Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/162747
Title: Adaptive coordinated path tracking control strategy for autonomous vehicles with direct yaw moment control
Authors: Tian, Ying
Yao, Qiangqiang
Hang, Peng
Wang, Shengyuan
Keywords: Engineering::Mechanical engineering
Issue Date: 2022
Source: Tian, Y., Yao, Q., Hang, P. & Wang, S. (2022). Adaptive coordinated path tracking control strategy for autonomous vehicles with direct yaw moment control. Chinese Journal of Mechanical Engineering (English Edition), 35(1). https://dx.doi.org/10.1186/s10033-021-00666-0
Journal: Chinese Journal of Mechanical Engineering (English Edition)
Abstract: It is a striking fact that the path tracking accuracy of autonomous vehicles based on active front wheel steering is poor under high-speed and large-curvature conditions. In this study, an adaptive path tracking control strategy that coordinates active front wheel steering and direct yaw moment is proposed based on model predictive control algorithm. The recursive least square method with a forgetting factor is used to identify the rear tire cornering stiffness and update the path tracking system prediction model. To adaptively adjust the priorities of path tracking accuracy and vehicle stability, an adaptive strategy based on fuzzy rules is applied to change the weight coefficients in the cost function. An adaptive control strategy for coordinating active front steering and direct yaw moment is proposed to improve the path tracking accuracy under high-speed and large-curvature conditions. To ensure vehicle stability, the sideslip angle, yaw rate and zero moment methods are used to construct optimization constraints based on the model predictive control frame. It is verified through simulation experiments that the proposed adaptive coordinated control strategy can improve the path tracking accuracy and ensure vehicle stability under high-speed and large-curvature conditions.
URI: https://hdl.handle.net/10356/162747
ISSN: 1000-9345
DOI: 10.1186/s10033-021-00666-0
Rights: © The Author(s) 2022. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

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