In this paper,Hu, Chaofang an iterative learning model predictive Zhao, Lingxue (ILMPC) strategy is introduced for Wang, Na trajectory tracking of Unmanned Ground Vehicle (UGV). First, a linear time-varying (LTV) system of UGV is derived from the simplified dynamic vehicle model of UGV by Taylors formula. Second, the constrained ILMPC controller is introduced to solve the trajectory tracking problem, which is described as a QP problem. Finally, a simulation about trajectory tracking of batch process is presented to show the effectiveness of the proposed controller.


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    Title :

    Trajectory Tracking of Unmanned Ground Vehicle Based on Iterative Learning Model Predictive Control


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Wang, Rui (editor) / Chen, Zengqiang (editor) / Zhang, Weicun (editor) / Zhu, Quanmin (editor) / Hu, Chaofang (author) / Zhao, Lingxue (author) / Wang, Na (author)


    Publication date :

    2019-12-04


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English






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