Dynamical Modelling and Robust Control for an Unmanned Aerial Robot Using Hexarotor with 2-DOF Manipulator

• Published in: International Journal of Aerospace Engineering Vol. 2019; no. 2019; pp. 1 - 12
• Main Authors: Ding, Li, Hongtao, Wu
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 2019; Hindawi; John Wiley & Sons, Inc; Wiley
• Subjects: Active control; Advanced manufacturing technologies; Aerospace engineering; Aircraft; Algorithms; Analysis; Artificial intelligence; Computer simulation; Control theory; Controllers; Couplings; Degrees of freedom; Design; Disturbances; Dynamic models; Feedback control; Kinematics; Manipulators; Numerical analysis; Parameters; Researchers; Robot arms; Robot control; Robot dynamics; Robotics; Robots; Robust control; State observers; State variable; Tracking control; Trajectory control; Uncertainty
• DOI: 10.1155/2019/5483073
• ISSN: 1687-5966

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.