Hierarchical Control Strategy of Trajectory Tracking for Intelligent Vehicle

doi:10.1007/s12204-017-1825-5

Abstract

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

摘要： 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.

关键词: trajectory tracking control| model predictive control (MPC)| linear parameter varying (LPV)| gainscheduling control

CLC Number:

TP 273

ZHANG Qian* (张茜), LIU Zhiyuan (刘志远). Hierarchical Control Strategy of Trajectory Tracking for Intelligent Vehicle[J]. Journal of shanghai Jiaotong University (Science), 2017, 22(2): 224-232.

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