Long horizon input parameterisations to enlarge the region of attraction of MPC

B. Khan; G. Valencia-Palomo; J. A. Rossiter; C. N. Jones; R. Gondhalekar

doi:10.1002/oca.2158

Long horizon input parameterisations to enlarge the region of attraction of MPC

B. Khan^*, G. Valencia-Palomo, J. A. Rossiter, C. N. Jones, R. Gondhalekar

^*Corresponding author for this work

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

10 Scopus citations

Abstract

In this paper, the efficacy of structured and unstructured parameterisations of the degree of freedom within a predictive control algorithm is investigated. While several earlier papers investigated the enlargement of the region of attraction using structured prediction dynamics, little consideration has been given to the potential of unstructured parameterisations to handle the trade-off between the region of attraction, performance and computational burden. This paper demonstrates how unstructured dynamics can be both selected and used effectively and furthermore gives a comparison with structured methods.

Original language	English
Pages (from-to)	139-153
Number of pages	15
Journal	Optimal Control Applications and Methods
Volume	37
Issue number	1
DOIs	https://doi.org/10.1002/oca.2158
State	Published - 1 Jan 2016
Externally published	Yes

Bibliographical note

Publisher Copyright:
Copyright © 2014 John Wiley & Sons, Ltd.

Keywords

MPC
alternative parameterisation
computational burden
performance
region of attraction

ASJC Scopus subject areas

Software
Control and Systems Engineering
Control and Optimization
Applied Mathematics

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10.1002/oca.2158

Cite this

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abstract = "In this paper, the efficacy of structured and unstructured parameterisations of the degree of freedom within a predictive control algorithm is investigated. While several earlier papers investigated the enlargement of the region of attraction using structured prediction dynamics, little consideration has been given to the potential of unstructured parameterisations to handle the trade-off between the region of attraction, performance and computational burden. This paper demonstrates how unstructured dynamics can be both selected and used effectively and furthermore gives a comparison with structured methods.",

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AU - Khan, B.

AU - Valencia-Palomo, G.

AU - Rossiter, J. A.

AU - Jones, C. N.

AU - Gondhalekar, R.

PY - 2016/1/1

Y1 - 2016/1/1

N2 - In this paper, the efficacy of structured and unstructured parameterisations of the degree of freedom within a predictive control algorithm is investigated. While several earlier papers investigated the enlargement of the region of attraction using structured prediction dynamics, little consideration has been given to the potential of unstructured parameterisations to handle the trade-off between the region of attraction, performance and computational burden. This paper demonstrates how unstructured dynamics can be both selected and used effectively and furthermore gives a comparison with structured methods.

AB - In this paper, the efficacy of structured and unstructured parameterisations of the degree of freedom within a predictive control algorithm is investigated. While several earlier papers investigated the enlargement of the region of attraction using structured prediction dynamics, little consideration has been given to the potential of unstructured parameterisations to handle the trade-off between the region of attraction, performance and computational burden. This paper demonstrates how unstructured dynamics can be both selected and used effectively and furthermore gives a comparison with structured methods.

KW - MPC

KW - alternative parameterisation

KW - computational burden

KW - performance

KW - region of attraction

UR - https://www.scopus.com/pages/publications/84954109681

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JF - Optimal Control Applications and Methods

IS - 1

ER -

Long horizon input parameterisations to enlarge the region of attraction of MPC

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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Cite this