Intelligent Vehicle Trajectory Tracking Control Based on Adaptive Time Domain Parameter MPC

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Intelligent Vehicle Trajectory Tracking Control Based on Adaptive Time Domain Parameter MPC

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[1]LIU Zhiqiang,ZHANG Qing.Intelligent Vehicle Trajectory Tracking Control Based on Adaptive Time Domain Parameter MPC[J].Journal of Zhengzhou University (Engineering Science),2024,45(01):47-53.[doi:10.13705/j.issn.1671-6833.2023.04.005]

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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 45 Number of periods: 2024 01 Page number: 47-53 Column: Public date: 2024-01-19

Title:: Intelligent Vehicle Trajectory Tracking Control Based on Adaptive Time Domain Parameter MPC

Author(s):: LIU Zhiqiang; ZHANG Qing; College of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China

Keywords:: intelligent vehicle; trajectory tracking; model predictive control; adaptive; active front steering

CLC:: -

DOI:: 10.13705/j.issn.1671-6833.2023.04.005

Abstract:: In order to solve the problem of stability and control accuracy of intelligent vehicle active steering tracking control on low adhesion road surface, an intelligent vehicle trajectory tracking control strategy based on adaptive time domain parameters was proposed. Based on the vehicle dynamics model and model predictive control algorithm (MPC) , a linear time-varying MPC controller was established, and dynamic constraints including tire side deflection constraints, centroid side deflection constraints and front wheel angle constraints were added to solve the optimal front wheel steering angle. The influence of time domain parameters in the controller on the control effect was analyzed, and an adaptive time domain parameter controller was designed. According to the acquired vehicle speed, the optimal predictive time domain and control time domain parameters were obtained and input to the controller, improving the control accuracy and stability of the controller at different speeds. By building the MATLAB / SimuLink and CarSim co-simulation platform, the fixed time domain controller and adaptive time domain controller were compared and simulated with the condition of low adhesion road surface. The results showed that the adaptive time-domain controller could effectively improve the performance of the controller, reduce the lateral deviation, and improve the control accuracy of trajectory tracking. At the same time, it also had strong adaptability to different speeds, and the lateral deflection angle of the vehicle center of mass was controlled within 0°-1. 5°, which effectively ensured the stability of the vehicle.

