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Lateral Motion Control of Intelligent Vehicle Based on Combination of Super-twisting Sliding Mode and Feedforward Compensation Algorithms
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    Abstract:

    Intelligent vehicle path tracking control is faced with interferences such as vehicle parameter perturbation and scene variability, which affects the accuracy of path tracking, and even causes the control system instability. In this paper, a second-order super-twisting sliding mode robust control algorithm considering uncertainty is designed, the convergence of control system is proved, and a feedforward compensation controller is designed for interference problems to further improve the accuracy of the control system. Then, to validate the accuracy and robustness of the proposed robust control algorithm, several cases including double-lane change, sine path, as well as parameter perturbation scenes, are simulated under the Carsim-Matlab/Simulink co-simulation environment, and the traditional first-order sliding mode control is selected as a comparison . The results show that, the proposed super-twisting sliding mode algorithm has better robustness and tracking accuracy than the traditional sliding mode algorithm when considering the above interferences. Meanwhile, the proposed super-twisting algorithm can effectively reduce the steering wheel buffeting problem which exists in the traditional sliding mode algorithm. Finally, the large curvature scene travelling at low speed is tested on the real vehicle platform to verify the more accurate path-tracking effect of the designed super-twisting sliding mode algorithm.

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  • Received:
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  • Online: March 21,2024
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