Design and Hardware Implementation of Autopilot Control Laws for MAV Using Super Twisting Control

  • R. Guruganesh
  • B. Bandyopadhyay
  • Hemendra Arya
  • G. K. Singh


In this paper we present the design and implementation of autopilot tracking control law for Micro Aerial Vehicle using the second order sliding mode approach. The inner loop attitude tracking control design is carried out using output feedback based second order sliding mode technique, to ensure finite time convergence of the tracking error dynamics. While addressing tracking control of a time varying reference signal, it is important to investigate the stability characteristics of the internal dynamics to ensure perfect tracking. This paper mainly addresses the output tracking control problem for a MAV and investigate the stability characteristics of the longitudinal zero dynamics during tracking. We have proposed a stability proof based on Lyapunov theory to analyze the stability of the MAV longitudinal zero dynamics during tracking. A nonlinear aircraft model obtained using aerodynamic derivatives of The Blackkite 300 mm wingspan fixed MAV is used for both control design and as well as to verify its performance against the classical control methods. Extensive hardware in-loop simulation results of the proposed control algorithm implemented on the commercially available PX4 based Pixhawk autopilot board are also presented here.


Micro aerial vehicle Zero dynamics Super twisting control Time varying reference Autopilot Hardware-in-loop 



Airspeed (m/s)


Velocity in body x axis (m/s)


Velocity in body y axis (m/s)


Velocity in body z axis (m/s)


Angle of Attack (rad)


Sideslip angle (rad)


Flight path angle (rad)


Bank angle (rad)


Pitch angle (rad)


Yaw angle (rad)


Roll rate (rad/s)


Pitch rate (rad/s)


Yaw rate (rad/s)


Altitude (m)

\(\bar {q}\)

Dynamic Pressure kg/ms 2


Elevator deflection (rad)


Aileron deflection (rad)


Thrust (N)

X, Y, Z

Inertial/NED frame coordinates

x, y, z

Aircraft body axes coordinates


Desired altitude


Commanded pitch angle


Desired heading angle


Commanded bank angle


Error Vector


No of states of a system


Relative degree


Sliding surface


Lyapunov function


Coefficient of lift


Coefficient of Drag


Coefficient of force in the x direction


Coefficient of force in the y direction


Coefficient of force in the z direction


Rolling moment coefficient


Pitching moment coefficient


Yawing moment coefficient


C L at zero degree α


C m at zero degree α


C L at minimum drag


Minimum drag coefficient

\(C_{L\alpha , \delta _{e}, q}\)

Change in C L w.r.t to change in α/δ e /q

\(C_{D\delta _{e}, \delta _{a}}\)

Change in C D w.r.t to change in δ e /δ a

\(C_{m\alpha , \delta _{e}, q}\)

Change in C m w.r.t to change in α/δ e /q

\(C_{y\beta , p, r, \delta _{a}}\)

Change in C y w.r.t to change in β/p/r/δ a

\(C_{l\beta , p, r, \delta _{a}}\)

Change in C l w.r.t to change in β/p/r/δ a

\(C_{n\beta , p, r, \delta _{a}}\)

Change in C n w.r.t to change in β/p/r/δ a


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Authors would like to acknowledge Mr. Swaroop Hangal and Mr. Dileep Krishnan, for their selfless help in setting up of hardware in-loop simulation. This facility was created by funding support from National Programme on Micro Aerial Vehicle (NPMICAV). Authors also acknowledges Dr. Kamali and team FMCD, CSIR-NAL for the help provided in developing the 6DoF simulation model of the Blackkite MAV.


