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Scientific paper - Original scientific paper
Optimizing vehicle handling through Koopman-based model predictive torque vectoring: An experimental investigation
Control Engineering Practice, 158 (2025); 106272. https://doi.org/10.1016/j.conengprac.2025.106272
Švec, Marko; Ileš, Šandor; Matuško, Jadranko

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Švec, M., Ileš, Š. & Matuško, J. (2025). Optimizing vehicle handling through Koopman-based model predictive torque vectoring: An experimental investigation. Control Engineering Practice, 158.. doi: 10.1016/j.conengprac.2025.106272

Švec, Marko, et al. "Optimizing vehicle handling through Koopman-based model predictive torque vectoring: An experimental investigation." Control Engineering Practice, vol. 158, 2025. https://doi.org/10.1016/j.conengprac.2025.106272

Švec, Marko, Šandor Ileš and Jadranko Matuško. "Optimizing vehicle handling through Koopman-based model predictive torque vectoring: An experimental investigation." Control Engineering Practice 158 (2025). https://doi.org/10.1016/j.conengprac.2025.106272

Švec, M., Ileš, Š. and Matuško, J. (2025) 'Optimizing vehicle handling through Koopman-based model predictive torque vectoring: An experimental investigation', Control Engineering Practice, 158. doi: 10.1016/j.conengprac.2025.106272

Švec M, Ileš Š, Matuško J. Optimizing vehicle handling through Koopman-based model predictive torque vectoring: An experimental investigation. Control Engineering Practice [Internet]. 2025 February 15 [cited 2025 April 01];158. doi: 10.1016/j.conengprac.2025.106272

M. Švec, Š. Ileš and J. Matuško, "Optimizing vehicle handling through Koopman-based model predictive torque vectoring: An experimental investigation", Control Engineering Practice, vol. 158, February 2025. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:168:116194. [Accessed: 01 April 2025]

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Metadata
Title (english)Optimizing vehicle handling through Koopman-based model predictive torque vectoring: An experimental investigation
AuthorMarko Švec
AuthorŠandor Ileš
AuthorJadranko Matuško
Author's institutionUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Abstract (english)
This paper presents a Koopman operator model predictive control (KMPC) torque vectoring where the vehicle model is represented by a finite-dimensional approximation of the Koopman operator obtained by using the extended dynamic mode decomposition. The Koopman operator acts like a linear predictor for a nonlinear dynamical system by lifting the nonlinear dynamics into a higher dimensional space where its evolution becomes linear. Different scenarios are simulated using the nonlinear vehicle... More model to generate the required data set and to obtain the Koopman model used for the KMPC. The KMPC was implemented on the dSPACE MicroLabBox platform, followed by its evaluation in two different experiments. These experiments are conducted using a scaled four-wheel-drive electric vehicle driving on a treadmill that serves as a surrogate for the roadway. The performance of KMPC is compared to that of linear time-varying model predictive controller (LTV-MPC), and nonlinear model predictive controller (NMPC). The results show not only the real-time applicability of KMPC but also a comparable performance and lower computational complexity compared to NMPC. Additionally, an interesting effect of discretization and communication delay on the performance of both LTV-MPC, and NMPC is observed, whereas KMPC demonstrates robustness in this scenario. Less
Keywords (english)
Languageenglish
Publication typeScientific paper - Original scientific paper
Publication statusPublished
Peer reviewPeer review - international
Publication versionPublished version
Journal titleControl Engineering Practice
Numberingvol. 158, 106272
BPC3360 EUR
p-ISSN0967-0661
DOIhttps://doi.org/10.1016/j.conengprac.2025.106272
URN:NBNurn:nbn:hr:168:116194
Online first2025-02-15
ProjectNumber: UIP-2019-04-6487
Title (croatian): Prediktivno upravljanje dinamikom vozila
Title (english): Predictive vehicle dynamics control
Acronym: PVDC
Leader: Šandor Ileš
Jurisdiction: Croatia
Funding stream: Installation Research Projects
Document URLhttps://www.sciencedirect.com/science/article/pii/S0967066125000358
Type of resourceText
Access conditionsOpen access
Terms of useLicence Attribution 4.0 International (CC BY 4.0) icon
Created on2025-03-24 11:15:33
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