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Predictive approach to torque vectoring based on the Koopman operator (CROSBI ID 713040)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Švec, Marko ; Ileš, Šandor ; Matuško, Jadranko Predictive approach to torque vectoring based on the Koopman operator // 2021 European Control Conference (ECC). Delft: Institute of Electrical and Electronics Engineers (IEEE), 2022. str. 1341-1346 doi: 10.23919/ecc54610.2021.9654836

Podaci o odgovornosti

Švec, Marko ; Ileš, Šandor ; Matuško, Jadranko

engleski

Predictive approach to torque vectoring based on the Koopman operator

Torque Vectoring (TV) system uses an individually controlled electric powertrain to improve the dynamic behavior and enhance the handling and stability of a vehicle. In this paper, a Model Predictive Control (MPC) algorithm with a model of the vehicle identified using the Koopman operator theory is proposed. The Koopman operator is a linear predictor for nonlinear dynamical systems based on the lifting of the nonlinear dynamics in a higher-dimensional space where its evolution is linear. Using such a model may allow for achieving similar performance to those of a nonlinear MPC with the computational efficiency of a linear MPC. The Koopman MPC was compared to a Linear Time-Variant (LTV) MPC, a common approach in the existing literature, and showed increased performance.

Koopman operator, basis function, data-driven methods, extended dynamic mode decomposition, model predictive control, vehicle dynamics

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Podaci o prilogu

1341-1346.

2022.

objavljeno

10.23919/ecc54610.2021.9654836

Podaci o matičnoj publikaciji

2021 European Control Conference (ECC)

Delft: Institute of Electrical and Electronics Engineers (IEEE)

978-9-4638-4236-5

Podaci o skupu

Nepoznat skup

predavanje

29.02.1904-29.02.2096

Povezanost rada

Informacijske i komunikacijske znanosti, Interdisciplinarne tehničke znanosti

Poveznice