State-space approach to interpolation in MPC

Journal article

Abstract:: Interpolation between unconstrained optimal input trajectories and feasible trajectories forms the basis for a computationally efficient predictive control algorithm but lacks robustness in that uncertainty can destroy the guarantee of feasibility. To overcome this problem it is possible to introduce into the interpolation process a further input trajectory which is referred as `mean level'. This has been accomplished in an input-output setting and the purpose of the present paper is to show that it is possible to get a considerably simpler algorithm by recasting the problem into state-space form.

Publisher copy:: 10.1002/(SICI)1099-1239(200001)10:1<27::AID-RNC459>3.0.CO;2-5

Publisher:: John Wiley and Sons Ltd
Journal:: INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL More from this journal
Volume:: 10
Issue:: 1
Pages:: 27-38
Publication date:: 2000-01-01
DOI:: 10.1002/(SICI)1099-1239(200001)10:1<27::AID-RNC459>3.0.CO;2-5
EISSN:: 1099-1239
ISSN:: 1049-8923

Language:: English
Keywords:: feasibility

predictive control

optimality

stability

constraints
Pubs id:: pubs:62910
UUID:: uuid:03b56315-d062-4712-8812-1361021a7695
Local pid:: pubs:62910
Source identifiers:: 62910
Deposit date:: 2013-11-17
ARK identifier:: ark:/29072/ora_03b56315d062471288121361021a7695

Licence:: Terms and Conditions of Use for Oxford University Research Archive

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