Adaptive Fuzzy-PID Attitude and Altitude Control for a Lab Quadrotor

To control a nonlinear system efficiently, it is needed to use a nonlinear controller or to improvise a linear controller. The classical proportional-integral-derivative (PID) controllers have been developed and used for many purposes by researchers in the literature, and although they are tuned to give good results, the problems of overshoot, undershoot, long rise and settling times will always exist. A quadrotor has nonlinear dynamics and the traditional PID controllers implemented in the literature have the aforementioned deficiencies. In this paper, we propose two adaptive fuzzy-PID controllers for attitude and altitude control of a lab quadcopter to overcome such problems. Nonlinear modeling and simulation of quadrotor’s dynamics have been done using MATLAB, Simulink, and quadcopter’s properties such as weight, moment of inertia, motor torque, etc. have been modeled based on a lab quadrotor. Fuzzy decision making has been used to change PID coeficients constantly with respect to error and rate of error and based on ۱۴۷ fuzzy rules, thus creating an adaptive fuzzy-PID controller. The adaptive fuzzy-PID controller is tested against two different scenarios, one is the traditional single command and the other is a critical situation with multi-commands. The results show that the proposed controllers have less overshoot and lower settling times, and also they are more robust in critical conditions.