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

    Download


    Export, share and cite



    Title :

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




    Publication date :

    2019




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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

    Esfahani, Hossein Nejatbakhsh / Szlapczynski, Rafal | Online Contents | 2019


    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