Multipliers for model predictive control with structured input constraints

W. P. Heath; Guang Li

doi:10.1016/j.automatica.2010.01.020

Multipliers for model predictive control with structured input constraints

W. P. Heath, Guang Li

EEE - Academic & Research

Research output: Contribution to journal › Article › peer-review

Abstract

The stability and robustness of input-constrained model predictive control can be analyzed using the theory of integral quadratic constraints. We demonstrate the existence of improved multipliers when there are only staged input or box input constraints. This can significantly reduce the conservatism of any stability analysis, and we illustrate the improved performance with a simple numerical example. © 2010 Elsevier Ltd. All rights reserved.

Original language	English
Pages (from-to)	562-568
Number of pages	6
Journal	Automatica
Volume	46
Issue number	3
Early online date	1 Feb 2010
DOIs	https://doi.org/10.1016/j.automatica.2010.01.020
Publication status	Published - 1 Mar 2010

Keywords

Absolute stability
Constraints
Model predictive control
Multipliers
Robustness

Access to Document

10.1016/j.automatica.2010.01.020

Cite this

@article{ed750fa457474489be97ca043b3d39da,

title = "Multipliers for model predictive control with structured input constraints",

abstract = "The stability and robustness of input-constrained model predictive control can be analyzed using the theory of integral quadratic constraints. We demonstrate the existence of improved multipliers when there are only staged input or box input constraints. This can significantly reduce the conservatism of any stability analysis, and we illustrate the improved performance with a simple numerical example. {\textcopyright} 2010 Elsevier Ltd. All rights reserved.",

keywords = "Absolute stability, Constraints, Model predictive control, Multipliers, Robustness",

author = "Heath, {W. P.} and Guang Li",

year = "2010",

month = mar,

day = "1",

doi = "10.1016/j.automatica.2010.01.020",

language = "English",

volume = "46",

pages = "562--568",

journal = "Automatica",

issn = "0005-1098",

publisher = "Elsevier BV",

number = "3",

}

TY - JOUR

T1 - Multipliers for model predictive control with structured input constraints

AU - Heath, W. P.

AU - Li, Guang

PY - 2010/3/1

Y1 - 2010/3/1

N2 - The stability and robustness of input-constrained model predictive control can be analyzed using the theory of integral quadratic constraints. We demonstrate the existence of improved multipliers when there are only staged input or box input constraints. This can significantly reduce the conservatism of any stability analysis, and we illustrate the improved performance with a simple numerical example. © 2010 Elsevier Ltd. All rights reserved.

AB - The stability and robustness of input-constrained model predictive control can be analyzed using the theory of integral quadratic constraints. We demonstrate the existence of improved multipliers when there are only staged input or box input constraints. This can significantly reduce the conservatism of any stability analysis, and we illustrate the improved performance with a simple numerical example. © 2010 Elsevier Ltd. All rights reserved.

KW - Absolute stability

KW - Constraints

KW - Model predictive control

KW - Multipliers

KW - Robustness

U2 - 10.1016/j.automatica.2010.01.020

DO - 10.1016/j.automatica.2010.01.020

M3 - Article

SN - 0005-1098

VL - 46

SP - 562

EP - 568

JO - Automatica

JF - Automatica

IS - 3

ER -

Multipliers for model predictive control with structured input constraints

Abstract

Keywords

Access to Document

Fingerprint

Cite this