Hierarchical control strategy of trajectory tracking for intelligent vehicle

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Abstract

In order to track the desired trajectory for intelligent vehicle, a new hierarchical control strategy is presented. The control structure consists of two layers. The high-level controller adopts the model predictive control (MPC) to calculate the steering angle tracking the desired yaw angle and the lateral position. The low-level controller is designed as a gain-scheduling controller based on linear matrix inequalities. The desired longitudinal velocity and the yaw rate are tracked by the adjustment of each wheel torque. The simulation results via the high-fidelity vehicle dynamics simulation software veDYNA show that the proposed strategy has a good tracking performance and can guarantee the yaw stability of intelligent vehicle.

Key words

trajectory tracking control model predictive control (MPC) linear parameter varying (LPV) gainscheduling control 

CLC number

TP 273 

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References

  1. [1]
    GUO L, HUANG X H, GE P S, et al. Lane changing trajectory tracking control for intelligent vehicle on curved road based on backstepping [J]. Journal of Jilin University: Engineering and Technology Edition, 2013, 43(2): 323–328 (in Chinese).Google Scholar
  2. [2]
    YOU F, WANG R B, ZHANG R H, et al. Lane changing and overtaking control method for intelligent vehicle based on backstepping algorithm [J]. Transactions of the Chinese Society for Agricultural Machinery, 2008, 39(6): 42–45 (in Chinese).Google Scholar
  3. [3]
    RUAN J H, LI Y B, YANG F G, et al. Path tracking control of high-speed 4WID-4WIS autonomous vehicle [J]. Robot, 2011, 33(4): 411–418 (in Chinese).CrossRefGoogle Scholar
  4. [4]
    REN D B, ZHANG J Y, ZHANG J M, et al. Trajectory planning and yaw rate tracking control for lane changing of intelligent vehicle on curved road [J]. Science China Technology Science, 2011, 54(3): 630–642.MathSciNetCrossRefMATHGoogle Scholar
  5. [5]
    TAGNE G, TALJ R, CHARARA A. Design and validation of a robust immersion and invariance controller for the lateral dynamics of intelligent vehicles [J]. Control Engineering Practice, 2015, 40: 81–92.CrossRefGoogle Scholar
  6. [6]
    YAKUB F, MORI Y. Autonomous ground vehicle of path following control through model predictive control with feed forward controller [C]//Proceedings of the 12th International Symposium on Advanced Vehicle Control. Tokyo, Japan: Society of Automotive Engineers of Japan, 2014: 603–610.Google Scholar
  7. [7]
    YAKUB F, MORI Y. Enhancing path following control performance of autonomous ground vehicle through coordinated approach under disturbance effect [J]. IEEJ Transactions on Electronics, Information and Systems, 2014, 135(1): 102–110.CrossRefGoogle Scholar
  8. [8]
    SHIM T, ADIREDDY G, YUAN H L. Autonomous vehicle collision avoidance system using path planning and model-predictive-control-based active front steering and wheel torque control [J]. Proceedings of the Institution of Mechanical Engineers Part D: Journal of Automobile Engineering, 2012, 226(6): 767–778.Google Scholar
  9. [9]
    ATTIA R, ORJUELA R, BASSET M. Coupled longitudinal and lateral control strategy improving lateral stability for autonomous vehicle [C]//Proceedings of the American Control Conference. Montréal, Canada: IEEE, 2012: 6509–6514.Google Scholar
  10. [10]
    ATTIA R, ORJUELA R, BASSET M. Combined longitudinal and lateral control for automated vehicle guidance [J]. Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility, 2014, 52(2): 261–279.CrossRefGoogle Scholar
  11. [11]
    RAJAMANI R. Vehicle dynamics and control [M]. 2nd ed. New York, USA: Springer-Verlag, 2012.CrossRefMATHGoogle Scholar
  12. [12]
    CHEN H. Model predictive control [M]. Beijing, China: Science Press, 2013 (in Chinese).Google Scholar
  13. [13]
    YU Z S. Automobile theory [M]. 5th ed. Beijing, China: China Machine Press, 2009 (in Chinese).Google Scholar
  14. [14]
    OLALLA C, LEYVA R, AROUDI A E, et al. Robust LQR control for PWM converters: an LMI approach [J]. IEEE Transactions on Industrial Electronics, 2009, 56(7): 2548–2558.CrossRefGoogle Scholar
  15. [15]
    DUPONT F H, MONTAGNER V F, PINHEIRO J R. Comparison of linear quadratic controllers with stability analysis for DC-DC boost converters under large load range [J]. Asian Journal of Control, 2013. 15(3): 1–11.MathSciNetCrossRefMATHGoogle Scholar
  16. [16]
    HUANG X Y, ZHANG H, ZHANG G H, et al. Robust weighted gain-scheduling H vehicle lateral motion control with considerations of steering system backlash-type hysteresis [J]. IEEE Transactions on Control Systems Technology, 2014, 22(5): 1740–1753.CrossRefGoogle Scholar
  17. [17]
    DUAN G R. Linear matrix inequalities in control systems [M]. Boca Raton, USA: CRC Press Taylor & Francis Group, 2013.Google Scholar
  18. [18]
    GAO H J, YANG X B, SHI P. Multi-objective robust H control of spacecraft rendezvous [J]. IEEE Transactions on Control System Technology, 2009, 17(4): 794–802.CrossRefGoogle Scholar
  19. [19]
    YU Z P, JIANG W, ZHANG L J. Torque distribution control for four wheel in-wheel-motor electric vehicle [J]. Journal of Tongji University (Natural Science), 2008, 36(8): 1115–1119 (in Chinese).Google Scholar
  20. [20]
    ALMEIDA S, ARAúJO R E. Fault-tolerant control using sliding mode techniques applied to multi-motor electric vehicle [C]//Proceedings of IECON. Vienna, Austria: IEEE, 2013: 3530–3535.Google Scholar
  21. [21]
    KUTLUAY E, WINNER H. Assessment methodology for validation of vehicle dynamics simulations using double lane change maneuver [C]//Proceedings of the 2012 Winter Simulation Conference. Berlin, Germany: IEEE, 2012: 1–12.CrossRefGoogle Scholar

Copyright information

© Shanghai Jiaotong University and Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Department of Control Science and EngineeringHarbin Institute of TechnologyHarbinChina

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