Abstract This paper presents a new robust Model Predictive Control (MPC) algorithm for trajectory tracking of an Autonomous Surface Vehicle (ASV) in presence of the time-varying external disturbances including winds, waves and ocean currents as well as dynamical uncertainties. For fulfilling the robustness property, a sliding mode control-based procedure for designing of MPC and a super-twisting term are adopted. The MPC algorithm has been known as an effective approach for the implementation simplicity and its fast dynamic response. The proposed hybrid controller has been implemented in MATLAB / Simulink environment. The results for the combined Model Predictive Super-Twisting Sliding Mode Control (MP-STSMC) algorithm have shown that it significantly outperforms conventional MPC algorithm in terms of the transient response, robustness and steady state response and presents an effective chattering attenuation in comparison with the Super-Twisting Sliding Mode Control (STSMC) algorithm.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Model Predictive Super-Twisting Sliding Mode Control for an Autonomous Surface Vehicle



    Published in:

    Polish Maritime Research ; 26 , 3 ; 163-171


    Publication date :

    2019




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    Unknown


    Classification :

    BKL:    55.40 Schiffstechnik, Schiffbau / 50.92 Meerestechnik



    Model Predictive Super-Twisting Sliding Mode Control for an Autonomous Surface Vehicle

    Esfahani Hossein Nejatbakhsh / Szlapczynski Rafal | DOAJ | 2019

    Free access

    A Fuzzy Super Twisting Sliding Mode Control Scheme for Velocity Regulation in Autonomous Vehicles

    Bala, Jibril Abdullahi / Sadiq, Thomas / Aibinu, Abiodun Musa et al. | IEEE | 2021


    Vehicle Adaptive Cruise Controller Based on an Optimal Super-twisting Sliding Mode Control

    El Hajjami, Lhoussain / Mellouli, El Mehdi / Zuraulis, Vidas et al. | IEEE | 2022