Decoupling Control of Longitudinal and Lateral Motion for Intelligent Vehicle Based on Neural Network Inverse Method

LIANG Yixiao, LI Yinong, YU Yinghong, ZHENG Ling

Abstract

Aiming at the coupling phenomenon of longitudinal and lateral motions for automobile, autonomous vehicle with Four-wheel-driving and front-wheel-steering was set as the subject investigated. A dynamic model which reflects the longitudinal and lateral motion of vehicle was established and the reversibility of this model was analyzed by the interactor algorithm. On the basis of the existing classical structure of pseudo-linear system, the pseudo linear composition system with the ability to fit the upper level planning system of intelligent vehicle was established according to the characteristic of intelligent vehicle. In order to realize the decoupling of longitudinal and lateral motions for vehicle, an approach based on network inverse method was proposed as the decoupling control strategy in this paper, which can be combined with the internal model controller to form closed loop structure and it can significantly improve the performance of the plant by feedback and adjust the longitudinal speed and yaw rate of automobile. The simulation results validated the decoupling performance of the proposed approach. The results also showed that when compared with other control algorithms, the proposed approach can achieve good tracking performance of longitudinal speed and yaw rate under varieties of input condition. Further, the sideslip was constrained in a small range, which is beneficial to the path tracing accuracy and the stability of autonomous vehicle.

 

 

Keywords:  intelligent vehicle,  decoupling control of longitudinal and lateral motion,  neural networks,  inverse approach,  vehicle dynamics


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References


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