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An Anti-wind Modeling Method of Quadrotor Aircraft and Cascade Controller Design Based on Improved Extended State Observer

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Abstract

Wind disturbance may significantly reduce the flight control performance of quadrotors when flying. In order to meet high performance flight control requirements, this paper presents a quadrotor anti-wind model (QAWM) and a flight control scheme for quadrotors. The QAWM takes the influence of aerodynamic effects on the propeller, gyroscopic effect and wind disturbance into account. The model can represent more flight states including not only hovering but also flight in windy conditions even maneuver flight. A cascade control scheme with an improved extended state observer (IESO) is adopted to decompose the quadrotor flight control problem into position control loop and attitude control loop. In the attitude control loop, the IESO is used to estimate the unmodeled dynamics, parameter uncertainties and external disturbances, as well as compensate the angular velocity control. In addition, the stability of IESO and the closed loop system are proved. Simulation and experimental results show the effectiveness of the nonlinear quadrotor model and control scheme, and the control scheme can effectively improve the flight performance of quadrotors under wind disturbance even maneuver flight.

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Authors and Affiliations

  1. School of Information and Control Engineering, Qingdao University of Technology, 266520, Qingdao, China

    Houyin Xi, Dong Zhang, Tao Zhou & Yunxiao Yang

  2. School of Physics and Electronic Engineering, Taishan University, 271000, Taian, China

    Qiang Wei

Authors
  1. Houyin Xi
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  2. Dong Zhang
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Correspondence to Dong Zhang.

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Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Recommended by Associate Editor Donjun Lee under the direction of Editor Chan Gook Park. This work is supported by the National Natural Science Foundation of China (No.61703225, 61803220), the Shandong Provincial Natural Science Foundation (ZR2017BF033).

Houyin Xi received his B.S. degree in automation from Qingdao University of Technology, Qingdao, China, in 2018. He is now pursuing an M.S. degree in the School of Information and Control Engineering, Qingdao University of Technology, Qingdao, China. His research interests include aircraft stability control and visual positioning.

Dong Zhang received his M.S. degree and Ph.D. degree in control theory and control engineering both from Shandong University, China, in 2006 and 2009, respectively. Now he is an Associate Professor in the School of Information and Control Engineering of Qingdao University of Technology, China. His current research interests include nonlinear control system, robotics and intelligent control.

Tao Zhou received his B.S. degree in electrical engineering and automation from Jiangsu Normal University, China, in 2017. He is now pursuing an M.S. degree in the School of Information and Control Engineering, Qingdao University of Technology, Qingdao, China. His research interests include manipulator control and visual servo.

Yunxiao Yang received his B.S. degree in automation from Xinyang Normal University in 2019. He is now pursuing an M.S. degree in the School of Information and Control Engineering, Qingdao University of Technology, Qingdao, China. His research interests include robot control and visual servo.

Qiang Wei received his M.S. degree and Ph.D. degree in control theory and control engineering both from Shandong University, China, in 2003 and 2006, respectively. He has been an Exchange Visiting Scholar in the Department of Computer Science of Utah State University from 2009 to 2010. Now he is a professor in the School of Physics and Electronic Engineering of the Taishan University, China. His current interest are in the area of nonlinear system, intelligent control and industrial production process automation.

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Xi, H., Zhang, D., Zhou, T. et al. An Anti-wind Modeling Method of Quadrotor Aircraft and Cascade Controller Design Based on Improved Extended State Observer. Int. J. Control Autom. Syst. 19, 1363–1374 (2021). https://doi.org/10.1007/s12555-019-0878-7

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