Reinforcement Learning based Online Adaptive Flight Control for the Cessna Citation II(PH-LAB) Aircraft

R.B. Konatala, E. van Kampen, Gertjan H.N. Looye

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

16 Downloads (Pure)

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.
Original languageEnglish
Title of host publicationAIAA Scitech 2021 Forum
Subtitle of host publication11–15 & 19–21 January 2021, Virtual Event
PublisherAmerican Institute of Aeronautics and Astronautics Inc. (AIAA)
Number of pages27
ISBN (Electronic)978-1-62410-609-5
DOIs
Publication statusPublished - 2021
EventAIAA Scitech 2021 Forum - Virtual/online event due to COVID-19
Duration: 11 Jan 202121 Jan 2021

Conference

ConferenceAIAA Scitech 2021 Forum
Period11/01/2121/01/21

Fingerprint

Dive into the research topics of 'Reinforcement Learning based Online Adaptive Flight Control for the Cessna Citation II(PH-LAB) Aircraft'. Together they form a unique fingerprint.

Cite this