Akademik Veri Yönetim Sistemi
5th. International Conference on Engineering and Natural Sciences (ICENS 2019), Praha, Çek Cumhuriyeti, 12 - 16 Haziran 2019, ss.310-317
In this study, adaptive neuro-fuzzy inference system called ANFIS structure was investigated for longitudinal
control of a fixed wing unmanned aerial vehicle (UAV). ANFIS control is one of the modern control
techniques which is based on artificial neural networks (ANN) and the structure of the system is based on
Takagi-Sugeno fuzzy inference system. In this conference paper, ANFIS control method was studied in order
to design a longitudinal controller architecture of a fixed wing UAV. Reference model and aerodynamic
parameter values of the UAV were obtained from the literature for this specific UAV model. According to the
simulation data taken from PID controller structure in MATLAB®, ANFIS training and testing data were
obtained and trained data were used for longitudinal aircraft dynamics such as pitch attitude hold
characteristics. Hybrid and back-propagation optimization algorithms were applied to have optimum
training performance. ANFIS structure was also simulated together with PI and PID controllers in Simulink.
In this analysis, results have been satisfying in terms studies of the fixed wing UAV control and ANFIS and
PID hybrid methods had more suitable results