Hybrid fuzzy-based sliding-mode control approach, optimized by genetic algorithm for quadrotor unmanned aerial vehicles

Abstract

According to the diverse applications of quadrotors in various military and space industries, this study attempts to focus on the modeling and simulation of a particular type of such robots, entitled unmanned aerial vehicles. The quadrotors are the vertical flying robots that contain four engines with impeller and it is possible to control this flyer with respect to the transitional force on these impellers. In fact, the quadrotors are the flyers with four propellers in a crisscross structure. These propellers allow the possibility of various movements to the quadrotors in such a way that control signals are applied to its operators and the difference in rotor speeds leads to the generation of different forces and movements. Such systems are dynamically unstable. Due to the nonlinear nature of quadrotor systems, modeling uncertainties and unmodeled dynamics in these systems, the need to design a suitable controller for optimal performance in different working conditions is strongly felt. In this paper, research on the modeling of unmanned flying robots in recent years is firstly reviewed and a mathematical model has been proposed for quadrotor robots with 6 degrees of freedom on the basis of the popular Newton–Euler equations. In the following, the capability of hybrid fuzzy-based sliding-mode control approach has been used to ensure the system stability. In addition, the genetic algorithm has been added to the control structure in order to optimize the proposed control system to meet the requirement of realizing fuzzy-based control approach. The results of the simulations in Matlab software clearly demonstrate that the state variables of the quadrotor robot reach a certain situation and place at the right time, once the nominal inputs are considered.