This paper introduces and presents model predictive control approach based on Kautz function algorithm for path following control in autonomous car vehicle system. Predictive control is designed based on linearized vehicle and tire model, while the real vehicle is included a roll dynamic motion. The controller based on Kautz functions is compared with conventional method which is called Delta function in order to follow the desired trajectory while rejecting the crosswind. The vehicle is performed at constant middle forward speed maneuver for double lane change scenario through simulation. The result shows the predictive control based on Kautz function give a better tracking performance than conventional method, but has more complexes in term of algorithm implementation. It also demonstrates that Kautz function has a potential to eliminate the unmeasured disturbance or crosswind effect and it significantly improves the vehicle stability, and the trajectory along the desired path.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Model predictive control based on Kautz function for autonomous ground vehicle path following control application


    Contributors:


    Publication date :

    2014-09-01


    Size :

    275687 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Model predictive control of resonant systems using Kautz model

    Misra, S. / Reddy, R. / Saha, P. | British Library Online Contents | 2016


    Path Following Control of Autonomous Underwater Vehicle Using Nonlinear Model Predictive Control

    Taniguohi, Tomoki / Umeda, Jun / Fujiwara, Toshifumi et al. | British Library Conference Proceedings | 2020


    Model Predictive Control for Autonomous Vehicle Following

    Bienemann, Alexander / Wuensche, Hans-Joachim | IEEE | 2023