2-Sliding Mode Trajectory Tracking Control and EKF Estimation for Quadrotors

This paper addresses the trajectory tracking problem for a quadrotor affected by external perturbations and inaccurate measures. A control strategy is proposed using time scale separation of the translational and rotational dynamics. A second order sliding mode controller is developed for the translational dynamic in order to deal with external perturbations while avoiding the undesired chattering effect. The rotational dynamics are controlled by a linear PD control. A data fusion algorithm using the Extended Kalman Filter (EKF) is proposed to estimate the position and velocity of the quadrotor, taking into account information from multiple commonly used sensors such as an Inertial Measurement Unit (IMU), optic flow sensor and Global Positioning Systems (GPS). Simulations are carried out to test the proposed observer-controller scheme while introducing perturbations and inaccurate measures common in non expensive sensors.