Online Approximate Optimal Station Keeping of an Autonomous Underwater Vehicle

2013/09/30 by Walters, Patrick, Dixon, Warren E.
#FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Optimization and Control (math.OC) #Robotics (cs.RO) #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · doi:10.48550/arxiv.1310.0063

Abstract

Online approximation of an optimal station keeping strategy for a fully actuated six degrees-of-freedom autonomous underwater vehicle is considered. The developed controller is an approximation of the solution to a two player zero-sum game where the controller is the minimizing player and an external disturbance is the maximizing player. The solution is approximated using a reinforcement learning-based actor-critic framework. The result guarantees uniformly ultimately bounded (UUB) convergence of the states and UUB convergence of the approximated policies to the optimal polices without the requirement of persistence of excitation.

Related

• Proportional integral derivative controller assisted reinforcement learning for path following by autonomous underwater vehicles
• Deep Reinforcement Learning for Continuous Docking Control of Autonomous Underwater Vehicles: A Benchmarking Study
• Autonomous Satellite Docking via Adaptive Optimal Output Regulation: A Reinforcement Learning Approach
• Ocean Diviner: A Diffusion-Augmented Reinforcement Learning Framework for AUV Robust Control in Underwater Tasks
• When Motion Learns to Listen: Diffusion-Prior Lyapunov Actor-Critic Framework with LLM Guidance for Stable and Robust AUV Control in Underwater Tasks