Kose, Oguz; Oktay, Tugrul

In recent years, the interest in unmanned aerial vehicles (UAV) has increased. They have penetrated into all areas of life. However, studies on UAV control have been a frequently discussed topic by researchers. In this study, a hexarotor in which yaw flight is tried to be controlled by changing the arm lengths during flight (morphing) is discussed. The hexarotor mathematical model is linearly derived using Newton's equations of motion. The equations of motion are modeled using the state space model approach. Hexarotor has been drawn in Solidworks program in accordance with the reality of all morphing states. Morphing estimation and accordingly proportional-integral-derivative (PID) coefficients were estimated using Simultaneous Perturbation Stochastic Approximation (SPSA). SPSA was preferred because it converged to the optimum result faster than similar algorithms. Hexarotor simulations were performed in Matlab/Simulink environment. Hexarotor yaw flight stability was achieved by minimizing the SPSA generated cost function based on design performance criteria. The cost function converged in 3-4 iterations and approached the optimum result. Accordingly, the design performance criteria have also improved and successfully followed the given trajectory.

Kose, Oguz; Oktay, Tugrul

Quadrotor modeling has been done with collective and differential morphing. Quadrotor initial state and morphing states are drawn in the Solidworks program. Newton-Euler approximation was used for quadrotor modeling. The mass and moment of inertia values required for modeling and simulation were obtained from the Solidworks program. Matlab / Simulink environment and state-space model approaches are used for simulations. A simultaneous perturbation stochastic approximation (SPSA) algorithm was used to determine the quadrotor morphing rates. If the morphing state obtained by SPSA is not included in the values obtained from the drawings, here it is provided to find the moments of inertia with the method based on learning by using the data obtained with the Artificial Neural Network(ANN). Proportional Integral Derivative (PID) is used as the quadrotor control algorithm. PID coefficients are also determined by SPSA.