Trajectory tracking is currently one of the hot topics in the automotive field and has significant importance. Trajectory tracking mainly refers to the consistency between the path traveled within a specified time and a predetermined reference path. It is necessary to ensure that the mobile vehicle with no collisions and less time consumption during this time. The current track tracking method is caused by slow tracking or poor stability. In view of the above situation, this article designed a PD type Iterative Learning Control (ILC) algorithm for trajectory tracking, comparing it with D type Iterative Learning Control. When the trajectory of the mobile vehicle is tracked, it encounters obstacles or slow tracking speeds, it can also be adjusted quickly through system stability.


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    Title :

    Trajectory-tracking for mobile vehicle based on PD-type iterative learning control with disturbance


    Contributors:
    Lei, Tao (editor) / Chen, Lei (editor) / Ding, Hao (author) / Song, Lu (author) / Dou, Jinbiao (author) / Xu, Bohan (author) / Li, Liyan (author) / He, Wenchao (author) / Luo, Xiaoxia (author) / Ma, Tianru (author) ... [more]

    Conference:

    International Conference on Signal Processing and Neural Network Applications (SPNNA 2024) ; 2024 ; Wuhan, China


    Published in:

    Proc. SPIE ; 13652 ; 1365204


    Publication date :

    2025-06-11





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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