Can Öznurlu, M.Sc.
Department of Scientific Computing
August 2022
Supervisor: Ömür Uğur (Institute of Applied Mathematics, Middle East Technical University, Ankara)
Co-Supervisor: Tayfun Çimen (Turkish Aerospace, Turkey)
Abstract
The focus of this thesis is to control the lateral-directional motion of the fighter aircraft by using integral action based Model Predictive Control (MPC) where the model is obtained by data-driven model discovery method. Dynamic Mode Decomposition with Control (DMDc) is used as a model discovery technique based only on measurement data with no modeling assumptions. The model created using this technique is used for MPC and tested against noisy conditions. In addition, performance comparıson of MPC with Classical Controller is carried out. Finally, Speedgoat Unit Real-Time Target Machine®, which offers a real-time testing is used to verify the generated DMDc-MPC algorithm and understand the computational cost. The results show that the DMDc model discovery method performs very well in noise-free situations and meets the evaluation criteria together with MPC. However, its performance decreases in the presence of measurement noise. Finally, real-time test results on Speedgoat equipment have shown that the generated DMDc-MPC algorithm has low computational cost and can be used in systems with low computational power.
Keywords: DMDc, Modelling, System Identification, Data-Driven Control, Model Predictive Control, Fighter Aircraft Dynamics