抚顺石油学院学报2001，Vol.21Issue(2)：66-71,6.
基于BP网络的典型工业过程
自适应预测区域控制
Adaptive Predictive Zone Control Based on BP Neural Networks for
Typical Industrial Process
1
作者信息
- 1. 抚顺石油学院信息工程分院,;抚顺石油学院信息工程分院,;辽阳石化分公司生产监测中心,;The Production Supervise and Measurement Center of Liaoyang Branch of CNPC,
- 折叠
摘要
Abstract
After discussing the intrinsic relationship between the open-loop parameters in a class of typical industrial processes with fractional delay and time-variable properties and the parameters in the generalized predictive controller, a generalized adaptive predictive direct algorithm based on neural networks' mapping ability is presented by adding the open-loop system gain to the cost function. In this algorithm, an identifier is employed to estimate the parameters of the open-loop system. The parameters of the controller is directly calculated by using the identification results and the value of the control weight factor from a trained BP neural network. And then the control law is obtained. The method developed in this paper does not only depend on the exact model of the controlled plant, but also can substantially reduce the computation load on-line. Meanwhile, two kinds of zone predictive control schemes are presented as well by introducing the zone control to the predictive control. The simulation comparison with conventional GPC on a binary distillation column model demonstrates the feasibility of this algorithm.关键词
广义预测控制/自适应控制/BP网络/区域控制分类
信息技术与安全科学引用本文复制引用
..基于BP网络的典型工业过程
自适应预测区域控制[J].抚顺石油学院学报,2001,21(2):66-71,6.
