Subspace identification of local 1D homogeneous systems

Chengpu Yu, M Verhaegen, A Hansson

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

3 Citations (Scopus)
37 Downloads (Pure)


This paper studies the local subspace identification of 1D homogeneous networked systems. The main challenge lies at the unmeasurable interconnection signals between neighboring subsystems. Since there are many unknown inputs to the concerned local system, the corresponding identification problem is semi-blind. To cope with this problem, a nuclear norm optimization based subspace identification is presented, which is carried out for solving the Markov parameters of a locally lifted system, followed by determining the system matrices of a single subsystem. In the step of Markov parameter estimation, we form a nuclear norm regularized optimization problem which can well handle the adverse effects of the unknown system inputs as long as the number of unknown system inputs is relatively small. In the step of system realization, we again derive a nuclear norm regularized optimization formulation which can cope with the under-determinedness of the realization problem. In the end, the overall identification algorithm is summarized.
Original languageEnglish
Title of host publicationIFAC-PapersOnline - 17th IFAC Symposium on System Identification
EditorsY Zhao, E-W Bai, J-F Zhang
Place of PublicationLaxenburg, Austria
Publication statusPublished - 2015
EventSYSID 2015, Beijing, China - Laxenburg, Austria
Duration: 19 Oct 201521 Oct 2015

Publication series

ISSN (Print)2405-8963


ConferenceSYSID 2015, Beijing, China


  • Markov parameter
  • system realization
  • low rank constraint

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    Yu, C., Verhaegen, M., & Hansson, A. (2015). Subspace identification of local 1D homogeneous systems. In Y. Zhao, E-W. Bai, & J-F. Zhang (Eds.), IFAC-PapersOnline - 17th IFAC Symposium on System Identification (pp. 892-896). (IFAC-PapersOnline; Vol. 48). IFAC.