Hu, Y.; Li, B.; Jiang, B.; Han, J.; Wen, C.-Y. Disturbance Observer-Based Model Predictive Control for an Unmanned Underwater Vehicle. J. Mar. Sci. Eng. 2024, 12, 94. https://doi.org/10.3390/jmse12010094
Hu, Y.; Li, B.; Jiang, B.; Han, J.; Wen, C.-Y. Disturbance Observer-Based Model Predictive Control for an Unmanned Underwater Vehicle. J. Mar. Sci. Eng. 2024, 12, 94. https://doi.org/10.3390/jmse12010094
Hu, Y.; Li, B.; Jiang, B.; Han, J.; Wen, C.-Y. Disturbance Observer-Based Model Predictive Control for an Unmanned Underwater Vehicle. J. Mar. Sci. Eng. 2024, 12, 94. https://doi.org/10.3390/jmse12010094
Hu, Y.; Li, B.; Jiang, B.; Han, J.; Wen, C.-Y. Disturbance Observer-Based Model Predictive Control for an Unmanned Underwater Vehicle. J. Mar. Sci. Eng. 2024, 12, 94. https://doi.org/10.3390/jmse12010094
Abstract
This work focuses on addressing the dynamic positioning and trajectory tracking problem for a 4 degree-of-freedom (DOF) unmanned underwater vehicle (UUV) in the presence of nonlinear dynamics, parametric uncertainties, system constraints, and time-varying external disturbances. To tackle this problem, a disturbance observer-based control (DOBC) scheme is proposed. The scheme is structured around the model predictive control (MPC) method integrated with an extended active observer (EAOB). Compared to the conventional disturbance observer, the EAOB has the unique ability to handle both external disturbances and system/measurement noises simultaneously. The EAOB leverages a combination of sensor measurements and a system dynamic model to estimate disturbances in real-time, which allows continuous estimation and compensation of time-varying disturbances back to the controller. The proposed disturbance observer-based MPC (DOBMPC) is implemented by feeding the estimated disturbances back into the MPC’s prediction model, which forms a robust adaptive controller with a parameter-varying model. The proposed control strategy is validated through simulations in a Gazebo and Robot Operating System (ROS) environment. The results show that it can effectively reject unpredictable disturbances and improve the UUV’s control performance.
Keywords
disturbance observer; model predictive control (MPC); dynamic positioning; trajectory tracking; unmanned underwater vehicle (UUV)
Subject
Engineering, Control and Systems Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
