Identification of Linear Switching System with Unknown Dimensions

Amir H. Shirdel, Kaj-Mikael Björk, Hannu T. Toivonen

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2 Citations (Scopus)


Switching systems have the property that their dynamical behavior may switch between a number of different modes. Identification of switching systems consists of identifying both the individual models which describe the system in the various modes, as well as the time instants when the mode changes have occurred. This soft computing problem therefore consists of numerically demanding coupled parameter identification and clustering problem. In this contribution a method based on sparse optimization techniques is proposed for identification of switching systems. In the two proposed methods, the modes and the associated models are determined one by one by solving linear problems which are sparse with respect to the number of violated epsilon-insensitive constraints and also solving by extending the models with an alternative LP-formulation of the optimization problem. The performance of the identification procedure is demonstrated by simulated examples.
Original languageEnglish
Title of host publication 2014 47th Hawaii International Conference on System Sciences, Waikoloa, HI, USA
Publication date10.03.2014
ISBN (Electronic)978-1-4799-2504-9
Publication statusPublished - 10.03.2014
MoE publication typeA4 Article in conference proceedings
Event Hawaii International Conference on System Sciences (HICSS) - Big Island Hawaii, United States
Duration: 06.01.201409.01.2014
Conference number: 47


  • 512 Business and Management
  • Switching systems
  • Optimization
  • Vectors
  • Switches
  • Predictive models
  • Support vector machines
  • Computational modeling


Dive into the research topics of 'Identification of Linear Switching System with Unknown Dimensions'. Together they form a unique fingerprint.

Cite this