AlinaBaber / ReinforcementLearning-QLearning-based-self-tuned-PID-controller-for-AUV-MatLab

This repository showcases a hybrid control system combining Reinforcement Learning (Q-Learning) and Neural-Fuzzy Systems to dynamically tune a PID controller for an Autonomous Underwater Vehicle (AUV). The implementation aims to enhance precision, adaptability, and robustness in underwater environments.

Date Created 2022-12-24 (2 years ago)

Commits 3 (last one 4 months ago)

Stargazers 43 (0 this week)

Watchers 1 (0 this week)

Forks 4

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Ranking

RepositoryStats indexes 641,237 repositories, of these AlinaBaber/ReinforcementLearning-QLearning-based-self-tuned-PID-controller-for-AUV-MatLab is ranked #535,720 (16th percentile) for total stargazers, and #562,788 for total watchers. Github reports the primary language for this repository as MATLAB, for repositories using this language it is ranked #1,324/1,674.

AlinaBaber/ReinforcementLearning-QLearning-based-self-tuned-PID-controller-for-AUV-MatLab is also tagged with popular topics, for these it's ranked: deep-learning (#7,844/8876), reinforcement-learning (#1,257/1476), neural-network (#1,041/1139), matlab (#353/396)

All Topics

auv matlab fuzzy-logic deep-learning neural-network pid-controller underwater-robotics reinforcement-learning

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3 commits on the default branch (main) since jan '22

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The only known language in this repository is MATLAB

updated: 2025-04-07 @ 09:53am, id: 581760424 / R_kgDOIqz1qA