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Distributed Sliding Mode Platoon Control under Bidirectional Multi-vehicle Information Flow Topology

Published: 19 April 2023 Publication History

Abstract

In the control architecture of the platoon system, the interaction of the information between the vehicles is determined by the information flow topology. However, the current studies on platoon control are often restricted to a specific information flow topology. This paper proposes a distributed sliding mode control (DSMC) strategy for a platoon under bidirectional multi-vehicle information flow topology. Firstly, the platoon control is decomposed into upper level and lower level controllers by hierarchical strategy. In contrast to the lower controller, which uses an inverse dynamics model to achieve the consistency of the actual acceleration and the expected acceleration, the upper DSMC strategy optimizes expected acceleration. Topological sliding surface design and topological reaching law design constitute two components of the upper DSMC strategy. The topological sliding surface is defined by weighted summation of errors, and the topological reaching law is defined based on the information flow topology. In addition, the stability of the platoon is proved by Lyapunov function. On this basis, the effectiveness of the proposed DSMC strategy is verified on the Carsim/Simulink platform under the typical bidirectional multi-vehicle information flow topology.

References

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Wang, Z., Bian, Y., Shladover, S. E., Barth, M. J., & Li, S. 2020. A survey on cooperative longitudinal motion control of multiple connected and automated vehicles. IEEE Intelligent Transportation Systems Magazine, 2020, (Spring), 4-24.
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Guo, H., Liu, J., Dai, Q., Chen, H., Wang, Y., & Zhao, W. 2020. A distributed adaptive triple-step nonlinear control for a connected automated vehicle platoon with dynamic uncertainty. IEEE Internet of Things Journal, 7 (5), 3861-3871.
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Bian, Y., Zheng, Y., Ren, W., Li, S. E., Wang, J., & Li, K. 2019. Reducing time headway for platooning of connected vehicles via V2V communication. Transportation Research Part C: Emerging Technologies, 102, 87-105.
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Guo, G., Li, P., & Hao, L. Y. 2020. A new quadratic spacing policy and adaptive fault-tolerant platooning with actuator saturation. IEEE Transactions on Intelligent Transportation Systems.
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Li, H., Wu, H., Gulati, I., Ali, S. A., Pickert, V., & Dlay, S. 2022. An improved sliding mode control (SMC) approach for enhancement of communication delay in vehicle platoon system. IET Intelligent Transport Systems, 16 (7), 958-970.
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Yan, M., Song, J., Zuo, L., & Yang, P. 2017. Neural adaptive sliding-mode control of a vehicle platoon using output feedback. Energies, 10 (11), 1906.
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RICAI '22: Proceedings of the 2022 4th International Conference on Robotics, Intelligent Control and Artificial Intelligence
December 2022
1396 pages
ISBN:9781450398343
DOI:10.1145/3584376
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

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Published: 19 April 2023

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