Backstepping sliding mode controller improved with fuzzy logic: Application to the quadrotor helicopter

Open access

Abstract

In this paper we present a new design method for the fight control of an autonomous quadrotor helicopter based on fuzzy sliding mode control using backstepping approach. Due to the underactuated property of the quadrotor helicopter, the controller can move three positions (x;y; z) of the helicopter and the yaw angle to their desired values and stabilize the pitch and roll angles. A first-order nonlinear sliding surface is obtained using the backstepping technique, on which the developed sliding mode controller is based. Mathematical development for the stability and convergence of the system is presented. The main purpose is to eliminate the chattering phenomenon. Thus we have used a fuzzy logic control to generate the hitting control signal. The performances of the nonlinear control method are evaluated by simulation and the results demonstrate the effectiveness of the proposed control strategy for the quadrotor helicopter in vertical flights.

References
  • [1] D.LEE, H. JIN KIM and S.SASTRY: Feedback dinearization vs. adaptive sliding mode control for a quadrotor helicopter. Int. J. of Control, Automation, and Systems, 7(3), (2009), 419-428.

  • [2] A.TAYEBI and S. MCGILVRAY: Attidude stabilisation of a VTOL quadrotor aircraft. IEEE Trans. on Control Systems Technology, 14(3), (2006).

  • [3] L. DERAFA and T. MADANI and A. BENALLEGUE: Dynamic modelling and experimental identification of four rotor helicopter parameters. IEEE Conf. on IndustrialTechnology, Mumbai, India (2006).

  • [4] S. BOUABDALLAH, A. NOTH and R. SIEGWART: PID vs LQ control techniques applied to an indoor micro quadrotor. Autonomous Systems Laboratory, Swiss Federal Institute of Technology Lausanne, Switzerland, 2004.

  • [5] M. BOUCHOUCHA, M. TADJINE, A. TAYEBI and P. M ULLHAUPT: Step by step robust nonlinear PI for attitude stabilisation of a four-rotor mini-aircraft. 16thMediterranean Conf. on Control and Automation, Ajaccio, France, (2008).

  • [6] Y. AI-YOUNES and M. JARRAH: Attitude stabilization of quadrotor UAV using backstepping fuzzy logic backstepping least-mean-square controllers. Proc. of the5th Int. Symp. on Mechatronics and its Applications, Amman, Jordan, (2008).

  • [7] T. MADANI and A. BENALLEGUE: Control of a quadrotor mini-helicopter via full state backstepping technique. Proc. of the 45th IEEE Conf. on Decision & Control, San Diego, CA, USA, (2006).

  • [8] S. BOUABDALLAH and R. SIEGWART: Backstepping and sliding-mode techniques applied to an indoor micro quadrotor. Proc. of the 2005 IEEE Int. Conf. on Roboticsand Automation, Barcelona, Spain, (2005).

  • [9] E. ALTUG, J.P. OSTROWSKI and R. MAHONY: Control of a quadrotor helicopter using visual feedback. Prec of the 2002 IEEE Int. Conf. on Robotics and Automation, Washington, USA, (2002).

  • [10] A. DAS, F. LEWIS and K.SUBBARAO: Backstepping approach for controlling a quadrotor using Lagrange form dynamics. J. of Intelligent and Robototic Systems, 56 (2009), 127-151.

  • [11] A. MOKHTARI, A. BENALLEGUE and B. DAACHI: Robust feedback linearization and GH∞ controller for a quadrotor unmanned aerial vehicle. J. of ElectricalEngineering, 57(1), (2006), 20-27.

  • [12] A. AHMAD MIAN and W. DAOBO: Modeling and backstepping-based nonlinear control strategy for a 6 DOF quadrotor helicopter. Chinese J. of Aeronautics, 21 (2008), 261-268.

  • [13] C. COZA and C.J.B. MACNAB: A new robust adaptive-fuzzy control method applied to quadrotor helicopter stabilization. Fuzzy Information Processing Society,Annual meeting of the North American. (2006), 454-458.

  • [14] K.M. ZEMALACHE and H. MAAREF: Controlling a drone: Comparison between a based model method and a fuzzy inference system. Applied Soft Computing, 9 (2009), 553-562.

  • [15] G.V. RAFFO, M.G. ORTEGA and F.R. RUBIO: An integral predictive/nonlinear H∞ control structure for a quadrotor helicopter. 46(1), Automatica, (2010), 29-39.

  • [16] V.I. UTKIN: Sliding Modes in Control and Optimization. Springer-Verlag, 1992.

  • [17] RONG XU and UMIT OZG UNER: Sliding mode control of a class of underactuated systems. Automatica, 44 (2008), 233-241.

  • [18] Z. FANG, Z. ZHI, L. JUN and W. JIAN: Feedback linearization and continuous sliding mode control for a quadrotor UAV. Proc. of the 27th Chinese Control Conf., Kunming, Yunnan, China, (2008).

  • [19] T. MADANI and A. BENALLEGUE: Backstepping sliding mode control applied to a miniature quadrotor flying robot. IEEE Conf. on Industrial Electronics, Paris, France, (2006).

  • [20] F. XIANG: Block-oriented nonlinear control of pneumatic actuator systems. Doctoral thesis. Department of Machine Design, Royal Institute of Technology, Sweden, 2001.

  • [21] B. MOSHIRI, M. JALILI-KHARAAJOO and F. BESHARATI: Application of fuzzy sliding mode based on genetic algorithms to control of robotic manipulators. Proc.IEEE, of Int. Conf. on Emerging Technologies and Factory Automation, (2003), 169-172.

  • [22] J.Z. LIU, W.J. ZHAO and L.J. ZHANG: Design of sliding mode controller based on fuzzy logic. Proc. of the 3rd IEEE Conf. on Machine Learning and Cybernetics, IEEE Press, Shanghai, China, (2004), 616-619.[23] S.W. KIM and J.J. LEE: Design of a fuzzy controller with fuzzy sliding surface. Fuzzy Sets and Systems, 71(3), (1995), 359-367.

Archives of Control Sciences

The Journal of Polish Academy of Sciences

Journal Information


IMPACT FACTOR 2016: 0.705

CiteScore 2016: 3.11

SCImago Journal Rank (SJR) 2016: 0.231
Source Normalized Impact per Paper (SNIP) 2016: 0.565

Metrics

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 41 41 20
PDF Downloads 11 11 5