Advanced Transportation Equipment

Adaptive Coordinated Path Tracking Control Strategy for Autonomous Vehicles with Direct Yaw Moment Control

  • Ying Tian ,
  • Qiangqiang Yao ,
  • Peng Hang ,
  • Shengyuan Wang
展开
  • 1. Beijing Key Laboratory of Powertrain for New Energy Vehicle, School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing, 100044, China;
    2. School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, 639798, Singapore

收稿日期: 2021-04-06

  修回日期: 2021-11-24

  网络出版日期: 2022-06-30

基金资助

Supported by the Foundation of Key Laboratory of Vehicle Advanced Manufacturing, Measuring and Control Technology (Beijing Jiaotong University), Ministry of Education, China (Grant No. 014062522006), National Key Research Development Program of China (Grant No. 2017YFB0103701)

Adaptive Coordinated Path Tracking Control Strategy for Autonomous Vehicles with Direct Yaw Moment Control

  • Ying Tian ,
  • Qiangqiang Yao ,
  • Peng Hang ,
  • Shengyuan Wang
Expand
  • 1. Beijing Key Laboratory of Powertrain for New Energy Vehicle, School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing, 100044, China;
    2. School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, 639798, Singapore

Received date: 2021-04-06

  Revised date: 2021-11-24

  Online published: 2022-06-30

Supported by

Supported by the Foundation of Key Laboratory of Vehicle Advanced Manufacturing, Measuring and Control Technology (Beijing Jiaotong University), Ministry of Education, China (Grant No. 014062522006), National Key Research Development Program of China (Grant No. 2017YFB0103701)

摘要

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.

本文引用格式

Ying Tian , Qiangqiang Yao , Peng Hang , Shengyuan Wang . Adaptive Coordinated Path Tracking Control Strategy for Autonomous Vehicles with Direct Yaw Moment Control[J]. Chinese Journal of Mechanical Engineering, 2022 , 35(1) : 1 -1 . DOI: 10.1186/s10033-021-00666-0

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.

