Parameter identification for nonlinear models from a state-space approach⁎Research funded by PSA Groupe and the French National Association of Research and Technology (ANRT). Issue 2 (2020)

• Record Type: Journal Article
• Authors: Matz, Jules; Birouche, Abderazik; Mourllion, Benjamin; Bouziani, Fethi; Basset, Michel
• Is Part Of: IFAC-PapersOnLine. Volume 53:Issue 2(2020)
• Page Start: 13910
• Page End: 13915
• Publication Date: 2020
• Subjects: parameter identification -- state-space models -- nonlinear system -- vehicle dynamics; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2020.12.905
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: A new approach to parameter estimation of dynamical models is proposed. Its objective is to approximate at best the different dynamics of the system, instead of approximating at best the system output in time. This leads to a weighting of the error depending on the samples location in the state-space and input space. A possible implementation is proposed and applied for estimating the parameters of a two degrees of freedom vehicle dynamics model. The proposed approach is shown to better approximate the fast transient dynamics, at the cost of a degraded performance on steady-states.