Stabilizing conditions for model predictive control
File(s)
Accepted version
Author(s)
Mayne, David Q
Falugi, Paola
Type
Journal Article
Abstract
Existing stabilizing conditions that use a terminal cost and constraint that, if satisfied, ensure stability and recursive feasibility for deterministic, robust, and stochastic model predictive control are briefly reviewed and analyzed. It is pointed out that these conditions do not cover all situations. Proposals are made to cover a wider range of desired applications.
Date Issued
2019-03-10
Date Acceptance
2018-10-25
Citation
International Journal of Robust and Nonlinear Control, 2019, 29 (4), pp.894-903
ISSN
1049-8923
Publisher
Wiley
Start Page
894
End Page
903
Journal / Book Title
International Journal of Robust and Nonlinear Control
Volume
29
Issue
4
Copyright Statement
© 2018 John Wiley & Sons Ltd. This is the pre-peer reviewed version of the following article: Mayne DQ, Falugi P. Stabilizing conditions for model predictive control. Int J Robust Nonlinear Control. 2018; 1–10., which has been published in final form at https://dx.doi.org/10.1002/rnc.4409
Subjects
Science & Technology
Technology
Physical Sciences
Automation & Control Systems
Engineering, Electrical & Electronic
Mathematics, Applied
Engineering
Mathematics
descent property
model predictive control
recursive feasibility
stabilizing conditions
STATE
0102 Applied Mathematics
0906 Electrical and Electronic Engineering
0913 Mechanical Engineering
Industrial Engineering & Automation
Publication Status
Published
Date Publish Online
2018-11-18