Incomplete Differential PID Neural Network Temprature Controller for Thermal Process

摘要：

The system parameters of thermal process such like heating network have a feature of nonlinearity, time-variant and high time-delay. Using the intelligent control methods of combining neural network theory and incomplete differential PID controlling, adjusting the self-learning of neural network and weighting coefficients, the output of neural network is corresponding to the parameters of incomplete differential PID controller which is under the best control rate, also the system will have better controllability, robustness and adaptability. Matlab simulation shows that the presented control scheme makes the control process about second return water temperature of thermal station into the steadystate quickly, comparing with the conventional incremental PID control performance. Through online learning and auto-update parameters, the response of control system is speeding up, and it can restrain disturbance effectively.

关键词： Neural network Incomplete Differential PID Heating network control

作者: Weibing Wang Xudong Wang Wei Wang Dongju Liu

作者单位: College of Computer Science and Technology Harbin University of Science And Technology Harbin,China College of Electrical and Electronic Engineering Harbin University of Science And Technology Harbin,

会议类型: 国际会议

会议名称: The 6th International Forum on Strategic Technology(IFOST 2011)(第六届国际战略技术论坛)

会议地点: 哈尔滨

会议语种:英文

页码: 920-923

在线出版日期: 2011-08-22（万方平台首次上网日期，不代表论文的发表时间）