Sensor-Fused Fuzzy Variable Structure Incremental Control for Partially Known Nonlinear Dynamic Systems and Application to an Outdoor Quadrotor

The fuzzy rules with two premise variables, the switching surface of subsystem i and its time derivative, and a consequent variable with zero-order incremental control of subsystem i, are established. Irrespective of the controlled systems and their input/output data, the proposed control is designed by only the consistence between the controlled system and its fuzzy rule table. Due to stochastic noise and a low-end computing unit, the sensor-fused extended Kalman filter (EKF) can satisfactorily estimate three-dimensional pose. Based on system input/output response, the five control parameters and the values of fuzzy rule table are suitably tuned to achieve a satisfactory tracking response. It is called the sensor-fused fuzzy variable structure incremental control. Based on the lower bound of system functions and the relative upper bound of estimated output error and system functions, the stability of the closed-loop system is verified by the Lyapunov stability theory. Finally, the application to the circular path tracking at specific altitude of an outdoor quadrotor with comparison between the normal and broken propellers validates the effectiveness and robustness of the proposed control.