Cloud-aided moving horizon state estimation of a full-car semi-active suspension system

Lixian Zhang; Xunyuan Yin; Junnan Shen; Haitao Yu

doi:10.1109/SMC.2016.7844293

Cloud-aided moving horizon state estimation of a full-car semi-active suspension system

Lixian Zhang
, Xunyuan Yin
, Junnan Shen
, Haitao Yu

Department of Chemical and Materials Engineering
Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Scopus citations

Abstract

In this work, we investigate a state estimation problem for a full-car semi-active suspension system. To account for the complex calculation and optimization problems, a vehicle-to-cloud-to-vehicle (V2C2V) scheme is utilized. Moving horizon estimation is introduced for the state estimation system design. All the optimization problems are solved in a remotely-embedded agent with high computational ability. Measurements and state estimates are transmitted between the vehicle and the remote agent via networked communication channels. The effectiveness of the proposed method is illustrated via a set of simulations.

Original language	English
Title of host publication	2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	527-532
Number of pages	6
ISBN (Electronic)	9781509018970
DOIs	https://doi.org/10.1109/SMC.2016.7844293
State	Published - 6 Feb 2017
Event	2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Budapest, Hungary Duration: 9 Oct 2016 → 12 Oct 2016

Publication series

Name	2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings

Conference

Conference	2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016
Country/Territory	Hungary
City	Budapest
Period	9/10/16 → 12/10/16

Access to Document

10.1109/SMC.2016.7844293

Cite this

Zhang, L., Yin, X., Shen, J., & Yu, H. (2017). Cloud-aided moving horizon state estimation of a full-car semi-active suspension system. In 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings (pp. 527-532). Article 7844293 (2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2016.7844293

Zhang, Lixian ; Yin, Xunyuan ; Shen, Junnan et al. / Cloud-aided moving horizon state estimation of a full-car semi-active suspension system. 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 527-532 (2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings).

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title = "Cloud-aided moving horizon state estimation of a full-car semi-active suspension system",

abstract = "In this work, we investigate a state estimation problem for a full-car semi-active suspension system. To account for the complex calculation and optimization problems, a vehicle-to-cloud-to-vehicle (V2C2V) scheme is utilized. Moving horizon estimation is introduced for the state estimation system design. All the optimization problems are solved in a remotely-embedded agent with high computational ability. Measurements and state estimates are transmitted between the vehicle and the remote agent via networked communication channels. The effectiveness of the proposed method is illustrated via a set of simulations.",

author = "Lixian Zhang and Xunyuan Yin and Junnan Shen and Haitao Yu",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 ; Conference date: 09-10-2016 Through 12-10-2016",

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Zhang, L, Yin, X, Shen, J & Yu, H 2017, Cloud-aided moving horizon state estimation of a full-car semi-active suspension system. in 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings., 7844293, 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 527-532, 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016, Budapest, Hungary, 9/10/16. https://doi.org/10.1109/SMC.2016.7844293

Cloud-aided moving horizon state estimation of a full-car semi-active suspension system. / Zhang, Lixian; Yin, Xunyuan; Shen, Junnan et al.
2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 527-532 7844293 (2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - In this work, we investigate a state estimation problem for a full-car semi-active suspension system. To account for the complex calculation and optimization problems, a vehicle-to-cloud-to-vehicle (V2C2V) scheme is utilized. Moving horizon estimation is introduced for the state estimation system design. All the optimization problems are solved in a remotely-embedded agent with high computational ability. Measurements and state estimates are transmitted between the vehicle and the remote agent via networked communication channels. The effectiveness of the proposed method is illustrated via a set of simulations.

AB - In this work, we investigate a state estimation problem for a full-car semi-active suspension system. To account for the complex calculation and optimization problems, a vehicle-to-cloud-to-vehicle (V2C2V) scheme is utilized. Moving horizon estimation is introduced for the state estimation system design. All the optimization problems are solved in a remotely-embedded agent with high computational ability. Measurements and state estimates are transmitted between the vehicle and the remote agent via networked communication channels. The effectiveness of the proposed method is illustrated via a set of simulations.

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DO - 10.1109/SMC.2016.7844293

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BT - 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016

Y2 - 9 October 2016 through 12 October 2016

ER -

Zhang L, Yin X, Shen J, Yu H. Cloud-aided moving horizon state estimation of a full-car semi-active suspension system. In 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 527-532. 7844293. (2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings). doi: 10.1109/SMC.2016.7844293

Cloud-aided moving horizon state estimation of a full-car semi-active suspension system

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