A Method of Implicit Generalized Predictive Control Based on Genetic Algorithm and Improved BP Neural Network

被引：0
|
作者：
Gao Lin [1 ]
Sun Hairong [1 ]
Yang Huaishen [1 ]
He Tongyu [1 ]
机构：
[1] N China Elect Power Univ, Sch Control Sci & Engn, Baoding, Peoples R China
来源：
SYSTEMS, ORGANIZATIONS AND MANAGEMENT: PROCEEDINGS OF THE 3RD WORKSHOP OF INTERNATIONAL SOCIETY IN SCIENTIFIC INVENTIONS | 2009年
关键词：
improved BP neural network; implicit self-correcting generalized predictive control; genetic algorithm; optimization of parameters;
D O I：
暂无
中图分类号：
C93 [管理学]; O22 [运筹学];
学科分类号：
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要：
A method of predictive control combining genetic algorithm (GA) and improved BP neural network (NN) is put forward in this paper. Firstly, we identify system model with improved BP NN. GA is used to optimize the parameters of NN weighting initial value and offset initial value, speed of learning and momentum coefficient in identification process of improved BP NN, solving the problem that it's difficult to determine the value of them. Subsequently, NN model optimized by GA is used in implicit self-correcting generalized predictive control (GPC) process. We use GA to optimize predictive control process and to find the optimal control parameters (prediction length, control length, control weight number and soft coefficient). The application in thermal process shows the method is effective.
引用
收藏
页码：97 / 105
页数：9
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