Development of model free flight control system using deep deterministic policy gradient (DDPG)

dc.contributor.advisorTsourdos, Antonios
dc.contributor.advisorShin, Hyo-Sang
dc.contributor.authorBudiarti, Dewi H.
dc.date.accessioned2023-09-21T13:34:16Z
dc.date.available2023-09-21T13:34:16Z
dc.date.issued2019-09
dc.description.abstractDeveloping a flight control system for a complete 6 degree-of-freedom for an air vehicle remains a huge task that requires time and effort to gather all the necessary data. This thesis proposes the use of reinforcement learning to develop a policy for a flight control system of an air vehicle. This method is designed to be independent of a model but it does require a set of samples for the reinforcement learning agent to learn from. A novel reinforcement learning method called Deep Deterministic Policy Gradient (DDPG) is applied to counter the problem with large and continuous space in a flight control. However, applying the DDPG for multiple action is often difficult. Too many possibilities can hinder the reinforcement learning agent from converging its learning process. This thesis proposes a learning strategy that helps shape the way the learning agent learns with multiple actions. It also shows that the final policy for flight control can be extracted and applied immediately for a flight control system.en_UK
dc.description.coursenameAerospaceen_UK
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/20268
dc.language.isoenen_UK
dc.publisherCranfield Universityen_UK
dc.publisher.departmentSATMen_UK
dc.rights© Cranfield University, 2019. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder.en_UK
dc.subjectreinforcement learningen_UK
dc.subjectflight controlen_UK
dc.subjectdeep deterministic policy gradienten_UK
dc.subjectlearning strategyen_UK
dc.titleDevelopment of model free flight control system using deep deterministic policy gradient (DDPG)en_UK
dc.typeThesis or dissertationen_UK
dc.type.qualificationlevelDoctoralen_UK
dc.type.qualificationnamePhDen_UK

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