KFU. Card publication. Road Train Sideslip and Jackknifing Angle Estimation using Functional Observer

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

ROAD TRAIN SIDESLIP AND JACKKNIFING ANGLE ESTIMATION USING FUNCTIONAL OBSERVER

Form of presentation

Conference proceedings in international journals and collections

Year of publication

2021

Authors, employees of KFU

Volkov Vasiliy Gennadevich, author

Demyanov Dmitriy Nikolaevich, author

Authors, postgraduates KFU

Galimova Gulshat Rifkatovna, postgraduate kfu

Bibliographic description in the original language

Volkov V., Galimova G., Demyanov D. Road Train Sideslip and Jackknifing Angle Estimation using Functional Observer //2021 International Russian Automation Conference (RusAutoCon). ? IEEE, 2021. ? S. 934-939.

Annotation

In this paper we consider the problem of a road train dynamic parameter estimation, specifically the truck and semitrailer axle sideslip angles, and road train jackknifing angle. We introduce a state-space linear model of road train planar motion obtained via the analytical linearization of the nonlinear model under the assumption of small slip and jackknifing angles. For this state-space linear model, we devise a linear functional of its state variables to calculate the slip and jackknifing angles. Using these proposed state-space models and linear functional of its states we design a functional observer to estimate the slip and jackknifing angles. Finally, analyzing the computer simulation results, we show that the proposed algorithm of the slip and jackknifing angles of a road train estimation works fairly well, with low estimation error, even under quite difficult driving maneuvers.

Keywords

road train, slip angle, jackknifing angle, estimation, observation, functional observer, minimal order observer

Publishing house

IEEE

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=257334&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Volkov Vasiliy Gennadevich	ru_RU
dc.contributor.author	Demyanov Dmitriy Nikolaevich	ru_RU
dc.contributor.author	Galimova Gulshat Rifkatovna	ru_RU
dc.date.accessioned	2021-01-01T00:00:00Z	ru_RU
dc.date.available	2021-01-01T00:00:00Z	ru_RU
dc.date.issued	2021	ru_RU
dc.identifier.citation	Volkov V., Galimova G., Demyanov D. Road Train Sideslip and Jackknifing Angle Estimation using Functional Observer //2021 International Russian Automation Conference (RusAutoCon). ? IEEE, 2021. ? �. 934-939.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=257334&p_lang=2	ru_RU
dc.description.abstract	In this paper we consider the problem of a road train dynamic parameter estimation, specifically the truck and semitrailer axle sideslip angles, and road train jackknifing angle. We introduce a state-space linear model of road train planar motion obtained via the analytical linearization of the nonlinear model under the assumption of small slip and jackknifing angles. For this state-space linear model, we devise a linear functional of its state variables to calculate the slip and jackknifing angles. Using these proposed state-space models and linear functional of its states we design a functional observer to estimate the slip and jackknifing angles. Finally, analyzing the computer simulation results, we show that the proposed algorithm of the slip and jackknifing angles of a road train estimation works fairly well, with low estimation error, even under quite difficult driving maneuvers.	ru_RU
dc.language.iso	ru	ru_RU
dc.publisher	IEEE	ru_RU
dc.subject	road train	ru_RU
dc.subject	slip angle	ru_RU
dc.subject	jackknifing angle	ru_RU
dc.subject	estimation	ru_RU
dc.subject	observation	ru_RU
dc.subject	functional observer	ru_RU
dc.subject	minimal order observer	ru_RU
dc.title	Road Train Sideslip and Jackknifing Angle Estimation using Functional Observer	ru_RU
dc.type	Conference proceedings in international journals and collections	ru_RU