Neural Network PID Control System for the FTGS

摘要：

This paper proposes the neural network PID control system for the nonlinear Francis hydroturbine generator set FTGS including the Francis turbine neural network model FTNNM.The neural network model FTNNM reflect nonlinear characteristic of the Francis turbine truly.In the neural network PID control system,the regular PID controller receives the PID parameters from the neural network NNPID in different mode of operation and gives the optimal control signal in time.The Levenberg-Marquardt algorithm is used to train the FTNNM and the NNPID.The convergence speed of the offline training is fast and the accuracy of the model is high. Due to the simple and fast continuous variable parameter control algorithm,It satisfy the high real-time need of the hyroturbine governing system.

关键词： Neural network PID control system Nonlinear Francis hydroturbine generator set FTGS Francis turbine neural network model FTNNM

作者: Jiang Chang Yan Peng

作者单位: Department of Mechanical and Electrical Engineering Shenzhen Polytechnic Shenzhen, China Industry Center Shenzhen Polytechnic Shenzhen, China

会议类型: 国际会议

会议名称: 2009 Second International Conference on Intelligent Computation Technology and Automation(2009 第二届IEEE智能计算与自动化国际会议 ICICTA 2009)

会议地点: 长沙

会议语种:英文

页码: 87-90

在线出版日期: 2009-10-10（万方平台首次上网日期，不代表论文的发表时间）