Fuzzy modeling and control for a nonlinear quadrotor under network environment

This paper considers the fuzzy modeling and H∞ state feedback control for network-based quadrotor under unreliable communication links, and there are delays and packet dropouts throughout the transmission. The nonlinear quadrotor in this paper is firstly approximated by a Takagi-Sugeno (T-S) fuzzy model. The network-induced delays and packet dropouts in both sensor-to-controller (S/C) and controller-to-actuator (C/A) channels are modeled in a unified framework. Then a fuzzy controller is designed so that the resulting closed-loop quadrotor system is asymptotically stable with guaranteed H∞ performance. Finally, a simulation is given to illustrated the procedure of the proposed approach.

[1]  Zehui Mao,et al.  $H_\infty$-Filter Design for a Class of Networked Control Systems Via T–S Fuzzy-Model Approach , 2010, IEEE Transactions on Fuzzy Systems.

[2]  Radhakant Padhi,et al.  Simultaneous attitude control and trajectory tracking of a micro quadrotor: A SNAC aided nonlinear dynamic inversion approach , 2013, 2013 American Control Conference.

[3]  J. Jim Zhu,et al.  Attitude tracking control of a quadrotor UAV in the exponential coordinates , 2013, J. Frankl. Inst..

[4]  Abdelaziz Benallegue,et al.  Nonlinear H ∞ control of a Quadrotor (UAV), using high order sliding mode disturbance estimator , 2012, Int. J. Control.

[5]  S. Lesecq,et al.  Hybrid priority scheme for networked control quadrotor , 2009, 2009 17th Mediterranean Conference on Control and Automation.

[6]  Gang Feng,et al.  Analysis and Synthesis of Fuzzy Control Systems , 2010 .

[7]  Antonio Sala,et al.  Application of Takagi-Sugeno observers for state estimation in a quadrotor , 2011, IEEE Conference on Decision and Control and European Control Conference.

[8]  G. Raffo,et al.  An integral predictive / nonlinear H ∞ control structure for a quadrotor helicopter , 2009 .

[9]  M. Moghavvemi,et al.  Modelling and PID controller design for a quadrotor unmanned air vehicle , 2010, 2010 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR).

[10]  Kazuo Tanaka,et al.  Fuzzy modeling via sector nonlinearity concept , 2003 .

[11]  Jianbin Qiu,et al.  A novel dropout compensation scheme for control of networked T-S fuzzy dynamic systems , 2014, Fuzzy Sets Syst..

[12]  Roland Siegwart,et al.  Design and control of an indoor micro quadrotor , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[13]  Shashi Bhushan Mohanty H∞ Filter Design for Networked Control System , 2016 .

[14]  G. Feng,et al.  A Survey on Analysis and Design of Model-Based Fuzzy Control Systems , 2006, IEEE Transactions on Fuzzy Systems.