dc.contributor.author | Kimathi, Stephen | |
dc.date.accessioned | 2017-07-24T13:39:56Z | |
dc.date.available | 2017-07-24T13:39:56Z | |
dc.date.issued | 2017 | |
dc.identifier.issn | 2277-8616 | |
dc.identifier.uri | http://41.89.227.156:8080/xmlui/handle/123456789/609 | |
dc.description.abstract | Heading control of an Unmanned Aerial Vehicle, UAV is a vital operation of an autopilot system. It is executed by employing a design of control algorithms that control its direction and navigation. Most commonly available autopilots exploit Proportional-Integral-Derivative (PID) based heading controllers. In this paper we propose an online adaptive reinforcement learning heading controller. The autopilot heading controller will be designed in Matlab/Simulink for controlling a UAV in X-Plane test platform. Through this platform, the performance of the controller is shown using real time simulations. The performance of this controller is compared to that of a PID controller. The results show that the proposed method performs better than a well tuned PID controller. | en_US |
dc.language.iso | en | en_US |
dc.publisher | IJSTR | en_US |
dc.subject | UAV | en_US |
dc.subject | Reinforcement Learning | en_US |
dc.subject | PID | en_US |
dc.subject | X-Plane PID | en_US |
dc.subject | X-Plane | en_US |
dc.title | Application Of Reinforcement Learning In Heading Control Of A Fixed Wing UAV Using X-Plane Platform | en_US |
dc.type | Article | en_US |