Modeling and Control for Agile Aircraft Development
Description/Abstract/Artist Statement
The Modeling and Control for Agile Aircraft Development is a program that attempts to develop a model-less controller for aircraft. This work is being done in conjunction with the NASA Langley Research Center. The results of this research will be tested at NASA’s 12-ft Low speed wind tunnel. The goal of this work is to initially use fuzzy logic to control an aircraft while its model is learned in flight. Once the model is learned, a controller needs to be designed to more accurately control the aircraft. My research focuses on using the MATLAB MPC toolbox to design a controller that uses the learned model to control the pitch, yaw, and roll of the aircraft. The benefit of the MPC controller over a classical PID controllers is it allows for amplitude and rate constraints to be set for multiple control surfaces. The biggest drawback to the MPC controller is the long processing time. This is accounted for in my research by converting the MATLAB code into MATLAB executable (MEX) code. Thus far I have been able to confirm that by converting to MEX code, we can decrease processing time by 38% . As of now, the expectation is the controller for the aircraft pitch should be finished soon and the roll and yaw not long after.
Faculty Advisor/Mentor
Oscar Gonzalez
Presentation Type
Poster
Disciplines
Controls and Control Theory
Session Title
Poster Session
Location
Learning Commons @ Perry Library, Northwest Atrium
Start Date
2-2-2019 8:00 AM
End Date
2-2-2019 12:30 PM
Modeling and Control for Agile Aircraft Development
Learning Commons @ Perry Library, Northwest Atrium
The Modeling and Control for Agile Aircraft Development is a program that attempts to develop a model-less controller for aircraft. This work is being done in conjunction with the NASA Langley Research Center. The results of this research will be tested at NASA’s 12-ft Low speed wind tunnel. The goal of this work is to initially use fuzzy logic to control an aircraft while its model is learned in flight. Once the model is learned, a controller needs to be designed to more accurately control the aircraft. My research focuses on using the MATLAB MPC toolbox to design a controller that uses the learned model to control the pitch, yaw, and roll of the aircraft. The benefit of the MPC controller over a classical PID controllers is it allows for amplitude and rate constraints to be set for multiple control surfaces. The biggest drawback to the MPC controller is the long processing time. This is accounted for in my research by converting the MATLAB code into MATLAB executable (MEX) code. Thus far I have been able to confirm that by converting to MEX code, we can decrease processing time by 38% . As of now, the expectation is the controller for the aircraft pitch should be finished soon and the roll and yaw not long after.