TIAN J , ZENG Q K , WANG P , et al . Active steering control based on preview theory for articulated heavy vehicles [J ] . PLoS One , 2021 , 16 ( 5 ): e0252098 .

CHENG C , CEBON D . Improving roll stability of articulated heavy vehicles using active semi-trailer steering [J ] . Vehicle System Dynamics , 2008 , 46 ( S1 ): 373 - 388 .

MARUMO Y , YOKOTA T , AOKI A . Improving stability and lane-keeping performance for multi-articulated vehicles using vector follower control [J ] . Vehicle System Dynamics , 2020 , 58 ( 12 ): 1859 - 1872 .

ZHANG Y B , KHAJEPOUR A , ATAEI M . A universal and reconfigurable stability control methodology for articulated vehicles with any configurations [J ] . IEEE Transactions on Vehicular Technology , 2020 , 69 ( 4 ): 3748 - 3759 .

DING N G , ZHANG Y P , GAO F , et al . A gain-scheduled PID controller for automatic path following of a tractor semi-trailer [J ] . SAE International Journal of Commercial Vehicles , 2013 , 6 ( 1 ): 110 - 117 .

KOLB J K , NITZSCHE G , WAGNER S . A simple yet efficient path tracking controller for autonomous trucks [J ] . IFAC-Papers OnLine , 2019 , 52 ( 8 ): 307 - 312 .

MANAV A C , LAZOGLU I , AYDEMIR E . Adaptive path-following control for autonomous semi-trailer docking [J ] . IEEE Transactions on Vehicular Technology , 2021 , 71 ( 1 ): 69 - 85 .

MIAO S Y , ZHOU Y S . An identical path tracking control strategy of the tractor-trailer wheeled mobile robot with an off-axle hitching based on a passive steering angle [J ] . Journal of the Franklin Institute , 2024 , 361 ( 4 ): 106634 .

JI X W , HE X K , LV C , et al . Adaptive-neural-network-based robust lateral motion control for autonomous vehicle at driving limits [J ] . Control Engineering Practice , 2018 , 76 : 41 - 53 .

BARBOSA F M , MARCOS L B , DA SILVA M M , et al . Robust path-following control for articulated heavy-duty vehicles [J ] . Control Engineering Practice , 2019 , 85 : 246 - 256 . DOI: 10.1016/j.conengprac.2019.01.017 http://doi.org/10.1016/j.conengprac.2019.01.017 Path following and lateral stability are crucial issues for autonomous vehicles. Moreover, these problems increase in complexity when handling articulated heavy-duty vehicles due to their poor manoeuvrability, large sizes and mass variation. In addition, uncertainties on mass may have the potential to significantly decrease the performance of the system, even to the point of destabilising it. These parametric variations must be taken into account during the design of the controller. However, robust control techniques usually require offline adjustment of auxiliary tuning parameters, which is not practical, leading to sub-optimal operation. Hence, this paper presents an approach to path-following and lateral control for autonomous articulated heavy-duty vehicles subject to parametric uncertainties by using a robust recursive regulator. The main advantage of the proposed controller is that it does not depend on the offline adjustment of tuning parameters. Parametric uncertainties were assumed to be on the payload, and an H-infinity controller was used for performance comparison. The performance of both controllers is evaluated in a double lane-change manoeuvre. Simulation results showed that the proposed method had better performance in terms of robustness, lateral stability, driving smoothness and safety, which demonstrates that it is a very promising control technique for practical applications.

LIU X Z , MADHUSUDHANAN A K , CEBON D . Minimum swept-path control for autonomous reversing of a tractor semi-trailer [J ] . IEEE Transactions on Vehicular Technology , 2019 , 68 ( 5 ): 4367 - 4376 .

ZHANG Y B . Multi-axle vehicle modeling and stability control:a reconfigurable approach [D ] . Waterloo,Ontario,Canada : University of Waterloo , 2019 .

刘聪 , 刘辉 , 韩立金 , 等 . 分布式电驱动车辆极限越野环境下高速避障与稳定性控制 [J ] . 兵工学报 , 2021 , 42 ( 10 ): 2102 - 2113 .

LIU C , LIU H , HAN L J , et al . High-speed obstacle avoidance and stability control of distributed electric drive vehicle under extreme off-road conditions [J ] . Acta Armamentarii , 2021 , 42 ( 10 ): 2102 - 2113 . (in Chinese) DOI: 10.3969/j.issn.1000-1093.2021.10.006 http://doi.org/10.3969/j.issn.1000-1093.2021.10.006 A layered coordinated lateral stability control method is proposed to improve the high-speed obstacle avoidance ability and handling stability of distributed electric drive vehicles in extreme off-road environment, in which the attitude feedback of vehicle during cornering is fully considered. The upper controller combines the multi-model online modeling algorithm with the nonlinear model predictive control theory, and a coordinated control strategy for yaw and roll motion based on data-driven multi-model predictive control is proposed. Considering that the optimal control center is time-varying under different lateral instability states of vehicle, a two-level integrated yaw dynamic model is refined and reconstructed.Considering the time-varying road curvature and lateral slope angle under off-road conditions, a zero-moment point-based rollover instability judgment model is constructed, and the rollover stability control constraint is introduced on the basis of yaw stability control. The lower level controller converts the fused yaw moment into each wheel drive torque based on the quadratic programming algorithm. The joint simulation of MATLAB/Simulink and Carsim was built for test verification. The results show that the proposed layered coordinated control method can give full play to the high maneuverability of distributed electric drive vehicles under extreme off-road condition, which has a strong body attitude correction ability, and can improve the path tracking accuracy and the lateral stability of vehicle during cornering.

