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Flight and Hover Control System Design for a Mini-quadrotor Based on Multi-sensors

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  • Robot and Applications
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Abstract

Mini-quadrotor is difficult to control in the air due to its small size and light weight. This paper presents the flight and hover control system for a mini-quadrotor, including design and simulation of calculations and controllers. Firstly, the attitude and position of the mini-quadrotor are obtained by distributed multi-sensors. Since attitude calculation of aircraft needs a number of combined rotations and vectors transformed by rotation, quaternions are applied to express the attitude model. About error compensation of gyroscope and accelerometer, IMU_Updata algorithm of Mahony filter are applied and improved to realize data fusion [1]. In order to realize accurate hovering at certain position, UWB (UltraWideband) are applied to gain positional information of mini-quadrotor and correct the antenna delay caused sensor error by base station positioning. The discrete Kalman filter of original data is used to achieve the optimized estimation of the airborne position. Px4flow optical flow sensor is able to gets velocity information and avoid the noise problem, which is caused by differential of position data. Then, the mathematical model of a mini-quadrotor’s flight and hover control system can be established. Herein, integral items are solved by the integral separation and integral limiting to mitigate the serious overshoot and oscillation of the system caused by the cascade PID. Finally, the simulation of the attitude controller and position controller are applied with the MATLAB Simulink library. The simulation result shows that the designed attitude controller and position controller can enable the mini-quadrotor to fly smoothly, move in all directions and hover.

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Authors and Affiliations

  1. Department of Control Engineering in Chengdu University of Information Technology, No. 24 Xuefu Road, economic development zone of southwest airport, Chengdu, Sichuan, China

    Zhongli Ma

  2. College of Automation, Harbin Engineering University, Harbin, China

    Huixin Li & Qianqian Li

  3. School of Astronautics, Harbin Institute of Technology, Harbin, Heilongjiang, China

    Yanming Gu

  4. Fujian Provincial Key Laboratory of Information Processing and Intelligent Control, Minjiang University, Fuzhou, China

    Zuoyong Li

Authors
  1. Zhongli Ma
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  2. Huixin Li
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  3. Yanming Gu
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  4. Zuoyong Li
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  5. Qianqian Li
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Corresponding author

Correspondence to Huixin Li.

Additional information

Recommended by Associate Editor Son-cheol Yu under the direction of Editor Hyun-Seok Yang. The authors are grateful to College of Automation Harbin Engineering University and Fujian Provincial Key Laboratory of Information Processing and Intelligent Control of Minjiang University. This project is supported by National Natural Science Foundation of China (61772254) and Key Project of College Youth Natural Science Foundation of Fujian Province (JZ160467). The authors thank Ms Yifang Wang from South China University of Technology for her help in improving this paper.

Zhongli Ma received the Ph.D. degree in Automation from Harbin Engineering University, Harbin, China in 2006. Her research include machine vision and pattern recognition.

Huixin Li will receive the M.E. degree in Automation from Harbin Engineering University, Harbin, China in 2019. Her research interests include machine vision, pattern recognition and robot technology.

Yanming Gu received the Master degree in the School of Astronautics, Harbin Institute of Technology, Harbin, China in 2018. His research interests include aircraft control, pattern recognition and robot technology.

Zuoyong Li received the Ph.D. degree from the School of Computer Science and Technology at Nanjing University of Science and Technology, Nanjing (NUST), China, in 2010. His current research interests include image processing, pattern recognition and machine learning.

Qianqian Li received the M.E. degree in Automation from Harbin Engineering University, Harbin, China in 2018. Her research interests include machine vision, pattern recognition and robot technology.

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Ma, Z., Li, H., Gu, Y. et al. Flight and Hover Control System Design for a Mini-quadrotor Based on Multi-sensors. Int. J. Control Autom. Syst. 17, 486–499 (2019). https://doi.org/10.1007/s12555-017-0308-7

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  • DOI: https://doi.org/10.1007/s12555-017-0308-7

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