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International Conference on Neural Information Processing

ICONIP 2017: Neural Information Processing pp 122–129Cite as

Data-Driven Nonlinear Adaptive Optimal Control of Connected Vehicles

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10639))

Abstract

This paper studies the cooperative adaptive cruise control (CACC) problem of connected vehicles with unknown nonlinear dynamics. Different from the existing literature on CACC, a data-driven optimal control policy is developed by global adaptive dynamic programming (GADP). Interestingly, the developed control policy achieves global stabilization of the nonlinear vehicular platoon system in the absence of the a priori knowledge of system dynamics. Numerical simulation results are presented to validate the effectiveness of the developed approach.

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Acknowledgments

This work has been supported in part by the U.S. National Science Foundation grant ECCS-1501044.

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Authors and Affiliations

  1. Department of Electrical Engineering, Allen E. Paulson College of Engineering and Information Technology, Georgia Southern University, Statesboro, GA, 30460, USA

    Weinan Gao

  2. Department of Electrical and Computer Engineering, Tandon School of Engineering, New York University, Brooklyn, NY, 11201, USA

    Zhong-Ping Jiang

Authors
  1. Weinan Gao
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  2. Zhong-Ping Jiang
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Corresponding author

Correspondence to Weinan Gao .

Editor information

Editors and Affiliations

  1. Guangdong University of Technology, Guangzhou, China

    Derong Liu

  2. Guangdong University of Technology, Guangzhou, China

    Shengli Xie

  3. South China University of Technology, Guangzhou, China

    Yuanqing Li

  4. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Dongbin Zhao

  5. King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    El-Sayed M. El-Alfy

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© 2017 Springer International Publishing AG

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Gao, W., Jiang, ZP. (2017). Data-Driven Nonlinear Adaptive Optimal Control of Connected Vehicles. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10639. Springer, Cham. https://doi.org/10.1007/978-3-319-70136-3_13

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  • DOI: https://doi.org/10.1007/978-3-319-70136-3_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70135-6

  • Online ISBN: 978-3-319-70136-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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