Multivariable RBF-ARX model-based robust MPC approach and application to thermal power plant

被引：35

作者：

Peng, Hui ^{[1
]}

Kitagawa, Genshiro ^{[2
]}

Wu, Jun ^{[1
]}

Ohtsu, Kohei ^{[3
]}

机构：

[1] Cent S Univ, Sch Informat Sci & Engn, Changsha 410083, Hunan, Peoples R China

[2] Inst Stat Math, Tokyo 1908562, Japan

[3] Tokyo Univ Marine Sci & Technol, Koto Ku, Tokyo 1358533, Japan

来源：

APPLIED MATHEMATICAL MODELLING | 2011年 / 35卷 / 07期

基金：

中国国家自然科学基金;

关键词：

Nonlinear system; Modeling; Predictive control; Robustness; Stability; Thermal power plant; PREDICTIVE CONTROL STRATEGY; STABILITY; SYSTEMS;

D O I：

10.1016/j.apm.2011.01.002

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

For a class of smooth nonlinear multivariable systems whose working-points vary with time and the future working-points knowledge are unknown, a combination of a local linearization and a polytopic uncertain linear parameter-varying (LPV) state-space model is built to approximate the present and the future system's nonlinear behavior, respectively. The combination models are constructed on the basis of a matrix polynomial multi-input multi-output (MIMO) RBF-ARX model identified offline for representing the underlying nonlinear system. A min-max robust MPC strategy is designed to achieve the systems' output-tracking control based on the approximate models proposed. The closed loop stability of the MPC algorithm is guaranteed by the use of time-varying parameter-dependent Lyapunov function and the feasibility of the linear matrix inequalities (LMIs). The effectiveness of the modeling and control methods proposed in this paper is illustrated by a case study of a thermal power plant simulator. (C) 2011 Elsevier Inc. All rights reserved.

引用

页码：3541 / 3551

页数：11

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