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

Open Access
|Oct 2019

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.

DOI: https://doi.org/10.2478/pomr-2019-0057 | Journal eISSN: 2083-7429 | Journal ISSN: 1233-2585
Language: English
Page range: 163 - 171
Published on: Oct 18, 2019
Published by: Gdansk University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 times per year

© 2019 Hossein Nejatbakhsh Esfahani, Rafal Szlapczynski, published by Gdansk University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.