References:: [1] 李印祥, 王凯. 基于滑模控制的汽车主动换道避障研究[J]. 车辆与动力技术, 2018(2)： 26-30, 35.LI Y X, WANG K. Research on vehicle obstacle avoi-dance based on synovium control[J]. Vehicle &Power Technology, 2018(2)： 26-30, 35.
[2] 张家旭, 周时莹, 施正堂, 等. 采用滑模条件积分的无人驾驶汽车弯道超车路径规划与跟踪控制[J]. 控制理论与应用, 2021, 38(2)： 197-205.ZHANG J X, ZHOU S Y, SHI Z T, et al. Path planning and tracking control for corner overtaking of driverless vehicle using sliding mode technique with conditional integrators[J]. Control Theory &Applications, 2021, 38(2)： 197-205.
[3] 李渊, 马戎, 付维平. 智能车辆的滑模轨迹跟踪控制[J]. 测控技术, 2012, 31(9)： 71-74.LI Y, MA R, FU W P. Sliding mode control for trajectory tracking of intelligent vehicle[J]. Measurement &Control Technology, 2012, 31(9)： 71-74.
[4] 聂枝根, 王万琼, 赵伟强, 等. 基于轨迹预瞄的智能汽车变道动态轨迹规划与跟踪控制[J]. 交通运输工程学报, 2020, 20(2)： 147-160.NIE Z G, WANG W Q, ZHAO W Q, et al. Dynamic trajectory planning and tracking control for lane change of intelligent vehicle based on trajectory preview[J]. Journal of Traffic and Transportation Engineering, 2020, 20(2)： 147-160.
[5] 寇发荣, 杨慧杰, 张新乾, 等. 采用状态反馈的无人车路径跟踪横向控制[J]. 机械科学与技术, 2022, 41(1)： 143-150.KOU F R, YANG H J, ZHANG X Q, et al. A lateral control strategy for unmanned vehicle path tracking using state feedback[J]. Mechanical Science and Technology for Aerospace Engineering, 2022, 41(1)： 143-150.
[6] 赵伟, 王宁宁, 段燕燕, 等. 载重汽车曲线行驶智能循迹控制仿真研究[J]. 郑州大学学报(工学版), 2015, 36(2)： 10-13.ZHAO W, WANG N N, DUAN Y Y, et al. The simulation study of the truck curve traveling intelligent traction control[J]. Journal of Zhengzhou University (Enginee-ring Science), 2015, 36(2)： 10-13.
[7] WANG H, HUANG Y J, KHAJEPOUR A, et al. Crash mitigation in motion planning for autonomous vehicles[J]. IEEE Transactions on Intelligent Transportation Systems, 2019, 20(9)： 3313-3323.
[8] BRUSCHETTA M, MARAN F, BEGHI A. A fast implementation of MPC-based motion cueing algorithms for mid-size road vehicle motion simulators[J]. Vehicle System Dynamics, 2017, 55(6)： 802-826.
[9] PRACH A, KAYACAN E. An MPC-based position controller for a tilt-rotor tricopter VTOL UAV[J]. Optimal Control Applications and Methods, 2018, 39(1)： 343-356.
[10] FALCONE P, BORRELLI F, TSENG H E, et al. Linear time-varying model predictive control and its application to active steering systems： stability analysis and experimental validation[J]. International Journal of Robust and Nonlinear Control, 2008, 18(8)： 862-875.
[11] WU H D, SI Z L, LI Z H. Trajectory tracking control for four-wheel independent drive intelligent vehicle based on model predictive control[J]. IEEE Access, 2020,8： 73071-73081.
[12] 张维刚, 张朋, 韦昊, 等. 一种基于LTVMPC改进的无人驾驶汽车路径跟踪控制算法[J]. 湖南大学学报(自然科学版), 2021, 48(10)： 67-73.ZHANG W G, ZHANG P, WEI H, et al. An improved path tracking control algorithm for autonomous vehicle based on LTVMPC[J]. Journal of Hunan University (Natural Sciences), 2021, 48(10)： 67-73.
[13] 由智恒. 基于MPC算法的无人驾驶车辆轨迹跟踪控制研究[D]. 长春：吉林大学, 2019.YOU Z H. Research on model predictive control-based trajectory tracking for unmanned vehicles[D]. Changchun： Jilin University, 2019.
[14] ZHANG K W, SUN Q, SHI Y. Trajectory tracking control of autonomous ground vehicles using adaptive learning MPC[J]. IEEE Transactions on Neural Networks and Learning Systems, 2021, 32(12)： 5554-5564.
[15] YUAN T F, ZHAO R C. LQR-MPC-based trajectory-tracking controller of autonomous vehicle subject to coupling effects and driving state uncertainties[J]. Sensors, 2022, 22(15)： 5556.
[16] 王艺, 蔡英凤, 陈龙, 等. 基于模型预测控制的智能车辆路径跟踪控制器设计[J]. 汽车技术, 2017(10)： 44-48.WANG Y, CAI Y F, CHEN L, et al. Design of intelligent vehicle path tracking controller based on model predictive control[J]. Automobile Technology, 2017(10)： 44-48.
[17] 王艺, 蔡英凤, 陈龙, 等. 基于模型预测控制的智能网联汽车路径跟踪控制器设计[J]. 机械工程学报, 2019, 55(8)： 136-144, 153.WANG Y, CAI Y F, CHEN L, et al. Design of intelligent and connected vehicle path tracking controller based on model predictive control[J]. Journal of Mechanical Engineering, 2019, 55(8)： 136-144, 153.
[18] 王银, 张灏琦, 孙前来, 等. 基于自适应MPC算法的轨迹跟踪控制研究[J]. 计算机工程与应用, 2021, 57(14)： 251-258.WANG Y, ZHANG H Q, SUN Q L, et al. Research on trajectory tracking control based on adaptive MPC algorithm[J]. Computer Engineering and Applications, 2021, 57(14)： 251-258.

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Last Update: 2024-01-24