Abstract
A new finite-time control method based on a sliding mode for a multirotor unmanned aerial vehicle (UAV) is developed to improve both the transient and steady-state responses, including overshoot and steady-state error in the presence of uncertainties and external disturbances. First, a virtual control with nonlinear sliding manifolds is designed to achieve position-tracking capability, as well as to guarantee the fast convergence of the UAV to a desired position. Furthermore, an ultimate control is developed for the desired attitude-tracking performance. Various uncertainties, including torque due to the discordance between the centre of mass and rotation and wind disturbances are considered. The Lyapunov stability theorem is then applied step-by-step to prove the asymptotically stable and finite-time convergence in position and attitude controllers. Second, the proposed controller is implemented in an open-source hardware platform for a quadrotor UAV. Both numerical and experimental results are compared to validate the tracking performance for attitude and position control, as well as robustness under disturbances.
Highlights
In recent years, multirotor unmanned aerial vehicles (UAVs) have been widely developed and have become popular because of their extensive usefulness in a wide area of applications, such as military surveillance, management of natural risks, agriculture, and industrial automation. [1]
Both numerical and experimental results on a quadrotor UAV are demonstrated in the presence of modelled uncertainty and disturbance to show robustness of the controller
The attitude and angular velocities of the UAV are measured by an inertial measurement unit (IMU) sensor, and the attitude control loop was operated at 200 Hz
Summary
Multirotor unmanned aerial vehicles (UAVs) have been widely developed and have become popular because of their extensive usefulness in a wide area of applications, such as military surveillance, management of natural risks, agriculture, and industrial automation. [1]. A few controllers have been developed so far for the finite-time convergence of both the attitude and position of UAVs to the sliding manifold in the presence of disturbance and model uncertainties; still there are limitation to UAV applications in practice.
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