Comparison of RL agent and PID response for heading controller.
<p>Comparison of RL agent and PID response for heading controller.</p>
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2025
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| _version_ | 1852015875813539840 |
|---|---|
| author | Hasan Raza Khanzada (22404835) |
| author2 | Adnan Maqsood (22404838) Abdul Basit (174463) |
| author2_role | author author |
| author_facet | Hasan Raza Khanzada (22404835) Adnan Maqsood (22404838) Abdul Basit (174463) |
| author_role | author |
| dc.creator.none.fl_str_mv | Hasan Raza Khanzada (22404835) Adnan Maqsood (22404838) Abdul Basit (174463) |
| dc.date.none.fl_str_mv | 2025-10-09T20:08:09Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0334219.g025 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Comparison_of_RL_agent_and_PID_response_for_heading_controller_/30324100 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Cell Biology Biotechnology Ecology Inorganic Chemistry Science Policy Biological Sciences not elsewhere classified critical gap persists classical pid controllers 3 %, offering varying flight conditions suitable rl algorithm space rl algorithms rl algorithms outperformed provide valuable insight comparative analysis reveals uav flight controls evaluated rl algorithms comparative analysis flight control rl agents rl ). analysis aims wing uavs wind gusts uncertain environments uavs ). state error soft actor rigorous evaluation results demonstrate relative strengths reinforcement learning recent studies paper aims major shift leading continuous environmental disturbances deliver robust control pitch best trade 400 episodes |
| dc.title.none.fl_str_mv | Comparison of RL agent and PID response for heading controller. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>Comparison of RL agent and PID response for heading controller.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_abb541cac99bfaf16a3ba418cdbd6ffd |
| identifier_str_mv | 10.1371/journal.pone.0334219.g025 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30324100 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Comparison of RL agent and PID response for heading controller.Hasan Raza Khanzada (22404835)Adnan Maqsood (22404838)Abdul Basit (174463)Cell BiologyBiotechnologyEcologyInorganic ChemistryScience PolicyBiological Sciences not elsewhere classifiedcritical gap persistsclassical pid controllers3 %, offeringvarying flight conditionssuitable rl algorithmspace rl algorithmsrl algorithms outperformedprovide valuable insightcomparative analysis revealsuav flight controlsevaluated rl algorithmscomparative analysisflight controlrl agentsrl ).analysis aimswing uavswind gustsuncertain environmentsuavs ).state errorsoft actorrigorous evaluationresults demonstraterelative strengthsreinforcement learningrecent studiespaper aimsmajor shiftleading continuousenvironmental disturbancesdeliver robustcontrol pitchbest trade400 episodes<p>Comparison of RL agent and PID response for heading controller.</p>2025-10-09T20:08:09ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0334219.g025https://figshare.com/articles/figure/Comparison_of_RL_agent_and_PID_response_for_heading_controller_/30324100CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/303241002025-10-09T20:08:09Z |
| spellingShingle | Comparison of RL agent and PID response for heading controller. Hasan Raza Khanzada (22404835) Cell Biology Biotechnology Ecology Inorganic Chemistry Science Policy Biological Sciences not elsewhere classified critical gap persists classical pid controllers 3 %, offering varying flight conditions suitable rl algorithm space rl algorithms rl algorithms outperformed provide valuable insight comparative analysis reveals uav flight controls evaluated rl algorithms comparative analysis flight control rl agents rl ). analysis aims wing uavs wind gusts uncertain environments uavs ). state error soft actor rigorous evaluation results demonstrate relative strengths reinforcement learning recent studies paper aims major shift leading continuous environmental disturbances deliver robust control pitch best trade 400 episodes |
| status_str | publishedVersion |
| title | Comparison of RL agent and PID response for heading controller. |
| title_full | Comparison of RL agent and PID response for heading controller. |
| title_fullStr | Comparison of RL agent and PID response for heading controller. |
| title_full_unstemmed | Comparison of RL agent and PID response for heading controller. |
| title_short | Comparison of RL agent and PID response for heading controller. |
| title_sort | Comparison of RL agent and PID response for heading controller. |
| topic | Cell Biology Biotechnology Ecology Inorganic Chemistry Science Policy Biological Sciences not elsewhere classified critical gap persists classical pid controllers 3 %, offering varying flight conditions suitable rl algorithm space rl algorithms rl algorithms outperformed provide valuable insight comparative analysis reveals uav flight controls evaluated rl algorithms comparative analysis flight control rl agents rl ). analysis aims wing uavs wind gusts uncertain environments uavs ). state error soft actor rigorous evaluation results demonstrate relative strengths reinforcement learning recent studies paper aims major shift leading continuous environmental disturbances deliver robust control pitch best trade 400 episodes |