education(KZ200910772001) Funding Project for Academic Human Resources Development in Institutions of Higher Learning Under the Jurisdiction of Beijing Municipalipality(PHR20090518) Beijing Key Laboratory on Measurement and Control of Mechanical and Electrical System(KF20091123206 KF2009112302)
主 题:PID neural network membrane structure
摘 要:Because it is difficult for the traditional PID algorithm for nonlinear time-variant control objects to obtain satisfactory control results, this paper studies a neuron PID controller. The neuron PID controller makes use of neuron self-learning ability, complies with certain optimum indicators, and automatically adjusts the parameters of the PID controller and makes them adapt to changes in the controlled object and the input reference signals. The PID controller is used to control a nonlinear time-variant membrane structure inflation system. Results show that the neural network PID controller can adapt to the changes in system structure parameters and fast track the changes in the input signal with high control precision.