This work introduces two system identification methods and applies them to flight data from the Cessna 172 and LearJet 25 in the X-Plane flight simulator. The identified models are compared to reference models for the two airplanes to evaluate the algorithms application to aircraft. The system identification methods are the Sparse Identification of Nonlinear Dynamics (SINDY) and the Output-Error Method (OEM). Both methods produced linear models that had minimal errors when predicted aircraft states were compared to measured aircraft states.

The identified models were then used to develop a control augmentation system for the LearJet in the cruise condition. Desired closed loop dynamics were produced using handling qualities metrics. Implicit model following control was then used to create the control law algorithm that produces the desired closed loop dynamics.

Finally, the developed control augmentation system was implemented using MATLAB/Simulink and ran in real time with X-Plane in the loop. The identified models proved to be sufficient to create control law algorithms with excellent performance in the presence of the nonlinear flight simulation.