This paper proposes the rules of proper flight control and the design of an intelligent controller for the UAVs’ used for carrying blood and motion-sensitive medical equipment such as optical tubes that are used in industrial health monitors and glass vacuum tube structures. This equipment may be damaged if the device falls or vibrates. We proposed a new algorithm called UAVs’ Flight Optimization (DFO) that separates the couplings between the four main channels of the quadcopter, and in order to separate the rotational and roll motions from the yaw movement, we consider a new motion mechanism and the corresponding equations and relationships are extracted. The yaw movement of quadcopter during rotation and roll is eliminated. For this purpose, the nonlinear model of the quadcopter is extracted using Newton-Euler rules and the decision-making process is performed for this purpose to move to the desired point (target point) and the appropriate speed of the engines using the control rules. We simulated our algorithms over two controllers called proportional– integral–derivative (PID) and linear square adjusters (LQR) and compared our results against an adaptive slidingmode control algorithm. Simulation studies show that DFO has achieved minimum 91% less motion of yaw movements.

Autopilot, Control engineering, Drones, Remotely guided vehicles.