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Modeling and Neuro-Fuzzy adaptive attitude control for Eight-Rotor MAV

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Abstract

This paper focuses on modeling and intelligent control of the new Eight-Rotor MAV which is used to solve the problem of low coefficient proportion between lift and gravity for Quadrotor MAV. The dynamical and kinematical modeling for the Eight-Rotor MAV was developed which has never been proposed before. Based on the achieved dynamic modeling, two types of controller were presented. One type, a PID controller is derived in a conventional way with simplified dynamics and turns out to be quite sensitive to sensor noise as well as external perturbation. The second type controller is the Neuro-Fuzzy adaptive controller which is composed of two type-II fuzzy neural networks (TIIFNNs) and one PD controller: The PD controller is adopted to control the attitude, one of the TIIFNNs is designed to learn the inverse model of Eight-Rotor MAV on-line, the other one is the copy of the former one to compensate for model errors and external disturbances, both structure and parameters of T-IIFNNs are tuned on-line at the same time, and then the stability of the Eight-Rotor MAV closed-loop control system is proved using Lyapunov stability theory. Finally, the validity of the proposed control method has been verified through real-time experiments. The experimental results show that the performance of Neuro-Fuzzy adaptive controller performs very well under sensor noise and external disturbances, and has more superiority than traditional PID controller.

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Authors and Affiliations

  1. Chang Chun Institute of Optics Fine Mechanics and Physics, Chinese Academy of Sciences, Chang Chun, China

    Xiangjian Chen & Di Li

  2. Chinese Academy of Sciences, Chang Chun, China

    Yue Bai & Zhijun Xu

Authors
  1. Xiangjian Chen
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  2. Di Li
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  3. Yue Bai
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  4. Zhijun Xu
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Corresponding authors

Correspondence to Xiangjian Chen or Zhijun Xu.

Additional information

Recommended by Editorial Board member Young Jae Lee under the direction of Editor Jae Weon Choi.

This work was supported by National Natural Science Foundation of China NSFC 50905174.

Xiangjian Chen is a Ph.D. student at the Department of Mechanical and Electronic Engineering, Chang Chun Institute of Optics Fine Mechanics and Physics, Chinese Academy of Sciences, China. She received her Master degree at university of North East Dian Li. Her research interests include intelligent control and Micro aircraft vehicle.

Di Li studies embedded operation system and control, and he is a Ph.D. student at the Department of Mechanical and Electronic Engineering, Chang Chun Institute of Optics Fine Mechanics and Physics, Chinese Academy of Sciences, China. His interests include embedded operation system, image processing and Micro aircraft vehicle.

Yue Bai received his Ph.D. degree at the Department of Mechanical and Electronic Engineering, Chang Chun Institute of Optics Fine Mechanics and Physics, Chinese Academy of Sciences, China in 2006. His interests include automatic control and dynamics for MAV, and friction lubrication, space flywheel practical technology under extreme conditions.

Zhijun Xu is serving as Ph.D. supervisor and working at Chang Chun Institute of Optics Fine Mechanics and Physics, Chinese Academy of Sciences, China. His interests include automatic control and electronics.

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Chen, X., Li, D., Bai, Y. et al. Modeling and Neuro-Fuzzy adaptive attitude control for Eight-Rotor MAV. Int. J. Control Autom. Syst. 9, 1154–1163 (2011). https://doi.org/10.1007/s12555-011-0617-1

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  • DOI: https://doi.org/10.1007/s12555-011-0617-1

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