Research on Trajectory Planning and Tracking of Hexa-copter

Abstract

In this paper, the flight control problem of hexa-copter is studied in detail from threedimensional trajectory planning to tracking. Then the cubic spline interpolation method is used to generate the trajectory by using these time marked waypoints. The flight trajectory curve produced by this method is smooth, twice differentiable, and it is easy to control implementation. The flight dynamics model of the UAV has the characteristics of multi-input multi-output, strong coupling, under-actuation, severe nonlinearity and external environmental disturbance. In order to improve the accuracy of flight trajectory and the stability of attitude control, a multi-loop sliding mode variable structure control method is proposed to achieve the hexa-copter flight trajectory tracking. The simulation results show that this method can track the predetermined flight trajectory and keep the attitude stability of the UAV normally.

System Identification and Nonlinear Model Predictive Control with Collision Avoidance Applied in Hexacopters UAVs

“…Linear models are only valid around the hover position, providing slow movements where the controllers cannot guarantee the convergence to the desired trajectories. In order to improve the performance and to satisfy the requirements of high-speed trajectories, a large number of studies have used the principles of nonlinear control, e.g., Chen et al, who proposed a nonlinear trajectory controller for UAVs based on backstepping and nonlinear observer [28] and Wang et al presented the sliding mode control (SMC) with a variable structure to generate the control inputs [29]. Recently, many authors have proposed using geometric tracking controllers, e.g., Lee et al showed the results of trajectory tracking using a nonlinear controller developed in a Euclidean group SE(3) [30]; Mellinger et al revealed the differential flatness properties in UAVs and the ability to derive the attitude, acceleration and angular rate [31].…”

Robust and Adaptive Backstepping Control for Hexacopter UAVs

“…Subtracting (24) from (23) yieldṡ e =Āe + B 2ẇd (25) where the observation errors of the disturbance observer are e = [X,X, 18 , A = A − K. The candidate control gains k O1 , k O2 and k O3 are chosen appropriately to letĀ satisfy the Hurwitz stability criterions, i.e., λI…”

“…However, these linear approaches are sensitive to the nonlinearities, and the flight performance will be degraded when the disturbances occur. In order to improve the robust control performance, more efforts have been made on the nonlinear control approaches, such as backstepping control [17], sliding mode control (SMC) [18], active disturbance rejection control (ADRC) [19], fuzzy control and other intelligent control methods [20]- [22]. The SMC method is insensitive to the disturbances and is widely applied for the nonlinear systems [23], [24].…”