RL-based NMPC Control Development for AUV

I'm seeking an experienced professional to develop a Reinforcement Learning (RL) based Nonlinear Model Predictive Control (NMPC) system for 3D trajectory tracking by an Autonomous Underwater Vehicle (AUV). Key Responsibilities: - Implement an RL (PPO) system that receives reference and actual trajectories, alongside any necessary data. This system will produce refined reference trajectories, with penalties applied for differences and smoothness. - Integrate the refined reference trajectories into an NMPC to generate the required torque/force signal. Requirements: - Proficiency in Python is essential as this will be the primary programming language for the project. - Extensive experience in developing RL based control systems, particularly within the context of NMPC and AUVs. - Proven experience in trajectory tracking control. Please note, I need this project completed as soon as possible. Your application should highlight your relevant experience, particularly with similar projects. The ability to deliver high quality work under tight timelines will be crucial.