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六自由度运动平台控制系统的神经网络优化
引用本文:方艺,吴学杰. 六自由度运动平台控制系统的神经网络优化[J]. 中国测试技术, 2006, 32(5): 100-103
作者姓名:方艺  吴学杰
作者单位:西南交通大学牵引动力国家重点实验室,四川,成都,610031
摘    要:阐述了六自由度运动平台的控制原理,并根据控制系统的特点,提出采用基于RBF和BP神经网络来改进常规PID控制器实现系统控制性能。在该控制系统结构中,提出了在RBF网络辨识Jacobian的基础上,将BP神经网络引入了平台控制系统中PID控制器的控制参数在线整定的算法,最后给出了在MATLAB下的具体仿真算法。

关 键 词:六自由度运动平台  BP网络  RBF网络  PID控制  仿真
文章编号:1672-4984(2006)05-0100-04
收稿时间:2005-11-11
修稿时间:2006-01-17

Optimal control system of 6-DOF motive platform based on neural network
FANG Yi,WU Xue-jie. Optimal control system of 6-DOF motive platform based on neural network[J]. China Measurement Technology, 2006, 32(5): 100-103
Authors:FANG Yi  WU Xue-jie
Affiliation:State Key Laboratoy of Traction Power,Southwest Jiaotong University, Chengdu 610031, China
Abstract:This article described the principles of control system of 6-DOF motive platform, According to the characteristics of the control system a neural network controller was proposed for improving the control performance of the traditional PID controller. Tne configuration of the control system was based on RBF and BP neural networks.A new algorithm was put forward, in which parameters of the PID control was optimized online by BP network based on RBF network identifying the Jacobian matrix of the controlled plant. At last, the programming steps under Matlab platform were also mentioned.
Keywords:6- DOF motive platform   BP neural networks   RBF neural networks   PID control   Simulation
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