Longitudinal control of platoon for electric vehicle using adaptive neural networks

Makoto Katayama; Koji Ichikawa; Yoshitaka Oikawa; Hiromitsu Ohmori

doi:10.3182/20050703-6-cz-1902.00257

Longitudinal control of platoon for electric vehicle using adaptive neural networks

Makoto Katayama, Koji Ichikawa, Yoshitaka Oikawa, Hiromitsu Ohmori

Department of System Design Engineering

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

Abstract

in AHS(Automated Highway Systems) project which is one of the ITS (Intelligent Highway Systems), the platoon control is developed. in this paper, a platoon control law based on Adaptive Neural Network (ANN) to lower level and Semi-Autonomous Adaptive Cruise Control (SAACC) to upper level is proposed. Moreover, there is "Delay" with the communication and the sensor. We design their compensators, and did stability analysis that takes those error into consideration. We confirmed that the closed loop system is stable, and confirmed the effectiveness in the numerical simulation.

Original language	English
Title of host publication	Proceedings of the 16th IFAC World Congress, IFAC 2005
Publisher	IFAC Secretariat
Pages	217-222
Number of pages	6
ISBN (Print)	008045108X, 9780080451084
DOIs	https://doi.org/10.3182/20050703-6-cz-1902.00257
Publication status	Published - 2005

Publication series

Name	IFAC Proceedings Volumes (IFAC-PapersOnline)
Volume	16
ISSN (Print)	1474-6670

Keywords

Adaptive control
Electric vehicles
Follow-up control
Inverse dynamics control
Neural networks
Nonlinear controlsystems

ASJC Scopus subject areas

Control and Systems Engineering

Access to Document

10.3182/20050703-6-cz-1902.00257

Cite this

Longitudinal control of platoon for electric vehicle using adaptive neural networks. / Katayama, Makoto; Ichikawa, Koji; Oikawa, Yoshitaka et al.
Proceedings of the 16th IFAC World Congress, IFAC 2005. IFAC Secretariat, 2005. p. 217-222 (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 16).

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

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title = "Longitudinal control of platoon for electric vehicle using adaptive neural networks",

abstract = "in AHS(Automated Highway Systems) project which is one of the ITS (Intelligent Highway Systems), the platoon control is developed. in this paper, a platoon control law based on Adaptive Neural Network (ANN) to lower level and Semi-Autonomous Adaptive Cruise Control (SAACC) to upper level is proposed. Moreover, there is {"}Delay{"} with the communication and the sensor. We design their compensators, and did stability analysis that takes those error into consideration. We confirmed that the closed loop system is stable, and confirmed the effectiveness in the numerical simulation.",

keywords = "Adaptive control, Electric vehicles, Follow-up control, Inverse dynamics control, Neural networks, Nonlinear controlsystems",

author = "Makoto Katayama and Koji Ichikawa and Yoshitaka Oikawa and Hiromitsu Ohmori",

note = "Funding Information: This work is supported in part by Grant in Aid for the 21st century center of excellence for “System Design: Paradigm Shift from Intelligence to Life” from Ministry of education, Culture, Sport, and Technology in Japan.",

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AU - Ichikawa, Koji

AU - Oikawa, Yoshitaka

AU - Ohmori, Hiromitsu

N1 - Funding Information: This work is supported in part by Grant in Aid for the 21st century center of excellence for “System Design: Paradigm Shift from Intelligence to Life” from Ministry of education, Culture, Sport, and Technology in Japan.

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N2 - in AHS(Automated Highway Systems) project which is one of the ITS (Intelligent Highway Systems), the platoon control is developed. in this paper, a platoon control law based on Adaptive Neural Network (ANN) to lower level and Semi-Autonomous Adaptive Cruise Control (SAACC) to upper level is proposed. Moreover, there is "Delay" with the communication and the sensor. We design their compensators, and did stability analysis that takes those error into consideration. We confirmed that the closed loop system is stable, and confirmed the effectiveness in the numerical simulation.

AB - in AHS(Automated Highway Systems) project which is one of the ITS (Intelligent Highway Systems), the platoon control is developed. in this paper, a platoon control law based on Adaptive Neural Network (ANN) to lower level and Semi-Autonomous Adaptive Cruise Control (SAACC) to upper level is proposed. Moreover, there is "Delay" with the communication and the sensor. We design their compensators, and did stability analysis that takes those error into consideration. We confirmed that the closed loop system is stable, and confirmed the effectiveness in the numerical simulation.

KW - Adaptive control

KW - Electric vehicles

KW - Follow-up control

KW - Inverse dynamics control

KW - Neural networks

KW - Nonlinear controlsystems

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SN - 008045108X

SN - 9780080451084

T3 - IFAC Proceedings Volumes (IFAC-PapersOnline)

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BT - Proceedings of the 16th IFAC World Congress, IFAC 2005

PB - IFAC Secretariat

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Longitudinal control of platoon for electric vehicle using adaptive neural networks

Abstract

Publication series

Keywords

ASJC Scopus subject areas

Access to Document

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