This paper proposes a model predictive control (MPC)-based trajectory tracking controller with active disturbance rejection control (ADRC) feedback to reduce the lateral tracking errors of autonomous vehicles caused by simplified kinematic models. The controller employs MPC for feedforward optimization and ADRC for negative feedback regulation. In the designed ADRC controller, the reference steering angle output from MPC replaces the smoothing signal generated by the tracking differentiator (TD), eliminating the TD while retaining the first-order extended state observer (ESO). In addition, a linear state error feedback (LSEF) control law is adopted to replace the nonlinear state error feedback (NLSEF) control law, which simplifies the ADRC structure and parameter tuning while preserving its disturbance compensation capability. Simulink/CarSim co-simulations on circular and sinusoidal trajectories at 3–10 m/s show that, compared with conventional MPC, the proposed MPC-ADRC controller reduces the mean lateral error by 10.6%–13.4% on circular paths and 8.7%–23.5% on sinusoidal paths; compared with an MPC-PID composite controller, the reductions are 6.1%–9.3% and 3.1%–14.8%, respectively, without compromising steering smoothness or ride comfort. Monte Carlo tests with heading-angle noise and speed fluctuations confirm that MPC-ADRC achieves the smallest mean lateral error under random disturbances, demonstrating robustness and real-time applicability.
KatrakazasCQuddusMChenWH, et al. Real-time motion planning methods for autonomous on-road driving: state-of-the-art and future research directions. Transp Res Part C Emerg Technol2015; 60: 416–442. https://doi.org/10.1016/j.trc.2015.09.011
2.
DixitSFallahSMontanaroU, et al. Trajectory planning and tracking for autonomous overtaking: state-of-the-art and future prospects. Annu Rev Control2018; 45: 76–86. https://doi.org/10.1016/j.arcontrol.2018.02.001
3.
YaoQTianYWangQ, et al. Control strategies on path tracking for autonomous vehicle: state of the art and future challenges. IEEE Access2020; 8: 161211–161222. https://doi.org/10.1109/ACCESS.2020.3020075
4.
ZhouHJiaFJingH, et al. Coordinated longitudinal and lateral motion control for four wheel independent motor-drive electric vehicle. IEEE Trans Veh Technol2018; 67(5): 3782–3790. https://doi.org/10.1109/tvt.2018.2816936
5.
YinCWangSLiX, et al. Trajectory tracking based on adaptive sliding mode control for agricultural tractor. IEEE Access2020; 8: 113021–113029. https://doi.org/10.1109/access.2020.3002814
6.
AwadNLasheenAElnaggarM, et al. Model predictive control with fuzzy logic switching for path tracking of autonomous vehicles. ISA Trans2022; 129: 193–205. https://doi.org/10.1016/j.isatra.2021.12.022
7.
WuTSKarkoubMWengCC, et al. Trajectory tracking for uncertainty time delayed-state self-balancing train vehicles using observer-based adaptive fuzzy control. Inf Sci2015; 324: 1–22. https://doi.org/10.1016/j.ins.2015.06.019
CuiQDingRZhouB, et al. Path-tracking of an autonomous vehicle via model predictive control and nonlinear filtering. Proc Inst Mech Eng Part D: J Automob Eng2018; 232(9): 1237–1252. https://doi.org/10.1177/0954407017728199
10.
ZhangCChuDLiuS, et al. Trajectory planning and tracking for autonomous vehicle based on state lattice and model predictive control. IEEE Intell Transp Syst Mag2019; 11(2): 29–40. https://doi.org/10.1109/mits.2019.2903536
11.
HuJXiongSZhaJ, et al. Lane detection and trajectory tracking control of autonomous vehicle based on model predictive control. Int J Automot Technol2020; 21(2): 285–295. https://doi.org/10.1007/s12239-020-0027-6
FalconePBorrelliFAsgariJ, et al. Predictive active steering control for autonomous vehicle systems. IEEE Trans Control Syst Technol2007; 15(3): 566–580. https://doi.org/10.1109/TCST.2007.894653
14.
LiuJJayakumarPSteinJL, et al. A nonlinear model predictive control formulation for obstacle avoidance in high-speed autonomous ground vehicles in unstructured environments. Veh Syst Dyn2018; 56(6): 853–882. https://doi.org/10.1080/00423114.2017.1399209
15.
GuoJLuoYLiK, et al. Coordinated path-following and direct yaw-moment control of autonomous electric vehicles with sideslip angle estimation. Mech Syst Signal Process2018; 105: 183–199. https://doi.org/10.1016/j.ymssp.2017.12.018
16.
ChenWHYangJGuoL, et al. Disturbance-observer-based control and related methods—an overview. IEEE Trans Ind Electron2016; 63(2): 1083–1095. https://doi.org/10.1109/TIE.2015.2478397
17.
WangRJingHHuC, et al. Robust path following control for autonomous ground vehicles with delay and data dropout. IEEE Trans Intell Transp Syst2016; 17(7): 2042–2050. https://doi.org/10.1109/TITS.2015.2498157
18.
HanJ. Active disturbance rejection control technology: control technique for estimating and compensating uncertainties. National Defense Industry Press, 2008.
XiaYPuFLiS, et al. Lateral path tracking control of autonomous land vehicle based on ADRC and differential flatness. IEEE Trans Ind Electron2016; 63(5): 3091–3099. https://doi.org/10.1109/TIE.2016.2531021
23.
JiJKhajepourAMelekWW, et al. Path planning and tracking for vehicle collision avoidance based on model predictive control with multiconstraints. IEEE Trans Veh Technol2016; 66(2): 952–964. https://doi.org/10.1109/tvt.2016.2555853
24.
ChengSLiLGuoHQ, et al. Longitudinal collision avoidance and lateral stability adaptive control system based on MPC of autonomous vehicles. IEEE Trans Intell Transp Syst2019; 21(6): 2376–2385. https://doi.org/10.1109/tits.2019.2918176
25.
RokonuzzamanMMohajerNNahavandiS, et al. Model predictive control with learned vehicle dynamics for autonomous vehicle path tracking. IEEE Access2021; 9: 128233–128249. https://doi.org/10.1109/access.2021.3112560
26.
ChoiYLeeWKimJ, et al. A variable-sampling time model predictive control algorithm for improving path-tracking performance of a vehicle. Sensors2021; 21(20): 6845. https://doi.org/10.3390/s21206845
27.
ChuDLiHZhaoC, et al. Trajectory tracking of autonomous vehicle based on model predictive control with PID feedback. IEEE Trans Intell Transp Syst2022; 24(2): 2239–2250. https://doi.org/10.1109/tits.2022.3150365
28.
YangCLiuJ. Trajectory tracking control of intelligent driving vehicles based on MPC and fuzzy PID. Math Probl Eng2023; 2023(1): 2464254. https://doi.org/10.1155/2023/2464254
LiuRWeiMSangN. Emergency obstacle avoidance trajectory tracking control based on active disturbance rejection for autonomous vehicles. Int J Adv Robot Syst2020; 17(3): 1729881420921105. https://doi.org/10.1177/1729881420921105
31.
LiZZhangZWangJ, et al. ADRC control system of PMLSM based on novel non-singular terminal sliding mode observer. Energies2022; 15(10): 3720. https://doi.org/10.3390/en15103720