卢佳兴 , 刘海鸥 , 关海杰 , 等 . 基于双参数自适应优化的无人履带车辆轨迹跟踪控制 [J ] . 兵工学报 , 2023 , 44 ( 4 ): 960 - 971 .

LU J X , LIU H O , GUAN H J , et al . Trajectory tracking control of unmanned tracked vehicles based on adaptive dual-parameter optimization [J ] . Acta Armamentarii , 2023 , 44 ( 4 ): 960 - 971 . (in Chinese) DOI: 10.12382/bgxb.2022.0009 http://doi.org/10.12382/bgxb.2022.0009 To improve the poor adaptability of trajectory tracking controllers with fixed parameters, an optimized adaptive dual-parameter trajectory tracking algorithm for unmanned tracked vehicles based on the improved Particle Swarm Optimization (IPSO) and Multi-Layer Perceptron (MLP) algorithms is proposed. In the offline state, based on the collected actual vehicle data, the IPSO algorithm is used to construct the optimal parameter data set under different motion primitives, aiming for high accuracy, high stability, and low time cost of trajectory tracking. With the motion primitive type and vehicle speed as feature vectors, control time domain length and control time step length as labels, adaptive learning rate optimization algorithm is used to complete the training of the MLP neural network model. In the online state, according to the trajectory information and vehicle state feedback information provided by the planning layer, the MLP neural network outputs the predicted optimal control time domain length and control time step. These parameters are then input to the model predictive controller as dual parameters, enabling the adaptive trajectory tracking control. ROS-VREP co-simulation test and actual vehicle test based on a bilateral electric drive platform are carried out. Vehicle test results show that under various working conditions including large curvature steering, the proposed controller achieves a 30.5% reduction in average lateral error, a 17.2% decrease in average heading error, and a 7.8% reduction in average change rate of rotation angle, compared with the fixed-parameter trajectory tracking control method with the same calculation time cost. The results verify the feasibility and effectiveness of the new algorithm.

KASSAEIYAN P , TARVIRDIZADEH B , ALIPOUR K . Control of tractor-trailer wheeled robots considering self-collision effect and actuator saturation limitations [J ] . Mechanical Systems and Signal Processing , 2019 , 127 : 388 - 411 .

李道飞 , 查安飞 , 徐彪 , 等 . 半挂汽车列车紧急避撞轨迹跟踪控制算法 [J ] . 汽车工程 , 2022 , 44 ( 7 ): 1098 - 1106 .

LI D F , ZHA A F , XU B , et al . Trajectory tracking control algorithm of emergency collision avoidance for tractor semi-trailer combination [J ] . Automotive Engineering , 2022 , 44 ( 7 ): 1098 - 1106 . (in Chinese)

李睿 , 项昌乐 , 王超 , 等 . 自动驾驶履带车辆鲁棒自适应轨迹跟踪控制方法 [J ] . 兵工学报 , 2021 , 42 ( 6 ): 1128 - 1137 . DOI: 10.3969/j.issn.1000-1093.2021.06.002 http://doi.org/10.3969/j.issn.1000-1093.2021.06.002 针对野外环境中自动驾驶履带车辆轨迹跟踪控制问题，考虑建模误差、参数不确定性及外界随机强干扰，以强鲁棒性及精确跟踪为目标，提出一种基于误差符号鲁棒积分的自动驾驶履带车辆鲁棒自适应轨迹跟踪控制方法。基于拉格朗日动力学方程建立自动驾驶履带车辆的运动学与动力学耦合模型；采用自适应控制方法实现对模型的精确前馈补偿，抵消模型非线性的影响；通过误差符号鲁棒积分有效抑制外界干扰及不确定性的影响；利用Lyapunov稳定性理论证明了闭环系统的全局渐进稳定性与收敛性。对仿真结果进行了实车实验一致性验证。仿真和实验结果证明：该方法在存在建模误差、参数不确定性、外界干扰条件下，在实现自动驾驶履带车辆高精度轨迹跟踪控制的同时，具有较强的自适应和鲁棒性。

