An adaptive neuro PID for controlling the altitude of quadcopter robot

Controlling the altitude of flying robots is one of the challenging issues in robotics. In this regard, this paper tries to investigate an adaptive PID controller which can adaptively result proper coefficients for controlling the altitude of flying robot. The structure of this PID controller is similar to Artificial Neuron used in many of artificial neural networks. Control of the robot´s altitude by this controller was shown in a sinusoidal path and eliminating the incoming disturbance by adaptive neuro PID controller was investigated too. The primary coefficients were obtained by genetic algorithm for improving the performance of controller and it was demonstrated. A PID controller that the coefficients of which was improved by genetic algorithm was used for better studying the controller in eliminating the disturbances´ effect which the results show the advantages of adaptive neuro PID controller with proper primary coefficients.