Robust Nonlinear Model Predictive Control Based Visual Servoing of Quadrotor UAVs

• Published in: IEEE/ASME transactions on mechatronics Vol. 26; no. 2; pp. 700 - 708
• Main Authors: Zhang, Kunwu, Shi, Yang, Sheng, Huaiyuan
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Cameras; Disturbances; Field of view; Image-based visual servoing (IBVS); Kinematics; Lipschitz condition; Mechatronics; Nonlinear control; Predictive control; quadrotor; Robust control; robust nonlinear model predictive control (NMPC); Rotary wing aircraft; Servocontrol; Tracking errors; Uncertainty; Unmanned aerial vehicles; Virtual cameras; Visibility; Visual servoing; Visualization
• ISSN: 1083-4435; 1941-014X
• DOI: 10.1109/TMECH.2021.3053267

In this article, a robust nonlinear model predictive control (NMPC) scheme is proposed for the visual servoing of quadrotors subject to external disturbances. By using the virtual camera approach, the image moments are defined in the virtual camera plane and adopted as visual features to derive the decoupled image kinematics. As a result, the image-based visual servoing (IBVS) system model is established by integrating the image kinematics and quadrotor dynamics. To handle the visibility constraint, a robust NMPC scheme is developed for the IBVS of the quadrotor such that the visual target can stay within the field of view of the camera. In addition, based on the Lipschitz condition, the tightened state constraints are constructed to tackle external disturbances. The sufficient conditions on guaranteeing recursive feasibility of the proposed NMPC algorithm are derived. Furthermore, we theoretically show that the tracking error will converge to a small set around the origin in finite time under some derived conditions. Finally, simulation studies and experimental tests are conducted to verify the efficacy of the proposed method.