PID Neural Network Control of Hydraulic Roll Gap Control System

摘要：

Based on BP neural network to control the complex hydraulic gap control (HGC) system and point out the boundness of selection uncertainty for the BP neural network layers and neurons and the randomness of connection weights between layers. In this paper, an improved PID neural network (PIDNN) is proposed to make trapezoidal integral transform for hidden integral neuron nodes and to make incomplete differential transformation for hidden differential neuron nodes. The output function of each network node is hyperbolic tangent function to replace proportion threshold function. To control the hydraulic gap system by improved PIDNN, the simulation results show that the improved control has better efficiency and tracking characteristics.

关键词： magnetic hydraulic gap control neural network back propagation PID control

作者: Jing Zhang Yutao Fan Weifeng Zhong Junshan Gao Tingting Guan Yanwen Liu

作者单位: College of Automation, Harbin University of Science and Technology, Harbin China Zoomlion Heavy Industry Science and Technology Co.,.Ltd, Changsha China College of Automation, Harbin Engineering University, Harbin China

会议类型: 国际会议

会议名称: 2012 International Conference on Measurement,Information and Control(2012测量、信息与控制国际会议 ICMIC2012)

会议地点: 哈尔滨

会议语种:英文

页码: 791-795

在线出版日期: 2012-05-18（万方平台首次上网日期，不代表论文的发表时间）