SparseJSR: A fast algorithm to compute joint spectral radius via sparse SOS decompositions
(2021) 2021 American Control Conference, ACC 2021 In Proceedings of the American Control Conference 2021-May. p.2254-2259- Abstract
- This paper focuses on the computation of the joint spectral radius (JSR), when the involved matrices are sparse. We provide a sparse variant of the procedure proposed by Parrilo and Jadbabaie to compute upper bounds of the JSR by means of sum-of-squares (SOS) programming. Our resulting iterative algorithm, called SparseJSR, is based on the term sparsity SOS (TSSOS) framework developed by Wang, Magron and Lasserre, which yields SOS decompositions of polynomials with arbitrary sparse supports. SparseJSR exploits the sparsity of the input matrices to significantly reduce the computational burden associated with the JSR computation. Our algorithmic framework is then successfully applied to compute upper bounds for JSR on randomly generated... (More)
- This paper focuses on the computation of the joint spectral radius (JSR), when the involved matrices are sparse. We provide a sparse variant of the procedure proposed by Parrilo and Jadbabaie to compute upper bounds of the JSR by means of sum-of-squares (SOS) programming. Our resulting iterative algorithm, called SparseJSR, is based on the term sparsity SOS (TSSOS) framework developed by Wang, Magron and Lasserre, which yields SOS decompositions of polynomials with arbitrary sparse supports. SparseJSR exploits the sparsity of the input matrices to significantly reduce the computational burden associated with the JSR computation. Our algorithmic framework is then successfully applied to compute upper bounds for JSR on randomly generated benchmarks as well as on problems arising from stability proofs of controllers, in relation with possible hardware and software faults. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2ab02df8-4c7d-4446-a405-a7f73fde6937
- author
- Wang, Jie ; Maggio, Martina LU and Magron, Victor LU
- organization
- publishing date
- 2021
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2021 American Control Conference, ACC 2021
- series title
- Proceedings of the American Control Conference
- volume
- 2021-May
- article number
- 9483347
- pages
- 6 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 2021 American Control Conference, ACC 2021
- conference location
- Virtual, New Orleans, United States
- conference dates
- 2021-05-25 - 2021-05-28
- external identifiers
-
- scopus:85101645952
- scopus:85101645952
- ISSN
- 0743-1619
- ISBN
- 9781665441971
- DOI
- 10.23919/ACC50511.2021.9483347
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2021 American Automatic Control Council.
- id
- 2ab02df8-4c7d-4446-a405-a7f73fde6937
- date added to LUP
- 2022-03-22 23:25:17
- date last changed
- 2023-11-16 15:46:10
@inproceedings{2ab02df8-4c7d-4446-a405-a7f73fde6937, abstract = {{This paper focuses on the computation of the joint spectral radius (JSR), when the involved matrices are sparse. We provide a sparse variant of the procedure proposed by Parrilo and Jadbabaie to compute upper bounds of the JSR by means of sum-of-squares (SOS) programming. Our resulting iterative algorithm, called SparseJSR, is based on the term sparsity SOS (TSSOS) framework developed by Wang, Magron and Lasserre, which yields SOS decompositions of polynomials with arbitrary sparse supports. SparseJSR exploits the sparsity of the input matrices to significantly reduce the computational burden associated with the JSR computation. Our algorithmic framework is then successfully applied to compute upper bounds for JSR on randomly generated benchmarks as well as on problems arising from stability proofs of controllers, in relation with possible hardware and software faults.}}, author = {{Wang, Jie and Maggio, Martina and Magron, Victor}}, booktitle = {{2021 American Control Conference, ACC 2021}}, isbn = {{9781665441971}}, issn = {{0743-1619}}, language = {{eng}}, pages = {{2254--2259}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{Proceedings of the American Control Conference}}, title = {{SparseJSR: A fast algorithm to compute joint spectral radius via sparse SOS decompositions}}, url = {{http://dx.doi.org/10.23919/ACC50511.2021.9483347}}, doi = {{10.23919/ACC50511.2021.9483347}}, volume = {{2021-May}}, year = {{2021}}, }