Presentation Title

Identification of Flight Dynamics Models of a Multicopter using Flight Data

Faculty Mentor

Subodh Bhandari

Start Date

17-11-2018 8:30 AM

End Date

17-11-2018 10:30 AM

Location

HARBESON 11

Session

POSTER 1

Type of Presentation

Poster

Subject Area

engineering_computer_science

Abstract

Effective use of UAVs requires complex flight controllers. This work presents the flight-testing, data collection, data processing, and system identification of a multicopter unmanned aerial vehicle (UAV) for use in designing flight controllers using advanced control system design techniques. The multicopter was flown extensively for the identification of flight dynamic models and verification. The collected data was first processed using MATLAB, and then converted into a frequency response using CIFER (Comprehensive Identification from FrEquency Response) software. The frequency response was then used for the identification of transfer function and state-space mathematical models of the Y6 multicopter in hovering flight. Different tools within the CIFER software were used to analyze the data and for the model identification. Methods of flight data collection, data types required for the identification and verification, identified models, and comparison between the identified model response, and flight data will be presented.

Summary of research results to be presented

The flight test data was processed in MATLAB. The processed data was used for the model identification using CIFER software that first converts the time-domain data to frequency response using Fourier transform. The frequency response was then used for the identification of state-space and transfer function model parameters. Motor lag was introduced during the identification process. Cramer-Rao (CR) bound of less than 20%, insensitivity of less than 10%, and average cost function of 40.8723 was obtained, indicating a good and satisfactory model identification. The doublet data collected during flight tests were used to verify the model identified using CIFER. The total cost function for time-domain verification on the lateral axis was 21.018, indicating a good model identification. Due to wind and lag in pilot inputs, the model responses shows some discrepancies with the flight data, but overall response is satisfactory.

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Nov 17th, 8:30 AM Nov 17th, 10:30 AM

Identification of Flight Dynamics Models of a Multicopter using Flight Data

HARBESON 11

Effective use of UAVs requires complex flight controllers. This work presents the flight-testing, data collection, data processing, and system identification of a multicopter unmanned aerial vehicle (UAV) for use in designing flight controllers using advanced control system design techniques. The multicopter was flown extensively for the identification of flight dynamic models and verification. The collected data was first processed using MATLAB, and then converted into a frequency response using CIFER (Comprehensive Identification from FrEquency Response) software. The frequency response was then used for the identification of transfer function and state-space mathematical models of the Y6 multicopter in hovering flight. Different tools within the CIFER software were used to analyze the data and for the model identification. Methods of flight data collection, data types required for the identification and verification, identified models, and comparison between the identified model response, and flight data will be presented.