Robust Model Predictive Control Based on Active Disturbance Rejection Control for a Robotic Autonomous Underwater Vehicle

This work aims to develop a robust model predictive control (MPC) based on the active disturbance rejection control (ADRC) approach by using a discrete extended disturbance observer (ESO). The proposed technique uses the ADRC approach to lump disturbances and uncertainties into a total disturbance,...

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Main Authors: Jaime Arcos-Legarda, Álvaro Gutiérrez
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Journal of Marine Science and Engineering
Subjects:
Online Access:https://www.mdpi.com/2077-1312/11/5/929
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author Jaime Arcos-Legarda
Álvaro Gutiérrez
author_facet Jaime Arcos-Legarda
Álvaro Gutiérrez
author_sort Jaime Arcos-Legarda
collection DOAJ
description This work aims to develop a robust model predictive control (MPC) based on the active disturbance rejection control (ADRC) approach by using a discrete extended disturbance observer (ESO). The proposed technique uses the ADRC approach to lump disturbances and uncertainties into a total disturbance, which is estimated with a discrete ESO and rejected through feedback control. Thus, the effects of the disturbances are attenuated, and a model predictive control is designed based on a canonical model free of uncertainties and disturbances. The proposed control technique is tested through simulation into a robotic autonomous underwater vehicle (AUV). The AUV’s dynamic model is used to compare the performance of a classical MPC and the combined MPC-ADRC. The evaluation results show evidence of the superiority of the MPC-ADRC over the classical MPC under tests of reference tracking, external disturbances rejection, and model uncertainties attenuation.
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spelling doaj.art-b220645397a0403c9a579d83fbed305a2023-11-18T01:58:38ZengMDPI AGJournal of Marine Science and Engineering2077-13122023-04-0111592910.3390/jmse11050929Robust Model Predictive Control Based on Active Disturbance Rejection Control for a Robotic Autonomous Underwater VehicleJaime Arcos-Legarda0Álvaro Gutiérrez1Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, 28040 Madrid, SpainEscuela Técnica Superior de Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, 28040 Madrid, SpainThis work aims to develop a robust model predictive control (MPC) based on the active disturbance rejection control (ADRC) approach by using a discrete extended disturbance observer (ESO). The proposed technique uses the ADRC approach to lump disturbances and uncertainties into a total disturbance, which is estimated with a discrete ESO and rejected through feedback control. Thus, the effects of the disturbances are attenuated, and a model predictive control is designed based on a canonical model free of uncertainties and disturbances. The proposed control technique is tested through simulation into a robotic autonomous underwater vehicle (AUV). The AUV’s dynamic model is used to compare the performance of a classical MPC and the combined MPC-ADRC. The evaluation results show evidence of the superiority of the MPC-ADRC over the classical MPC under tests of reference tracking, external disturbances rejection, and model uncertainties attenuation.https://www.mdpi.com/2077-1312/11/5/929model predictive controlactive disturbance rejection controlextended state observerautonomous underwater vehiclesunderwater robotics
spellingShingle Jaime Arcos-Legarda
Álvaro Gutiérrez
Robust Model Predictive Control Based on Active Disturbance Rejection Control for a Robotic Autonomous Underwater Vehicle
Journal of Marine Science and Engineering
model predictive control
active disturbance rejection control
extended state observer
autonomous underwater vehicles
underwater robotics
title Robust Model Predictive Control Based on Active Disturbance Rejection Control for a Robotic Autonomous Underwater Vehicle
title_full Robust Model Predictive Control Based on Active Disturbance Rejection Control for a Robotic Autonomous Underwater Vehicle
title_fullStr Robust Model Predictive Control Based on Active Disturbance Rejection Control for a Robotic Autonomous Underwater Vehicle
title_full_unstemmed Robust Model Predictive Control Based on Active Disturbance Rejection Control for a Robotic Autonomous Underwater Vehicle
title_short Robust Model Predictive Control Based on Active Disturbance Rejection Control for a Robotic Autonomous Underwater Vehicle
title_sort robust model predictive control based on active disturbance rejection control for a robotic autonomous underwater vehicle
topic model predictive control
active disturbance rejection control
extended state observer
autonomous underwater vehicles
underwater robotics
url https://www.mdpi.com/2077-1312/11/5/929
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AT alvarogutierrez robustmodelpredictivecontrolbasedonactivedisturbancerejectioncontrolforaroboticautonomousunderwatervehicle