Index Catalog // Arch : Northwestern University Institutional Repository

Start Over

Filtering by: Type Work Resource type Masters Thesis Subject Machine learning Subject Proximal Policy Optimization Subject Space vehicles--Attitude control systems

1 entry found

List Gallery Masonry Slideshow

1. Comparison of Traditional Optimal Control Methodologies to Reinforcement Learning Agents in Quadcopter Attitude Control Applications

Description:: Attitude control in quadrotor Unmanned Aerial Vehicle (UAV) systems is traditionally managed by optimal control loops tuned to minimize errors in performance. While robust, these loops perform sub-optimally in dynamic and unpredictable environments which inspire new interest in sophisticated solution and approaches such as reinforcement learning (RL) approaches which should...
Keyword:: Intelligent Systems, Reinforcement Learning, Quadcopters, Learning and Adaptive Systemsons, Aerial Systems: Mechanics and Control, Proximal Policy Optimization, Drones, and Attitude Control
Subject:: Space vehicles--Attitude control systems, Proximal Policy Optimization, Reinforcement learning, Policy Gradient, Drone aircraft, and Machine learning
Creator:: Stephen Kleppinger,
Contributor:: Bharadwaj, Shreenidhi (advisor)
Owner:: Stephen Michael Kleppinger
Publisher:: Northwestern University
Language:: English
Date Uploaded:: 04/05/2022
Date Modified:: 04/05/2022
Date Created:: 12-2021
Resource Type:: Masters Thesis

LIBRARIES | ARCH

Limit your search

Type

Resource type

Creator

Contributor

Keyword

Subject

Language

Publisher

1. Comparison of Traditional Optimal Control Methodologies to Reinforcement Learning Agents in Quadcopter Attitude Control Applications

Limit your search

Search Constraints

Search Results

1. Comparison of Traditional Optimal Control Methodologies to Reinforcement Learning Agents in Quadcopter Attitude Control Applications