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
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