Optimal Predictive Control for Path Following of a Full Drive -by-Wire Vehicle at Varying Speeds

• Published in: Chinese journal of mechanical engineering 2017-05, Vol.30 (3), p.711-721
• Main Authors: SONG, Pan, GAO, Bolin, XIE, Shugang, FANG, Rui
• Format: Article
• Language: English
• Subjects: Acceleration; Algorithms; Braking; Chassis; Collision avoidance; Computer simulation; Control algorithms; Control theory; Controllers; Drive by wire; Electrical Machines and Networks; Electronics and Microelectronics; Engineering; Engineering Thermodynamics; Heat and Mass Transfer; Instrumentation; Lane changing; Lane keeping; Machines; Manufacturing; Mechanical Engineering; Motion control; Nonlinear control; Original Article; Power Electronics; Predictive control; Processes; Sideslip; Sliding mode control; Steering; Structural hierarchy; Theoretical and Applied Mechanics; Tracking errors; Traffic speed; Trajectory planning; 半实物仿真系统; 最优预测控制; 线控转向; 路径跟踪; 车辆速度; 运动控制器; 非线性模型预测控制; 驱动模型
• ISSN: 1000-9345; 2192-8258
• DOI: 10.1007/s10033-017-0103-7

The current research of the global chassis control problem for the full drive-by-wire vehicle focuses on the control allocation （CA） of the four-wheel-distributed trac- tion/braking/steering systems. However, the path following performance and the handling stability of the vehicle can be enhanced a step further by automatically adjusting the vehicle speed to the optimal value. The optimal solution for the combined longitudinal and lateral motion control （MC） problem is given. First, a new variable step-size spatial transformation method is proposed and utilized in the prediction model to derive the dynamics of the vehicle with respect to the road, such that the tracking errors can be explicitly obtained over the prediction horizon at varying speeds. Second, a nonlinear model predictive con- trol （NMPC） algorithm is introduced to handle the non- linear coupling between any two directions of the vehicular planar motion and computes the sequence of the optimal motion states for following the desired path. Third, a hierarchical control structure is proposed to separate the motion controller into a NMPC based path planner and a terminal sliding mode control （TSMC） based path fol- lower. As revealed through off-line simulations, the hier- archical methodology brings nearly 1700% improvement in computational efficiency without loss of control per- formance. Finally, the control algorithm is verified through a hardware in-the-loop simulation system. Double-lane- change （DLC） test results show that by using the optimalpredictive controller, the root-mean-square （RMS） values of the lateral deviations and the orientation errors can be reduced by 41% and 30%, respectively, comparing to those by the optimal preview acceleration （OPA） driver model with the non-preview speed-tracking method. Additionally, the average vehicle speed is increased by 0.26 km/h with the peak sideslip angle suppressed to 1.9~. This research proposes a novel motion controller, which provides the full drive-by-wire vehicle with better lane-keeping and colli- sion-avoidance capabilities during autonomous driving.