Model predictive control for tracking randomly varying references
File(s)tracknljour_rev.pdf (341.17 KB)
Accepted version
Author(s)
Falugi, P
Type
Journal Article
Abstract
This paper proposes a model predictive control scheme for tracking a-priori unknown references varying in a wide range and analyses its performance. It is usual to assume that the reference eventually converges to a constant in which case convergence to zero of the tracking error can be established. In this note we remove this simplifying assumption and characterise the set to which the tracking error converges and the associated region of convergence.
Date Issued
2014-11-06
Date Acceptance
2014-09-30
Citation
International Journal of Control, 2014, 88 (4), pp.745-753
ISSN
1366-5820
Publisher
Taylor & Francis
Start Page
745
End Page
753
Journal / Book Title
International Journal of Control
Volume
88
Issue
4
Copyright Statement
This is an Accepted Manuscript of an article published by Taylor & Francis Group in International Journal of Control on 6 Nov 2014, available online at: https://dx.doi.org/10.1080/00207179.2014.972464
Subjects
tracking control
nonlinear model predictive control
constrained nonlinear systems
Publication Status
Published