A Self-adaptive Cascade Fuzzy PID Method of Attitude Control for Quadrotor

Quadrotor is a popular type of unmanned aerial vehicle (UAV). Usually, it can be regarded as a complex nonlinear control system, characterized of being multi-variable, under-actuated and strong-coupling. It, nowadays, has raised great interests of researchers due to several challenges, for instance it is time consuming to tune and adjust key parameters of a controller, also the attitude of a UAV would be too sensitive to environmental factors. The work proposes a new cascade fuzzy proportional integral derivative (PID) method for quadrotor. The method is based on the theory of fuzzy mathematics and control system modelling. One of the advantages of our method is that key control parameters are self-adapted to the PM controller designed. To verify the performance of the new method, we numerically simulate and quantitatively compare it with the conventional single-stack PM algorithm and cascade PM algorithm, with two indicators of responding speed and anti-interference ability of the control system. The results suggested that the method outperforms the rivals in terms of the indicators measured.