Real-Time Improvement of a Trajectory-Tracking Control Based on Super-Twisting Algorithm for a Quadrotor Aircraft

Abstract

This article addresses the development and experimental validation of a trajectory-tracking control for a miniature autonomous Quadrotor helicopter system (X4-prototype) using a robust algorithm control based on second-order sliding mode technique or also known as super-twisting algorithm in outdoor environments. This nonlinear control strategy guarantees the convergence in finite time to a desired path r(t) in the presence of external disturbances or uncertainties in the model affecting the appropriate behavior of our Quadrotor helicopter. For this purpose, a polynomial smooth curve trajectory is selected as a reference signal where the corresponding derivatives of the function are bounded. Moreover, we consider disturbances due to wind gusts acting on the aerial vehicle, and the reference signal is pre-programmed in an advanced autopilot system. The proposed solution consists of implementing a real-time control law based on super-twisting control using GPS measurements in order to obtain the position in the xy-plane to accomplish the desired trajectory. Simulation and experimental results of trajectory-tracking control are presented to demonstrate the performance and robustness of the proposed nonlinear controller in windy conditions.

In-flight directivity and sound power measurement of small-scale unmanned aerial systems

“…Determining the time-dependent position x(t) of a flying drone can be done in several ways. Possibilities include the use of GPS or similar systems [8], optical tracking with a multi-camera setup [9], built-in sensors [10], acoustic measurements [11], or a combination of these methods.…”

Dynamic Smooth Sliding Control Applied to UAV Trajectory Tracking

“…Solutions for the trajectory tracking problem of UAVs have been pursued in the literature [25]. In [26], [27], the altitude control of a quadrotor is based on a combined STA and high-order sliding mode (HOSM) observer, and in [28], a similar combination is addressed to estimate linear and angular velocities, and unknown lumped disturbance, including experimental evaluation with the quadcopter DJI M100. To be able to cover inspection tasks with UAVs, manipulators have been attached, such as in [29], where an STA with gain adaptation law is designed in the presence of a disturbance caused by the manipulator dynamics.…”

A Robust Fixed-Time Sliding Mode Control for Quadrotor UAV

“…The approach proposed in reference [26] uses an improved sliding mode speed control that combines a smoothed switching function and a low-pass filter to attenuate noise and improve motor speed control accuracy, while in reference [27], a control method is proposed where the estimated angles converge to the desired value for the scope of the orientation and therefore execute the tracking of the vehicle position to the given reference.…”