Computation, approximation and stability of explicit feedback min-max nonlinear model predictive control

被引：28
|
作者：
Grancharova, Alexandra [1 ]
Johansen, Tor A. [2 ]
机构：
[1] Bulgarian Acad Sci, Inst Control & Syst Res, BU-1113 Sofia, Bulgaria
[2] Norwegian Univ Sci & Technol, Dept Engn Cybernet, N-7491 Trondheim, Norway
来源：
AUTOMATICA | 2009年 / 45卷 / 05期
关键词：
Min-max model predictive control; Multi-parametric programming; l(2)-stability; RECEDING HORIZON CONTROL; MPC; SYSTEMS; STATE; DESIGN; INPUT;
D O I：
10.1016/j.automatica.2008.12.023
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 an approximate multi-parametric Nonlinear Programming (mp-NLP) approach to explicit solution of feedback min-max NMPC problems for constrained nonlinear systems in the presence of bounded disturbances and/or parameter uncertainties. It is based on an orthogonal search tree structure of the state space partition and consists in constructing a piecewise nonlinear (PWNL) approximation to the optimal sequence of feedback control policies. Conditions guaranteeing the robust stability of the closed-loop system in terms of a finite l(2)-gain are derived. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码：1134 / 1143
页数：10
相关论文
共 50 条
  • [21] 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.
    CONTROL ENGINEERING PRACTICE, 2009, 17 (11) : 1358 - 1366
  • [22] Terminal Set of Min-max Model Predictive Control with Guaranteed L2 Performance
    Yu, Shuyou
    Maier, Christoph
    Chen, Hong
    Allgoewer, Frank
    2012 IEEE 51ST ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), 2012, : 3264 - 3269
  • [23] Computationally efficient nonlinear Min-Max Model Predictive Control based on Volterra series models-Application to a pilot plant
    Gruber, J. K.
    Ramirez, D. R.
    Limon, D.
    Alamo, T.
    JOURNAL OF PROCESS CONTROL, 2013, 23 (04) : 543 - 560
  • [24] Robust Precision Position Tracking of Planar Motors Using Min-Max Model Predictive Control
    Huang, Su-Dan
    Peng, Kai-Yu
    Cao, Guang-Zhong
    Wu, Chao
    Xu, Junqi
    He, Jiangbiao
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2022, 69 (12) : 13265 - 13276
  • [25] A Min-Max Model Predictive Control Approach to Robust Power Management in Ambulatory Wireless Sensor Networks
    Witheephanich, Kritchai
    Escano, Juan M.
    de la Pena, David Munoz
    Hayes, Martin J.
    IEEE SYSTEMS JOURNAL, 2014, 8 (04): : 1060 - 1073
  • [26] A Computational Approach to Explicit Feedback Stochastic Nonlinear Model Predictive Control
    Grancharova, Alexandra
    Johansen, Tor A.
    49TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC), 2010, : 6083 - 6088
  • [27] Comparison of Model Predictive Controller and Min-Max Approach for Aircraft Engine Fuel Control
    Montazeri-Gh, Morteza
    Rasti, Ali
    Imani, Amin
    2017 5TH INTERNATIONAL CONFERENCE ON CONTROL, INSTRUMENTATION, AND AUTOMATION (ICCIA), 2017, : 331 - 336
  • [28] Robust dynamic programming for min-max model predictive control of constrained uncertain systems
    Diehl, M
    Björnberg, J
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2004, 49 (12) : 2253 - 2257
  • [29] Combined model approximation techniques and multiparametric programming for explicit nonlinear model predictive control
    Rivotti, Pedro
    Lambert, Romain S. C.
    Pistikopoulos, Efstratios N.
    COMPUTERS & CHEMICAL ENGINEERING, 2012, 42 : 277 - 287
  • [30] Min-Max Predictive Control of a Five-Phase Induction Machine
    Ramirez, Daniel R.
    Martin, Cristina
    Kowal G, Agnieszka
    Arahal, Manuel R.
    ENERGIES, 2019, 12 (19)
12345