Path Following Predictive Control for Autonomous Vehicles Subject to Uncertain Tire-ground Adhesion and Varied Road Curvature
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This paper presents an integrated active steering control (ASC) and direct yaw control (DYC) strategy for improving path following performance of the vehicle subject to the uncertain tire-ground adhesion and road curvature conditions. To begin with, a model predictive control (MPC)-based path following controller is designed to deal with system state constraints and actuator actuation limitations. After that, a constrained weighted least square (CWLS)-based torque distributor is developed to distribute the target resultant yaw moment signal into the four executive wheels. Then, the developed control strategy and methods are implemented and evaluated on an eight degree of freedom (8DOF) nonlinear vehicle model include longitudinal, lateral, yaw, roll and four wheels’ rotation dynamics. In the end, simulation results compared with ASC strategy, under the uncertain tire-ground adhesion and varied road curvature cases, confirm the feasibility and efficiency of the presented strategy and methods even subject to the uncertain tire-ground adhesion and varied road curvature.
KeywordsAutonomous ground vehicle model predictive control path following uncertain road information
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- Z. J. Li, C. G. Yang, C. Y. Su, J. Deng, and W. D. Zhang, “Vision–based model predictive control for steering of a nonholonomic mobile robot,” IEEE Trans. on Control Systems Technology, vol. 24, no. 2, pp. 553–564, March 2016.Google Scholar
- C. G. Yang, T. Teng, B. Xu, Z. J. Li, J. Na, and C. Y. Su, “Global adaptive tracking control of robot manipulators using neural networks with finite–time learning convergence,” International Journal of Control, Automation and Systems, vol. 15, no. 4, pp. 1916–1924, August 2017.CrossRefGoogle Scholar