Print Email Facebook Twitter Reinforcement Learning based Online Adaptive Flight Control for the Cessna Citation II(PH-LAB) Aircraft Title Reinforcement Learning based Online Adaptive Flight Control for the Cessna Citation II(PH-LAB) Aircraft Author Konatala, R.B. (Student TU Delft) van Kampen, E. (TU Delft Control & Simulation) Looye, Gertjan H.N. (Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR)) Date 2021 Abstract OnlineAdaptive Flight Control is interesting in the context of growing complexity of aircraft systems and their adaptability requirements to ensure safety. An Incremental Approximate Dynamic Programming (iADP) controller combines reinforcement learning methods, optimal control and online identified incremental model to achieve optimal adaptive control suitable for Nonlinear Time-Varying systems. The main contribution of this paper is twofold. Firstly, the iADP controller is designed to achieve automatic online rate control to track pilot commands via setpoints provided by the manual outer loop on Citation II Aircraft model. Secondly, to assess the controller performance in the presence of sensor dynamics and actuator dynamics, an analysis is carried out to identify causes of any performance degradation. The simulation results from iADP longitudinal control using full state feedback indicate that the discretization of sensor signals, sensor bias and transport delays did not have any significant effect on the controller performance or on the incremental model identification. However noisy signals and sensors delays are found to cause controller performance degradation. Appropriate filtering of signals resulted in better estimation of the incremental model subsequently improving the controller performance due to noisy signals. Control performance degradation due to sensor delays should be addressed in future before conducting flight tests on Citation II Aircraft. To reference this document use: http://resolver.tudelft.nl/uuid:b37cefbf-e353-43cf-8d9d-98f2653216c6 DOI https://doi.org/10.2514/6.2021-0883 Publisher American Institute of Aeronautics and Astronautics Inc. (AIAA) ISBN 978-1-62410-609-5 Source AIAA Scitech 2021 Forum: 11–15 & 19–21 January 2021, Virtual Event Event AIAA Scitech 2021 Forum, 2021-01-11 → 2021-01-21, Virtual/online event due to COVID-19 , Virtual, Online Bibliographical note Virtual/online event due to COVID-19 Part of collection Institutional Repository Document type conference paper Rights © 2021 R.B. Konatala, E. van Kampen, Gertjan H.N. Looye Files PDF 6.2021_0883.pdf 834.34 KB Close viewer /islandora/object/uuid:b37cefbf-e353-43cf-8d9d-98f2653216c6/datastream/OBJ/view