HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Theses

Hybrid dynamical system identification : geometry, sparsity and nonlinearities

Abstract : In automatic control, obtaining a model is always the cornerstone of the synthesis procedures such as controller design, fault detection or prediction... This thesis deals with the identification of a class of complex systems, hybrid dynamical systems. These systems involve the interaction of continuous and discrete behaviors. The goal is to build a model from experimental measurements of the system inputs and outputs. A new approach for the identification of linear hybrid systems based on the geometric properties of hybrid systems in the parameter space is proposed. A new algorithm is then proposed to recover the sparsest solutions of underdetermined systems of linear equations. This allows us to improve an identification approach based on the error sparsification. In addition, new approaches based on kernel models are proposed for the identification of nonlinear hybrid systems and piecewise smooth systems
Document type :
Theses
Complete list of metadata

Cited literature [105 references]  Display  Hide  Download

https://hal.univ-lorraine.fr/tel-01750090
Contributor : Thèses Ul Connect in order to contact the contributor
Submitted on : Thursday, March 29, 2018 - 12:37:35 PM
Last modification on : Saturday, October 16, 2021 - 11:14:14 AM
Long-term archiving on: : Friday, September 14, 2018 - 11:00:50 AM

File

DDOC_T_2013_0102_LE.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : tel-01750090, version 1

Collections

Citation

van Luong Le. Hybrid dynamical system identification : geometry, sparsity and nonlinearities. Other. Université de Lorraine, 2013. English. ⟨NNT : 2013LORR0102⟩. ⟨tel-01750090⟩

Share

Metrics

Record views

45

Files downloads

59