Complexity Reduction for Parameter-Dependent Linear Systems
2013 (English)In: 2013 American Control Conference (ACC), American Automatic Control Council , 2013, 2624-2630 p.Conference paper (Refereed)
We present a complexity reduction algorithm for a family of parameter-dependent linear systems when the system parameters belong to a compact semi-algebraic set. This algorithm potentially describes the underlying dynamical system with fewer parameters or state variables. To do so, it minimizes the distance (i.e., $H_\infty$-norm of the difference) between the original system and its reduced version. We present a sub-optimal solution to this problem using sum-of-squares optimization methods. We present the results for both continuous-time and discrete-time systems. Lastly, we illustrate the applicability of our proposed algorithm on numerical examples.
Place, publisher, year, edition, pages
American Automatic Control Council , 2013. 2624-2630 p.
, American Control Conference. Proceedings, ISSN 0743-1619
Large scale systems, Reduced order modeling, Linear systems
IdentifiersURN: urn:nbn:se:kth:diva-124939ISI: 000327210202129ScopusID: 2-s2.0-84883521472ISBN: 978-147990177-7OAI: oai:DiVA.org:kth-124939DiVA: diva2:638752
2013 1st American Control Conference, ACC 2013; Washington, DC; United States; 17 June 2013 through 19 June 2013
QC 201311052013-08-022013-08-022014-01-07Bibliographically approved