Abstract
This paper presents a data-driven model-based control system for autonomous underwater vehicles (or AUVs) subject to input delays. This work is motivated by the input time delays that can arise in underwater robotics due to communication restrictions and sensor malfunctions. Such delays can highly degrade the performance of classical control structures resulting in unpredictable system behaviours. The proposed control architecture addresses such limitations. The approach incorporates a linear dynamic representation of the system obtained using the Koopman operator in an observer/state prediction formulation. The proposed control architecture is designed based on discrepancies between the data-driven estimation of the system's behaviour and the actual AUV performance using chain predictors. The capabilities of the proposed approach are shown through experiments performed with a 4 degrees-of-freedom autonomous underwater vehicle. The results demonstrate stable behaviours without steady-state errors, even in the presence of long delay.
Original language | English |
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Pages (from-to) | 71287-71300 |
Number of pages | 14 |
Journal | IEEE Access |
Volume | 11 |
Early online date | 7 Jul 2023 |
DOIs | |
Publication status | Published - 2023 |
Keywords
- Autonomous underwater vehicles
- Koopman operator
- control theory
- model based control
- observer-based predictors
ASJC Scopus subject areas
- General Computer Science
- General Materials Science
- General Engineering