A Nonlinear Predictive Model Based on BP Neural Network

摘要：

MPCs have been widely applied in industrial process control field because of the excellent control effect. The classic MPCs, which are all based on linear predictive models, are unfit for the strong-nonlinearity control systems. In these cases, NMPCs must be constructed if a model predictive controller wants to be used. Nonlinear predictive model is the foundation of NMPC, and should be established firstly. This paper proposed a one-step nonlinear predictive model based on BP neural network by combining NARMAX model and neural network, and supplied a calculation method of the hidden-layer-neuron number of the two-layer BP neural network used in the one-step predictive model.

关键词： MPC NARMAX BP Neural Network Predictive Model

作者: Huijun Li

作者单位: School of Information and Electric Engineering, China University of Mining and Technology, Xuzhou, 221008, China

会议类型: 国际会议

会议名称: The 22nd China Control and Decision Conference(2010年中国控制与决策会议)

会议地点: 徐州

会议语种:英文

页码: 73-77

在线出版日期: 2010-05-26（万方平台首次上网日期，不代表论文的发表时间）