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An Aerial Robot or Unmanned Aerial Vehicle (UAV) is an aerial vehicle that provides its flight condition using aerodynamic forces. Also, this vehicle can be named as an autonomous robot. This robot is an under-actuated system and it is inherently unstable. Thus, the control of this nonlinear system is a problem for both practical and theoretical interest. So, the goal of this research is to contrast with highly nonlinear dynamic system of Octorotor that its control is difficult in many cases and it causes existence of instability in this Unmanned Aerial Vehicle (UAV). At the first, the structure of Octorotor is studied in this paper in order to increasing power, more carrying and increment of resistance into changing and distribution. Also, the electronic and mechanic of this robot is studied in some sections. Then, in the following, in order to attitude control of robot with introduction of dynamic system, one of the most common implemented controllers is applied on this robot. Initially, this process is done on the dynamic model of robot by Matlab/Simulink software and finally, implementation of this controller is applied on a fabricated Octorotor during a real flight in autonomous trajectory tracking in outdoor environment. At last, the study of sensors results is also shown.

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This paper presents a completely practical control approach for quadrotor drone. Quadrotor is modelled using Euler-Newton equations. For stabilization and control of quadrotor a classic PID controller has been designed and implemented on the plant and a fuzzy controller is used to adjust the controller parameters. Considering that quadrotor is a nonlinear system, using classic controllers for the plant is not effective enough. Therefor using fuzzy system which is a nonlinear controller is effective for the nonlinear plant. According to the desire set point, fuzzy system adjusts the controller gain values to improve the performance of quadrotor and it leads to better results than classical PID controller. To study the performance of fuzzy PID controller on attitude control of the system, a quadrotor is installed to the designed stand. The system consists of accelerometer and gyroscope sensors and a microcontroller which is used to design fuzzy PID attitude controller for the quadrotor. Considering that the experimental data has lots of errors and noises, Kalman filter is used to reduce the noises. Finally using the Kalman filter leads to better estimation of the quadrotor angle position and the fuzzy PID controller performs the desired motions successfully.