参考文献

[1] P Song, B L Gao, S G Xie, et al. Optimal predictive control for path following of a full drive-by-wire vehicle at varying speeds. Chinese Journal of Mechanical Engineering, 2017, 30(3):711-172.
[2] Q Q Yao, Y Tian, Q Wang, et al. Control strategies on path tracking for autonomous vehicle:state of the art and future challenges. IEEE Access, 2020, 8:161211-161222.
[3] S B Xu, H Peng. Design, Analysis, and Experiments of preview path tracking control for autonomous vehicles. IEEE Transactions on Intelligent Transportation Systems, 2020, 21(1):48-58.
[4] P Hang, X Xia, X Chen. Handling stability advancement with 4WS and DYC coordinated control:a gain-scheduled robust control approach. IEEE Transactions on Vehicular Technology, 2021, 70(4):3164-3174.
[5] Q Q Yao, Y Tian. A model predictive controller with longitudinal speed compensation for autonomous vehicle path tracking. Applied Sciences, 2019, 9(22):4739.
[6] F Lin, Y W Zhang, Y Q Zhao, et al. Trajectory tracking of autonomous vehicle with the fusion of DYC and longitudinal-lateral. Chinese Journal of Mechanical Engineering, 2019, 32:16.
[7] C Y Sun, X Zhang, L H Xi, et al. Design of a path-tracking steering controller for autonomous vehicles. Energies, 2018, 11(6):1451.
[8] P Hang, X B Chen, W Wang. Cooperative control framework for human driver and active rear steering system to advance active safety. IEEE Transactions on Intelligent Vehicles, 2021, 6(3):460-469.
[9] C Y Sun, X Zhang, Q Zhou, et al. A model predictive controller with switched tracking error for autonomous vehicle path tracking. IEEE Access, 2019, 7:53103-53114.
[10] A T Nguyen, C Sentouh, H Zhang, et al. Fuzzy static output feedback control for path following of autonomous vehicles with transient performance improvements. IEEE Transactions on Intelligent Transportation Systems, 2020, 21(7):3069-3079.
[11] Z J Wang, J M Wang. Ultra-local model predictive control:A model-free approach and its application on automated vehicle trajectory tracking. Control Engineering Practice, 2020, 101:104482.
[12] W Zhang. A robust lateral tracking control strategy for autonomous driving vehicles. Mechanical Systems and Signal Processing, 2021, 150:107238.
[13] M Fnadi, W Q Du, F Plumet, et al. Constrained model predictive control for dynamic path tracking of a bi-steerable rover on slippery grounds. Control Engineering Practice, 2021. 107:104693.
[14] K Kritayakirana, J C Gerdes. Using the center of percussion to design a steering controller for an autonomous race car. Vehicle System Dynamics, 2012. 50(suppl. 1):33-51.
[15] N R Kapania, J C Gerdes. Design of a feedback-feedforward steering controller for accurate path tracking and stability at the limits of handling. Vehicle System Dynamics, 2015, 53(12):1687-1704.
[16] J Funke, M Brown, S M Erlien, et al. Collision avoidance and stabilization for autonomous vehicles in emergency scenarios. IEEE Transactions on Control Systems Technology, 2017, 25(4):1204-1216.
[17] S M Erlien, S Fujita, J C Gerdes. Shared steering control using safe envelopes for obstacle avoidance and vehicle stability. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(2):441-451.
[18] J Y Goh, T Goel, J C Gerdes. Toward automated vehicle control beyond the stability limits:drifting along a general path. Journal of Dynamic Systems, Measurement, and Control, 2020:142.
[19] A Nahidi, A Kasaiezadeh, S Khosravani, et al. Modular integrated longitudinal and lateral vehicle stability control for electric vehicles. Mechatronics, 2017, 44:60-70.
[20] A Tahouni, M Mirzaei, B Najjari. Novel constrained nonlinear control of vehicle dynamics using integrated active torque vectoring and electronic stability control. IEEE Transactions on Vehicular Technology, 2019, 68(10):9564-9572.
[21] H N Peng, W D Wang, Q An, et al. Path tracking and direct yaw moment coordinated control based on robust MPC with the finite time horizon for autonomous independent-drive vehicles. IEEE Transactions on Vehicular Technology, 2020, 69(6):6053-6066.
[22] J C Chen, Z B Shuai, H Zhang, et al. Path following control of autonomous four-wheel-independent-drive electric vehicles via second-order sliding mode and nonlinear disturbance observer techniques. IEEE Transactions on Industrial Electronics, 2021, 68(3):2460-2469.
[23] J H Guo, Y G Luo, K Q Li, et al. Coordinated path-following and direct yaw-moment control of autonomous electric vehicles with sideslip angle estimation. Mechanical Systems and Signal Processing, 2018, 105:183-199.
[24] J Xie, X Xu, F Wang, et al. Coordinated control based path following of distributed drive autonomous electric vehicles with yaw-moment control. Control Engineering Practice, 2021, 106:104659.
[25] C Hu, H Jing, R R Wang, et al. Robust output-feedback control for path following of autonomous ground vehicles. Mechanical Systems and Signal Processing, 2016, 70-71:414-427.
[26] H Taghavifar, S Rakheja. Path-tracking of autonomous vehicles using a novel adaptive robust exponential-like-sliding-mode fuzzy type-2 neural network controller. Mechanical Systems and Signal Processing, 2019, 130:41-55.
[27] J Zhang, B J Zhang, N Zhang, et al. A novel robust event-triggered fault tolerant automatic steering control approach of autonomous land vehicles under in-vehicle network delay. International Journal of Robust and Nonlinear Control, 2021, 31(7):2436-2464.
[28] L Ling, M Li, M Yu, et al. Parameter identification method for the tire cornering stiffness of model vehicle. Autimotive Engineering, 2016, 38(12):1508-1515. (In Chinese)
[29] F Lin, H D Zhang, Y Q Zhao, et al. Road friction condition identification based on tire lateral stiffness estimation. Journal of South China University of Technology, 2019, 47(11):16-24. (in Chinese)
[30] Y Tian, Q Q Yao, C Q Wang, et al. Switched model predictive controller for path tracking of autonomous vehicle considering rollover stability. Vehicle System Dynamics, 2021. https://doi.org/10.1080/00423114.2021.1999990
[31] P G Stankiewicz, A A Brown, S N Brennan. Preview horizon analysis for vehicle rollover prevention using the zero-moment point. Journal of Dynamic Systems, Measurement, and Control, 2015, 137:091002.
[32] X H Li, Z P Sun, D P Cao, et al. Development of a new integrated local trajectory planning and tracking control framework for autonomous ground vehicles. Mechanical Systems and Signal Processing, 2017, 87:118-137.
[33] G Pereira, L Svensson, Lima, et al. Lateral model predictive control for over-actuated autonomous vehicle. Proceedings of 2017 IEEE Intelligent Vehicles Symposium, Redondo Beach, CA, USA, June 11-14, 2017:310-316.
文章导航

/