A nonlinear exponential ARX model-based multivariable generalized predictive control strategy for thermal power plants

被引:32
|
作者
Peng, H [1 ]
Ozaki, T
Haggan-Ozaki, V
Toyoda, Y
机构
[1] Cent S Univ, Coll Informat Engn, Changsha 410083, Peoples R China
[2] Inst Stat Math, Minato Ku, Tokyo 1068569, Japan
[3] Sophia Univ, Tokyo 1020081, Japan
[4] Bailey Japan Co Ltd, Shizuoka 4102193, Japan
关键词
ARX models; constraints; nonlinear systems; power systems; predictive control; system identification;
D O I
10.1109/87.987071
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a modeling and control method for thermal power plants having nonlinear dynamics varying with load. First, a load-dependent exponential ARX (Exp-ARX) model that can effectively describe the plant nonlinear properties and requires only off-line identification is presented. The model is then used to establish a constrained multivariate multistep predictive control (ExpMPC) strategy whose effectiveness is illustrated by a simulation study of a 600 megawatt (MW) thermal power plant. Although the predictive control algorithm may be used without resorting to online parameter estimation, it is much more reliable, and displays much better control performance than the usual generalized predictive control (GPC) algorithm.
引用
收藏
页码:256 / 262
页数:7
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