Tracking of a moving ground target by a quadrotor using a backstepping approach based on a full state cascaded dynamics

HighlightsA novel re-formulation of quadrotor dynamics leads to a cascaded form that allows the use of a backstepping controller and results in a more disturbance tolerant control as the use of algebraic inversion is avoided.Partial contraction is used to derive the backstepping control that guarantees stability and convergence.It is shown conclusively that the full state backstepping controller is more superior than the inverse kinematics-based backstepping controller in terms of unmodeled effects rejection.The backstepping controller formulated by the contraction theory in this paper is generic and can be applied to any dynamical systems satisfying the cascaded structure.Extensive simulation studies have been carried out to include aerodynamic effects and wind disturbances, and the proposed controller is verified to perform better than the benchmark controller. In this paper, a tracking controller is formulated for a quadrotor to track a moving ground target. The quadrotor exhibits distinct hierarchical dynamics that allows its position to be controlled by its attitude. This motivates the use of backstepping control on the underactuated quadrotor. Most backstepping architecture controls the quadrotor position and attitude independently, and couples them with inverse kinematics. Inverse kinematics computes the attitude angles required to achieve a desired acceleration. However unmodeled effects are shown to cause inexact inversion resulting in tracking error. The approach proposed in this paper uses a re-formulated full state cascaded dynamics to eliminate the need for inverse kinematics in a full state backstepping control architecture. It is shown that zero steady state error is achieved in the presence of unmodeled aerodynamics effect and wind disturbance despite no integral action. In addition, a backstepping formulation is derived using contraction theory that guarantees the boundedness of state response under bounded disturbances such as wind. This improves the system performance. Numerical simulations are performed using the proposed controller to track a target moving along predefined paths and the results are compared with a benchmark controller derived using inverse kinematics. The results show that the proposed controller is able to achieve better tracking performance under unmodeled aerodynamic effects and wind disturbance as compared with the benchmark controller.