A recentred barrier for constrained receding horizon control

A.G. Wills; W.P. Heath

doi:10.1109/ACC.2002.1024586

A recentred barrier for constrained receding horizon control

A.G. Wills
, W.P. Heath

The University of Newcastle

Research output: Contribution to conference › Paper › peer-review

Abstract

Constrained receding horizon controllers are often designed to govern the system state to some desired set-point subject to input constraints. This paper presents a class of receding horizon controllers which satisfy such constraints via the inclusion of a 'recentred barrier function'. The significance of such a controller is that hard constraints are replaced with penalty type soft constraints. The resulting control law is cautious near constraint boundaries with the degree of caution being determined by a positive weighting parameter. This approach is applicable to general convex objective functions with convex inequality constraints. We illustrate this idea by way of an example application to linear discrete-time plant models with linear and convex quadratic static input constraints

Original language	Unknown
Pages	4177-4182
Number of pages	6
DOIs	https://doi.org/10.1109/ACC.2002.1024586
Publication status	Published - 7 Nov 2002
Externally published	Yes
Event	Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301) - Anchorage, United States Duration: 8 May 2002 → 10 May 2002

Conference

Conference	Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301)
Country/Territory	United States
City	Anchorage
Period	8/05/02 → 10/05/02

Access to Document

10.1109/ACC.2002.1024586

Cite this

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title = "A recentred barrier for constrained receding horizon control",

abstract = "Constrained receding horizon controllers are often designed to govern the system state to some desired set-point subject to input constraints. This paper presents a class of receding horizon controllers which satisfy such constraints via the inclusion of a 'recentred barrier function'. The significance of such a controller is that hard constraints are replaced with penalty type soft constraints. The resulting control law is cautious near constraint boundaries with the degree of caution being determined by a positive weighting parameter. This approach is applicable to general convex objective functions with convex inequality constraints. We illustrate this idea by way of an example application to linear discrete-time plant models with linear and convex quadratic static input constraints",

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doi = "10.1109/ACC.2002.1024586",

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AB - Constrained receding horizon controllers are often designed to govern the system state to some desired set-point subject to input constraints. This paper presents a class of receding horizon controllers which satisfy such constraints via the inclusion of a 'recentred barrier function'. The significance of such a controller is that hard constraints are replaced with penalty type soft constraints. The resulting control law is cautious near constraint boundaries with the degree of caution being determined by a positive weighting parameter. This approach is applicable to general convex objective functions with convex inequality constraints. We illustrate this idea by way of an example application to linear discrete-time plant models with linear and convex quadratic static input constraints

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