Abstract
The robust control issues in trajectory tracking of an unmanned aerial robot (UAR) are challenging tasks due to strong parametric uncertainties, large nonlinearities, and high couplings in robot dynamics. This paper investigates the dynamical modelling and robust control of an aerial robot using a hexarotor with a 2-degrees-of-freedom (DOF) manipulator in a complex aerial environment. Firstly, the kinematic model and dynamic model of the aerial robot are developed by the Euler-Lagrange method. Afterwards, a linear active disturbance rejection control is designed for the robot to achieve a high-accuracy trajectory tracking goal under heavy lumped disturbances. In this control scheme, the modelling uncertainties and external disturbances are estimated by a linear extended state observer, and the high tracking precision is guaranteed by a proportion-differentiation (PD) feedback control law. Meanwhile, an artificial intelligence algorithm is applied to adjust the control parameters and ensure that the state variables of the robot converge to the references smoothly. Furthermore, it requires no detailed knowledge of the bounds on unknown dynamical parameters. Lastly, numerical simulations and experiments validate the efficiency and advantages of the proposed method.
Highlights
The capability of unmanned aerial robot (UAR) has been expanded radically with multidegrees-of-freedom aerial manipulators
This paper provides some discussion about the issues in dynamical modelling and robust controller of a UAR using a hexarotor with 2-DOF manipulator
We have presented modelling and control techniques to perform an aerial robot using an unmanned hexarotor and multiple-degree manipulator arms
Summary
The capability of UARs has been expanded radically with multidegrees-of-freedom aerial manipulators. This paper provides some discussion about the issues in dynamical modelling and robust controller of a UAR using a hexarotor with 2-DOF manipulator. The coupling effect may cause a change in the physical parameters of the system during the operating process Aiming at this issue, the aerial robot is divided into two subsystems, namely, the aircraft and the manipulator. Abaunza et al [10] adopted a dual quaternion method to generate the dynamic model of an aerial robot using a quadrotor with a 3-DOF manipulator. The robust control issue can be handled using the following two approaches, termed the model-based approach and the model-free approach In the former approach, the full information about the aerial robot plant should be known a priori.
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