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Scientific Literature Dataset for:Tube-Based Deep Koopman Model Predictive Control for PlanarTrajectory Tracking of Autonomous Underwater Vehicles
Research Abstract & Technology Focus
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Trajectory Tracking Control of Autonomous Underwater Vehicles Using GP-Based Model Predictive Control
In this paper, a Gaussian process-based model predictive control (GP-MPC) method is proposed, which aims to enhance the trajectory tracking performance of autonomous underwater vehicles (AUVs). Thi...
Adaptive Data-Driven Control of Autonomous Underwater Vehicles: Bridging the Gap Between Simulation and Experimental Baseline via LSTM-MPC
This study proposes a robust data-driven control framework, LSTM-MPC, designed to enhance the velocity stabilization of Autonomous Underwater Vehicles (AUVs) operating under stochastic marine distu...
Three-Dimensional Near-Seabed Path Planning for Autonomous Underwater Vehicles Using Fisher Information and Slope–Curvature–Yaw-Rate Constraints
Autonomous underwater vehicles (AUVs) operating near the seabed must maintain localization reliability while satisfying maneuverability and bottom-clearance constraints. This study proposes a three...
Adaptive Fixed-Time Sliding Mode Tracking Control of Underactuated AUVs with Flexible Prescribed Performance
This paper proposes a fixed-time nonsingular terminal sliding mode control (FXTNTSMC) method for underactuated autonomous underwater vehicles (AUVs) under uncertain dynamics and flexible prescribed...
Instantaneous Planning, Control and Safety for Navigation in Unknown Underwater Spaces
Navigating autonomous underwater vehicles (AUVs) in unknown environments is significantly challenging due to poor visibility, weak signal transmission, and dynamic water currents. These factors pos...
Frequently Asked Questions (FAQ)
Curated market intelligence mapped to this research.
What is the core focus of the research titled 'Dataset for:Tube-Based Deep Koopman Model Predictive Control for PlanarTrajectory Tracking of Autonomous Underwater Vehicles'?
This literature focuses on: This dataset consists of trajectory, state, and control input data generated from a MATLAB-based mathematical model of an underwater robot. The data are used for training the Deep Koopman model proposed in this study and are organized in the train...
What other academic literature is closely related to 'Dataset for:Tube-Based Deep Koopman Model Predictive Control for PlanarTrajectory Tracking of Autonomous Underwater Vehicles'?
Yes, highly correlated activity was mapped. An entry titled 'Trajectory Tracking Control of Autonomous Underwater Vehicles Using GP-Based Model Predictive Control' discusses this: In this paper, a Gaussian process-based model predictive control (GP-MPC) method is proposed, which aims to enhance the trajectory tracking perform...
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