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A model predictive control approach to trajectory tracking problems via time-varying level sets of Lyapunov functions
Publikationstyp
Conference Paper
Date Issued
2011
Sprache
English
Author(s)
Start Page
3381
End Page
3386
Article Number
6160492
Citation
50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC 2011)
Contribution to Conference
Publisher DOI
Scopus ID
Publisher
IEEE
ISSN
07431546
ISBN
978-1-61284-799-3
978-1-61284-800-6
978-1-61284-801-3
We discuss a model predictive control approach to trajectory tracking problems of constrained nonlinear continuous time systems, where the reference trajectory is a priori known and asymptotically constant. The proposed NMPC scheme is able to explicitly consider input and state constraints while guaranteeing recursive feasibility. To handle the time-varying nature of the tracking problem we advocate the use of time-varying level sets of Lyapunov functions as terminal regions. We prove a necessary and sufficient condition for positive invariance of these sets and show how these sets can be efficiently computed, if a quadratic Lyapunov function is available. As an example we consider a nonlinear CSTR reactor.
Subjects
invariant sets
nonlinear model predictive control
time-varying level sets
trajectory tracking
DDC Class
004: Computer Sciences
621: Applied Physics