Abstract
The trajectory tracking control strategy for intelligent vehicle is proposed in this article. Considering the parameters perturbations and external disturbances of the vehicle system, based on the vehicle dynamics and the preview follower theory, the lateral preview deviation dynamics model of the vehicle system is established which uses lateral preview position deviation, lateral preview velocity deviation, lateral preview attitude angle deviation, and lateral preview attitude angle velocity deviation as the tracking state variables. For this uncertain system, the adaptive sliding mode control algorithm is adopted to design the preview controller to eliminate the effects of uncertainties and realize high accuracy of the target trajectory tracking. According to the real-time deviations of lateral position and lateral attitude angle, the feedback controller is designed based on the fuzzy control algorithm. For improving the adaptability to the multiple dynamic states, the extension theory is introduced to design the coordination controller to adjusting the control proportions of the preview controller and the feedback controller to the front wheel steering angle. Simulation results verify the adaptability, robustness, accuracy of the control strategy under which the intelligent vehicle has good handling stability.
Highlights
Traffic congestion, frequent accidents, environmental pollution, and energy waste become more and more serious with the swift growth of traffic volume and vehicle ownership
The main contributions are summarized as follows: the lateral preview deviation dynamics model of the vehicle system is established involving the parameters perturbations and external disturbances of the system; according to the tracking state variables, the preview control method based on the adaptive sliding mode control (ASMC) algorithm is proposed to realize strong robustness and adaptability of the trajectory tracking control to uncertainties; the coordination control method is proposed to adjust the proportions of the preview controller and the feedback controller to the front wheel steering angle in order to improve the adaptability to multiple dynamic states
The results of the simulation test verify that ASMC preview controller has strong adaptivity and robustness, and can make intelligent vehicle accurately, rapidly, and stably travel into and along the straight target trajectory and have good handling stability
Summary
Frequent accidents, environmental pollution, and energy waste become more and more serious with the swift growth of traffic volume and vehicle ownership. The main contributions are summarized as follows: the lateral preview deviation dynamics model of the vehicle system is established involving the parameters perturbations and external disturbances of the system; according to the tracking state variables, the preview control method based on the adaptive sliding mode control (ASMC) algorithm is proposed to realize strong robustness and adaptability of the trajectory tracking control to uncertainties; the coordination control method is proposed to adjust the proportions of the preview controller and the feedback controller to the front wheel steering angle in order to improve the adaptability to multiple dynamic states.
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