Trajectory tracking control for intelligent vehicles driving in curved road based on expanded state observers

doi:10.3969/j.issn.1674-8484.2022.01.011

Abstract

Abstract:

A model prediction multi-objective optimal control method was proposed based on extended state observer for tracking control of intelligent vehicles driving on complex curved roads to improve tracking accuracy and driving stability. To prove the observer’ stability, the extended state observer was used to estimate the total disturbance of vehicle tracking in real time. Combined with model predictive control, the multi-objective optimization effect was realized in prediction domain, and the estimated disturbance value was used to compensate feedforward for the control quantity, and the optimal control quantity was obtained under dynamic disturbance. The results show that the lateral location root mean square error is less than 0.11 m, the maximum front wheel angle is less than 85 mrad, and the maximum yaw speed is less than 368 mrad under different vehicle speeds and different road adhesion coefficients. Therefore, this method has good tracking accuracy, driving stability and robustness when driving on complex road curves.

Key words: intelligent vehicles, driving in curved road, trajectory tracking, extended state observer, model predictive control

CLC Number:

U461.99

ZHAO Shuen, CHEN Wenbin, DENG Zhaoxue, LIU Wei. Trajectory tracking control for intelligent vehicles driving in curved road based on expanded state observers[J]. Journal of Automotive Safety and Energy, 2022, 13(1): 112-121.

Figures/Tables 8

References 20

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