International Journal of Control, Automation and Systems 2022; 20(7): 2178-2190
Published online June 9, 2022
https://doi.org/10.1007/s12555-021-0269-8
© The International Journal of Control, Automation, and Systems
This paper proposes a path-following controller and a torque allocation strategy for a four-wheelindependent-drive (FWID) electric autonomous ground vehicle (EAGV) on the slope roads. To improve the realtime accuracy of the controller, a model-predictive-control (MPC) controller with a linear-parameter-varying (LPV) model is proposed to maintain the vehicle dynamic stability and follow the given path for the EAGV. By updating the parameters of the states, the proposed controller can minimize the effects of the unequal normal tire forces and the gravity components of the vehicle on the slope road. As a result, the desired trajectory of the lateral position, longitudinal position, yaw angle, and velocity can be tracked by controlling the front-wheel-steering angle and the driving torque of each wheel. Finally, the high-fidelity simulations have been implemented on the CarSim-Matlab platform, and the results show that the proposed LPV-MPC controller with the torque allocation strategy is effective to achieve the control targets.
Keywords Autonomous vehicle, linear parameter varying (LPV), model predictive control (MPC), path following, slope terrain.
International Journal of Control, Automation and Systems 2022; 20(7): 2178-2190
Published online July 1, 2022 https://doi.org/10.1007/s12555-021-0269-8
Copyright © The International Journal of Control, Automation, and Systems.
Zhongchao Liang, Yidi Chen, and Jing Zhao*
Northeastern University
This paper proposes a path-following controller and a torque allocation strategy for a four-wheelindependent-drive (FWID) electric autonomous ground vehicle (EAGV) on the slope roads. To improve the realtime accuracy of the controller, a model-predictive-control (MPC) controller with a linear-parameter-varying (LPV) model is proposed to maintain the vehicle dynamic stability and follow the given path for the EAGV. By updating the parameters of the states, the proposed controller can minimize the effects of the unequal normal tire forces and the gravity components of the vehicle on the slope road. As a result, the desired trajectory of the lateral position, longitudinal position, yaw angle, and velocity can be tracked by controlling the front-wheel-steering angle and the driving torque of each wheel. Finally, the high-fidelity simulations have been implemented on the CarSim-Matlab platform, and the results show that the proposed LPV-MPC controller with the torque allocation strategy is effective to achieve the control targets.
Keywords: Autonomous vehicle, linear parameter varying (LPV), model predictive control (MPC), path following, slope terrain.
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