Vertical modeling of a quadcopter for mass estimation and diagnosis purposes
2017 (Engelska)Ingår i: Proceedings of the Workshop on Research, Education and Development on Unmanned Aerial Systems, RED-UAS, Linköping, Sweden, 3-5 October, 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]
In this work, we estimate a model of the vertical dynamics of a quadcopter and explain how this model can be used for mass estimation and diagnosis of system changes. First, a standard thrust model describing the relation between the calculated control signals of the rotors and the thrust that is commonly used in literature is estimated. The estimation results are compared to those using a refined thrust model and it turns out that the refined model gives a significant improvement. The combination of a nonlinear model and closed-loop data poses some challenges and it is shown that an instrumental variables approach can be used to obtain accurate estimates. Furthermore, we show that the refined model opens up for fault detection of the quadcopter. More specifically, this model can be used for mass estimation and also for diagnosis of other parameters that might vary between and during missions.
Ort, förlag, år, upplaga, sidor
Institute of Electrical and Electronics Engineers (IEEE), 2017.
Nyckelord [en]
payload, modeling, quadcopter, fault detection and isolation
Nationell ämneskategori
Reglerteknik
Identifikatorer
URN: urn:nbn:se:liu:diva-141883DOI: 10.1109/RED-UAS.2017.8101665ISI: 000427383700032ISBN: 978-1-5386-0939-2 (digital)ISBN: 978-1-5386-0940-8 (tryckt)OAI: oai:DiVA.org:liu-141883DiVA, id: diva2:1148624
Konferens
Workshop on Research, Education and Development on Unmanned Aerial Systems, RED-UAS, Linköping, Sweden, 3-5 October, 2017
Projekt
MarineUAS
Forskningsfinansiär
EU, Horisont 2020, 642153
Anmärkning
This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 642153.
2017-10-112017-10-112018-04-11Bibliografiskt granskad