How Statistical Learning Can Help to Estimate the Number of Modes in Switched System Identification?. Issue 7 (2021)

• Record Type: Journal Article
• Authors: Massucci, Louis; Lauer, Fabien; Gilson, Marion
• Is Part Of: IFAC-PapersOnLine. Volume 54:Issue 7(2021)
• Page Start: 637
• Page End: 642
• Publication Date: 2021
• Subjects: Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2021.08.432
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: This paper deals with hybrid dynamical system identification, and focuses more particularly on the estimation of the number of modes. An evaluation of a recent method based on model selection techniques from statistical learning is proposed, together with its comparison with more standard approaches based on algebraic arguments. Overall, three methods are benchmarked in various settings, including different noise conditions and data set sizes. The results provide insights into the respective advantages and weaknesses of the methods, thus yielding a set of guidelines on the choice of the most suitable method in a given situation for the practitioner.