Min-max generalized predictive control with stability

被引：7
|
作者：
Kim, YH
Kwon, WH
Lee, YI
机构：
[1] Daewoo elect Co Ltd, Adv Technol Lab 5, Seoul 100714, South Korea
[2] Seoul Natl Univ, Sch Elect Engn, Control Informat Syst Lab, Seoul 151742, South Korea
[3] Gyeongsang Natl Univ, RIACE, Dept Control & Instrumentat Engn, Kyungnam 660701, South Korea
来源：
COMPUTERS & CHEMICAL ENGINEERING | 1998年 / 22卷 / 12期
关键词：
stability conditions; linear matrix inequality; min-max generalized predictive control;
D O I：
10.1016/S0098-1354(98)00240-3
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
This paper presents a min-max generalized predictive control (MMGPC) which is robust to disturbances and has guaranteed stability. The MMGPC is derived from the min-max problem. It has non-recursive forms which do not use the Riccati equations. Stability conditions of the proposed control law are presented, which can be met by adjustment of some parameters such as input-output weightings. This paper presents a systematic way to obtain appropriate parameters for these stability conditions by using the linear matrix inequality (LMI) method. It is also shown that the suggested control guarantees that induced norm from disturbances to system outputs is bounded by a constant value under the same stability conditions. (C) 1998 Published by Elsevier Science Ltd. All rights reserved.
引用
收藏
页码：1851 / 1858
页数：8
相关论文
共 50 条
  • [21] Min-Max and Predictive Control for the Management of Distribution in Supply Chains
    Alessandri, Angelo
    Gaggero, Mauro
    Tonelli, Flavio
    [J]. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2011, 19 (05) : 1075 - 1089
  • [22] Robustly stable feedback min-max model predictive control
    Kerrigan, EC
    Maciejowski, JM
    [J]. PROCEEDINGS OF THE 2003 AMERICAN CONTROL CONFERENCE, VOLS 1-6, 2003, : 3490 - 3495
  • [23] Control of a pilot plant using QP based min-max predictive control
    Gruber, J. K.
    Ramirez, D. R.
    Alamo, T.
    Bordons, C.
    Camacho, E. F.
    [J]. CONTROL ENGINEERING PRACTICE, 2009, 17 (11) : 1358 - 1366
  • [24] Linearized min-max robust model predictive control: Application to the control of a bioprocess
    Benattia, S. E.
    Tebbani, S.
    Dumur, D.
    [J]. INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2020, 30 (01) : 100 - 120
  • [25] A min-max model predictive control for a class of hybrid dynamical systems
    Mukai, M
    Azuma, T
    Kojima, A
    Fujita, M
    [J]. 2003 IEEE INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE IN ROBOTICS AND AUTOMATION, VOLS I-III, PROCEEDINGS, 2003, : 694 - 699
  • [26] Min-max feedback model predictive control for constrained linear systems
    Scokaert, POM
    Mayne, DQ
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1998, 43 (08) : 1136 - 1142
  • [27] Min-max Predictive Control of a Pilot Plant using a QP Approach
    Gruber, J. K.
    Ramirez, D. R.
    Alamo, T.
    Bordons, C.
    Camacho, E. F.
    [J]. 47TH IEEE CONFERENCE ON DECISION AND CONTROL, 2008 (CDC 2008), 2008, : 3415 - 3420
  • [28] Min-max Model Predictive Control for Biaxial Feed Drive System
    Gao, Yu
    Zhang, Yuanliang
    Chong, Kil To
    [J]. 2017 29TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2017, : 769 - 773
  • [29] Towards the practical implementation of min-max nonlinear model predictive control
    Raimondo, D. M.
    Alamo, T.
    Limon, D.
    Camacho, E. F.
    [J]. PROCEEDINGS OF THE 46TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-14, 2007, : 5965 - +
  • [30] Constrained min-max predictive control:: a polynomial-time approach
    Alamo, T
    de la Peña, DM
    Limon, D
    Camacho, EF
    [J]. 42ND IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-6, PROCEEDINGS, 2003, : 912 - 916
12345