Real-Time Reconfiguration and Connectivity Maintenance for AUVs Network Under External Disturbances using Distributed Nonlinear Model Predictive Control
Advancements in underwater vehicle technology have significantly expanded the potential scope for deploying autonomous or remotely operated underwater vehicles in novel practical applications. However, the efficiency and maneuverability of these vehicles remain critical challenges, particularly in the dynamic aquatic environment. In this work, we propose a novel control scheme for creating multi-agent distributed formation control with limited communication between individual agents. In addition, the formation of the multi-agent can be reconfigured in real-time and the network connectivity can be maintained. The proposed use case for this scheme includes creating underwater mobile communication networks that can adapt to environmental or network conditions to maintain the quality of communication links for long-range exploration, seabed monitoring, or underwater infrastructure inspection. This work introduces a novel Distributed Nonlinear Model Predictive Control (DNMPC) strategy, integrating Control Lyapunov Functions (CLF) and Control Barrier Functions (CBF) with a relaxed decay rate, specifically tailored for 6-DOF underwater robotics. The effectiveness of our proposed DNMPC scheme was demonstrated through rigorous MATLAB simulations for trajectory tracking and formation reconfiguration in a dynamic environment. Our findings, supported by tests conducted using Software In The Loop (SITL) simulation, confirm the approach's applicability in real-time scenarios.
Code (0)
등록된 구현이 없습니다.
Tasks
Model Predictive ControlSimilar Papers 제목 키워드 기반
NemeSys: Toward Online Underwater Exploration with Remote Operator-in-the-loop Adaptive Autonomy
Adaptive mission control and dynamic parameter reconfiguration are essential for autonomous underwater vehicles (AUVs) operating in GPS-denied, communication-limited marine environments. However, AUV platforms generally …
Physics-Informed Graph Neural Network for Dynamic Reconfiguration of Power Systems
To maintain a reliable grid we need fast decision-making algorithms for complex problems like Dynamic Reconfiguration (DyR). DyR optimizes distribution grid switch settings in real-time to minimize grid losses and dispat…
Decision MakingGraph Neural NetworkLOTUSim-Energy: A Maritime Simulator for Human-Drone Interaction in Autonomous Offshore Operation \& Maintenance
Offshore maintenance requires operations in the air, the surface, and the subsea domain and include human supervision. This paper presents LOTUSim-Energy, a real-time maritime simulator designed for multi-domain human--d…
Connectivity Maintenance: Global and Optimized approach through Control Barrier Functions
Connectivity maintenance is an essential aspect to consider while controlling a multi-robot system. In general, a multi-robot system should be connected to obtain a certain common objective. Connectivity must be kept reg…
Connectivity Maintenance and Recovery for Multi-Robot Motion Planning
Connectivity is crucial in many multi-robot applications, yet balancing connectivity maintenance and fleet traversability in obstacle-rich environments remains challenging. Reactive controllers based on control barrier f…
Motion Planning