LI R , XIANG C L , WANG C , et al . Robust adaptive trajectory tracking control approach for autonomous tracked vehicles [J ] . Acta Armamentarii , 2021 , 42 ( 6 ): 1128 - 1137 . (in Chinese) DOI: 10.3969/j.issn.1000-1093.2021.06.002 http://doi.org/10.3969/j.issn.1000-1093.2021.06.002 A robust adaptive trajectory tracking control approach based on robust integral of sign of error is presented for the trajectory tracking control of autonomous tracked vehicles in the field environment. In the proposed approach, the modelling errors, parametric uncertainties, and external random and strong disturbances are taken into account. A kinematic and dynamic coupling model of autonomous tracked vehicles is established based on Lagrangian dynamical equation. The feedforward compensation of the established model is realized by adaptive control approach, and the external disturbances and uncertainties can be suppressed by using the robust integral of sign of error. And then the asymptotical global stability and convergence of the closed loop system is demonstrated by Lyapunov stability theory. The simulated results were verified through real vehicle test. Simulated and experimental results show that the proposed approach can be used to realize the high accuracy trajectory tracking and insure the adaptiveness and robustness for autonomous tracked vehicles in the presence of modelling errors, parametric uncertainties and external disturbances.

SHARMA T , HE Y P . Design of a tracking controller for autonomous articulated heavy vehicles using a nonlinear model predictive control technique [J ] . Proceedings of the Institution of Mechanical Engineers,Part K:Journal of Multi-body Dynamics , 2024 , 238 ( 2 ): 334 - 362 .

DE BERNARDIS M , RINI G , BOTTIGLIONE F , et al . On nonlinear model predictive direct yaw moment control for trailer sway mitigation [J ] . Vehicle System Dynamics , 2023 , 61 ( 2 ): 445 - 471 .

LI E H , YU H L , XI J Q , et al . Stability-guaranteed model predictive path tracking of autonomous tractor semi-trailers under extreme conditions [J/OL ] . IEEE Transactions on Intelligent Vehicles , 2024 (2024-03-18). https://doi.org/10.1109/TIV.2024.3376676. https://doi.org/10.1109/TIV.2024.3376676 https://doi.org/10.1109/TIV.2024.3376676

DUAN J L , REN Y G , ZHANG F W , et al . Encoding distributional soft actor-critic for autonomous driving in multi-lane scenarios [J ] . IEEE Computational Intelligence Magazine , 2024 , 19 ( 2 ): 96 - 112 .

肖礼明 , 张发旺 , 陈良发 , 等 . 依托多风格强化学习的车辆轨迹跟踪避撞控制 [J ] . 汽车工程 , 2024 , 46 ( 6 ): 945 - 955 .

XIAO L M , ZHANG F W , CHEN L F , et al . Vehicle trajectory tracking and collision avoidance control based on multi-style reinforcement learning [J ] . Automotive Engineering , 2024 , 46 ( 6 ): 945 - 955 . (in Chinese)

DUAN J L , GUAN Y , EBEN LI S E , et al . Distributional soft actor-critic:off-policy reinforcement learning for addressing value estimation errors [J ] . IEEE Transactions on Neural Networks and Learning Systems , 2021 , 33 ( 11 ): 6584 - 6598 .

ANDERSSON J A E , GILLIS J , HORN G , et al . CasADi:a software framework for nonlinear optimization and optimal control [J ] . Mathematical Programming Computation , 2019 , 11 : 1 - 36 .

刘辉 , 张发旺 , 聂士达 , 等 . 基于逆模型预测控制的拟人驾驶控制 [J ] . 汽车工程 , 2024 , 46 ( 4 ): 596 - 604 .

LIU H , ZHANG F W , NIE S D , et al . Human-like driving control based on inverse model predictive control [J ] . Automotive Engineering , 2024 , 46 ( 4 ): 596 - 604 . (in Chinese)

ZHANG F W , DUAN J L , XU H Y , et al . Inverse model predictive control:learning optimal control cost functions for MPC [J ] . IEEE Transactions on Industrial Informatics , 2024 , 20 ( 12 ): 13644 - 13655 .

国家标准化管理委员会 . 道路车辆重型商用汽车列车和铰接客车横向稳定性试验方法:GB/T 25979-2010 [S ] . 北京 : 中国标准出版社 , 2010 .

National Standardization Administration Committee . Test methods for lateral stability of heavy commercial vehicle trains and articulated buses for road vehicles:GB/T 25979-2010 [S ] . Beijing : China Standard Press , 2010 . (in Chinese)

国家标准化管理委员会 . 重型汽车操纵稳定性试验通用条件:GB/T 40499-2021 [S ] . 北京 : 中国标准出版社 , 2021 .

National Standardization Administration Committee . General conditions for handling stability test of heavy vehicles:GB/T 40499-2021 [S ] . Beijing : China Standard Press , 2021 . (in Chinese)

全国道路运输标准化技术委员会 . 营运车辆抗侧翻稳定性试验方法,稳态圆周试验:JT/T 884-2014 [S ] . 北京 : 中国标准出版社 , 2014 .

National Road Transportation Standardisation Technical Committee . Test method for rollover stability of operating vehicles,steady state circumferential test:JT/T 884-2014 [S ] . Beijing : China Standard Press , 2014 . (in Chinese)

WANG W X , ZHANG Y H , GAO J X , et al . GOPS:a general optimal control problem solver for autonomous driving and industrial control applications [J ] . Communications in Transportation Research , 2023 , 3 : 100096 .