Constrained receding horizon predictive control for nonlinear systems

This paper represents a receding horizon predictive control algorithm for constrained nonlinear systems which, unlike earlier works, can be solved by linear programming methods is developed. Use is made of a terminal inequality constraint in conjunction with a cost penalizing an upper bound on the t...

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Main Authors: Lee, Y, Kouvaritakis, B, Cannon, M
Format: Journal article
Language:English
Published: IEEE 1999
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author Lee, Y
Kouvaritakis, B
Cannon, M
author_facet Lee, Y
Kouvaritakis, B
Cannon, M
author_sort Lee, Y
collection OXFORD
description This paper represents a receding horizon predictive control algorithm for constrained nonlinear systems which, unlike earlier works, can be solved by linear programming methods is developed. Use is made of a terminal inequality constraint in conjunction with a cost penalizing an upper bound on the tracking error over a finite control horizon. The optimization procedure is based on predictions made by linearized incremental models at points of a given seed trajectory and the effects of linearization error are taken into account to give a bound on the predicted tracking error. The proposed algorithm is posed in the form of LP and its asymptotic stability can be guaranteed by proper selection of the terminal weights of the cost index.
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spelling oxford-uuid:5b0ed58c-cf8a-4841-8506-893faf2c06572022-03-26T17:19:45ZConstrained receding horizon predictive control for nonlinear systemsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:5b0ed58c-cf8a-4841-8506-893faf2c0657EnglishSymplectic Elements at OxfordIEEE1999Lee, YKouvaritakis, BCannon, MThis paper represents a receding horizon predictive control algorithm for constrained nonlinear systems which, unlike earlier works, can be solved by linear programming methods is developed. Use is made of a terminal inequality constraint in conjunction with a cost penalizing an upper bound on the tracking error over a finite control horizon. The optimization procedure is based on predictions made by linearized incremental models at points of a given seed trajectory and the effects of linearization error are taken into account to give a bound on the predicted tracking error. The proposed algorithm is posed in the form of LP and its asymptotic stability can be guaranteed by proper selection of the terminal weights of the cost index.
spellingShingle Lee, Y
Kouvaritakis, B
Cannon, M
Constrained receding horizon predictive control for nonlinear systems
title Constrained receding horizon predictive control for nonlinear systems
title_full Constrained receding horizon predictive control for nonlinear systems
title_fullStr Constrained receding horizon predictive control for nonlinear systems
title_full_unstemmed Constrained receding horizon predictive control for nonlinear systems
title_short Constrained receding horizon predictive control for nonlinear systems
title_sort constrained receding horizon predictive control for nonlinear systems
work_keys_str_mv AT leey constrainedrecedinghorizonpredictivecontrolfornonlinearsystems
AT kouvaritakisb constrainedrecedinghorizonpredictivecontrolfornonlinearsystems
AT cannonm constrainedrecedinghorizonpredictivecontrolfornonlinearsystems