Flight control board design and kalman filter based flight position control for UAVs

It is known that the widespread use of unmanned aerial vehicles (UAVs) in civil and military areas has increased with the development of technology. Especially the 4-engine UAVs, which can take off and land vertically, have important features such as high maneuverability, small size and autonomous flight ability, and have expanded their usage area. In this thesis study, it is aimed to design a unique control card for UAVs and to perform high accuracy measurement and balance control operations with Kalman Filters. In the study, firstly, a general purpose flight control card was designed and implemented. STM32F401RCT6 microcontroller, an ARM Cortex-M4 based microcontroller, was used in the flight control card and balance measurements were provided with IMU sensors. Later in the study, after the experimental control hardware created for UAVs, the signals received from the IMU sensor in the control software were converted into meaningful and stable signals with Kalman filters and made ready for the control cycle. The indigenously developed flight control card is hardware capable of providing all the autonomous flight control requirements required for a UAV. In the developed system, the flight control software consists of two main parts. The first is the predictive section, which provides more meaningful and accurate information to the controller by filtering and predicting noisy and delayed data from sensors. Here, Kalman filters and sensor fusion algorithms are used together, which provide a more accurate and reliable situation estimation by combining data from sensors. In the second part of the flight control software, there are controller algorithms that control the UAV's variables such as angular speed, angle, linear speed and position. In the experimental study, PID control, the most basic controller structure, was used for the closed-loop stability control test of the designed flight control card. In the test studies, settling to a fixed reference angle, settling to reference angles arranged in a square wave form, and behavior against disturbing effects were observed. Additionally, the effects of the Kalman Filter were examined experimentally. From the experimental results, it has been seen that the designed flight control card is quite successful in stability experiments, and complementary algorithms such as filtering, especially Kalman Filter, Sensor Fusion, affect thestability for a successful flight control.