Nuclear Reactor Temperature System based on DMC

摘要：

The traditional PID control method can rarely meet the stability and robustness of the high-order system in industrial process control. In this paper, we propose a multi-model predictive control strategy by combining the traditional Dynamic Matrix Control (DMC) with Bayesian probability weighting. The new Multi-model Predictive Control is used in the heat transfer model in reactor of nuclear power plants. We adopt a nine-step response model at various operating points and recursive Bayesian probability weighting to get the global prediction model. The proposed multi-model predictive control method can achieve a better performance for this nonlinear system. Simulation shows a satisfactory result with a wide range operation of a reactor temperature control system.

关键词： multi-model predictive control Dynamic Matrix Control Bayesian probability weighting reactor temperature system

作者: Li Suzhen Liu Shuai XJ.Liu

作者单位: Department of Control and computer engineer North China Electric Power University Beijing, P.R.China Department of Control and computer engineer North China Electric Power University Beijing, P.R. Chin

会议类型: 国际会议

会议名称: 2011 International Conference on Information and Industrial Electronics(2011年信息与工业电子国际会议 ICIIE 2011)

会议地点: 成都

会议语种:英文

页码: 808-811

在线出版日期: 2011-01-14（万方平台首次上网日期，不代表论文的发表时间）