A Simultaneous Balanced Truncation Approach to Model Reduction of Switched Linear Systems

Nima Monshizadeh*, Hendrikus Trentelman, M. Kanat Camlibel

*Corresponding author for this work

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33 Citations (Scopus)
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This paper deals with model reduction by balanced truncation of switched linear systems (SLS). We consider switched linear systems whose dynamics, depending on the switching signal, switches between finitely many linear systems with a common state space. These linear systems are called the modes of the SLS. The idea is to seek for conditions under which there exists a single state space transformation that brings all modes of the SLS in balanced coordinates. As a measure of reachability and observability of the state components of the SLS, we take the average of the diagonal gramians. We then perform balanced truncation by discarding the state components corresponding to the smallest diagonal elements of this average balanced gramian. In order to carry out this program, we derive necessary and sufficient conditions under which a finite collection of linear systems with common state space can be balanced by a single state space transformation. Among other things, we derive sufficient conditions under which global uniform exponential stability of the SLS is preserved under simultaneous balanced truncation. Likewise, we derive conditions for preservation of positive realness or bounded realness of the SLS. Finally, in case that the conditions for simultaneous balancing do not hold, or we simply do not want to check these conditions, we propose to compute a suitable state space transformation on the basis of minimization of an overall cost function associated with the modes of the SLS. We show that in case our conditions do hold, this transformation is in fact simultaneously balancing, bringing us back to the original method described in this paper.

Original languageEnglish
Pages (from-to)3118-3131
Number of pages14
JournalIEEE Transactions on Automatic Control
Issue number12
Publication statusPublished - Dec-2012


  • Model reduction
  • simultaneous balanced truncation
  • switched linear systems

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