Exponential ARX model-based long-range predictive control strategy for power plants

被引:25
作者
Peng, H
Ozaki, T
Toyoda, Y
Oda, K
机构
[1] Inst Stat Math, Minato Ku, Tokyo 1068569, Japan
[2] Cent S Univ, Coll Informat Engn, Changsha 410083, Peoples R China
[3] Bailey Japan Co Ltd, Shizuoka 41021, Japan
关键词
nonlinear systems; multivariable systems; ARX models; identification; predictive control; constraints; multivariable control;
D O I
10.1016/S0967-0661(01)00079-X
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
For nonlinear thermal power plants whose dynamics vary with load demand, a load-dependent exponential ARX (Exp-ARX) model, which can effectively describe the nonlinear properties of the plants, is presented, The Exp-ARX model requires only off-line identification. Based on the model, a constrained multivariable generalized predictive control (CMGPC) strategy is designed and implemented in a simulation of 375 MW thermal power plants. This CMGPC algorithm does not resort to on-line parameter estimation and can more exactly predict the future outputs of the nonlinear plants, so it shows better reliability and control performance than the usual GPC algorithm. (C) 2001 Elsevier Science Ltd. All rights reserved.
引用
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页码:1353 / 1360
页数:8
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