  1. 1.
    Haiyang, C., Youngcan, C., Yangquan, C.: Autopilots for small unmanned aerial vehicles: A survey. Int. J. Control. Autom. Syst. 8(1), 36–44 (2010)CrossRefGoogle Scholar
  2. 2.
    Kendoul, F.: Survey of advances in guidance, navigation and control of unmanned rotorcraft systems. J. Field Rob. 20(3), 315–378 (2012)CrossRefGoogle Scholar
  3. 3.
    Mc Lean, D.: Automatic flight control systems prentice hall. Englewoods Cliffs, USA (1990)Google Scholar
  4. 4.
    Beard, R.W., Mc, T.W.: Small unmanned aircraft: theory and practice, 1st edn. rinceton University Press, Princeton (2011)Google Scholar
  5. 5.
    Utkin, V.I.: Variable structure systems with sliding modes. IEEE Trans. Autom. Control 22(2), 212–222 (1977)MathSciNetCrossRefzbMATHGoogle Scholar
  6. 6.
    Edwards, C., Spurgeon, S.K.: Sliding Mode Control Theory and Applications. Taylor and Francis, London (1998)zbMATHGoogle Scholar
  7. 7.
    Haimo, V.T.: Finite time controllers. SIAM J. Control. Optim. 24(44), 760–770 (1986)MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    Bhat, S.P., Bernstein, D.S.: Finite time stability of homogeneous systems. In: Proceedings of American control conference, Albuquerque, New Mexico, pp. 2513–2514 (1997)Google Scholar
  9. 9.
    Bartolini, G., Alessandro, P., Elisabetta, P., Usai, E.: A survey of applications of second order sliding mode control to mechanical systems. Int. J. Control 76(9), 875–892 (2013)MathSciNetzbMATHGoogle Scholar
  10. 10.
    Shtessel, Y., Edwards, C., Fridman, L., Levant, A.: Sliding mode control and observation control engineering series. Springer, London (2013)Google Scholar
  11. 11.
    Levant, A., Pridor, A.: Sliding order and sliding accuracy in Sliding Mode Control. Int. J. Control 58(6), 1247–1263 (1993)MathSciNetCrossRefzbMATHGoogle Scholar
  12. 12.
    Levant, A., Pridor, A.: Aircraft pitch control via second order sliding technique. AIAA J. Guid. Control. Dyn. 23(4), 586–594 (2000)CrossRefGoogle Scholar
  13. 13.
    Levant, A.: Principles of 2-Sliding mode design. Automatica 43(4), 576–586 (2007)MathSciNetCrossRefzbMATHGoogle Scholar
  14. 14.
    Samar, R., Ahmed, S., Nzar, M.: Lateral guidance and control design for an Unmanned Aerial Vehicle. In: Proceedings of 17th IFAC world congress, COEX, South Korea, vol. 17, pp. 4737–4742 (2008)Google Scholar
  15. 15.
    Yamasaki, T., Balakrishnan, S.N., Takano, H.: Integrated guidance and autopilot for a path following UAV via high-order sliding modes. In: Proceeding of American Control Conference, June 27-29, Montreal, Canada, pp.143–148 (2012)Google Scholar
  16. 16.
    Syed, U.A., Zamurad, M.S., Samar, R.: Lateral control of UAVs trajectory tracking via higher-order sliding modes. In: Proceedings of 9th Asian Control conference, June 23-26, Istanbul, pp. 1–6 (2013)Google Scholar
  17. 17.
    Shah, M.Z., Samar, R., Bhatti, A.I.: Guidance of air vehicles a sliding mode approach. IEEE Trans. Control Syst. Technol. 23(1), 231–244 (2015)CrossRefGoogle Scholar
  18. 18.
    Davila, J., Monsivias, A., Mosqueda, A.: High-order sliding modes based linearization: An application to roll autopilot. In: Proceedings of the MUSME Conference, Huatulco, Mexico, pp. 273–284 (2014)Google Scholar
  19. 19.
    Zhou, W., Zhu, P., Wnag, C., Chu, M.: Position and attitude tracking control for a Quadrotor UAV Based on terminal sliding mode control. In: Proceedings of 34th Chinese Control conference, July 28-30, Hangzhou, China, pp. 3398–3304 (2015)Google Scholar
  20. 20.
    Derafa, L., Benallegue, A., Fridman, L.: Super twisting control algorithm for the attitude tracking of a four rotors UAV. J. Frankl. Inst. 349, 685–699 (2012)MathSciNetCrossRefzbMATHGoogle Scholar
  21. 21.
    Slotine, J.J.E., Li, W.: Applied nonlinear control Prentice Hall Inc. Englewood Cliffs, USA (1995)Google Scholar
  22. 22.
    Isidori, A.: Nonlinear control systems, communication and control engineering series, 3rd edn. Springer Verlog, London (1995)Google Scholar
  23. 23.
    Nelson, R.C.: Flight Stability and Automatic Control, 2nd edn. Mc.Graw-Hill higher education, USA (1997)Google Scholar
  24. 24.
    Stevens, L.F.L.: Aircraft Control and Simulation, 2nd edn. Wiley, New York (2003)Google Scholar
  25. 25.
    Kamali, C., Navendu, K.: A Report on Development of Nonlinear Derivative Model Based 6DOF Simulation for BlackKite MAV, NPMICAV, D-1-153/TM001 15th January 2012. CSIR-NAL, India (2012)Google Scholar
  26. 26.
    HAL: A Report on Low Speed Test Results of 1:1 Scale MAV Models, Report No.: HAL/ARDC/MAV/WNT/001, 20th, September 2010, Aircraft Research and Design Center, Design Complex, Hindustan Aeronautics limited, Bangalore, India (2010)Google Scholar
  27. 27.
    Moreno, J.A.: A linear framework for the robust stability analysis of a generalized super-twisting algorithm. In: Proceedings of 6th IEEE Conference on Electrical, Computing Science and Automatic control, CCE2009, Toluca, Mexico, pp. 1–6 (2009)Google Scholar
  28. 28.
    Guruganesh, R., Bandyopadhyay, B., Arya, H., Singh, G.K.: Design of Autopilot Control Laws for MAV using Super Twisting Control. In: Proceedings of 4th IFAC International Conference on ACODS, NIT Tiruchirapalli, India, February 01-05, pp. 736–741 (2016)Google Scholar
  29. 29.
    Morton, B., Enns, D., Zhang, B.Y.U.: Stability of dynamic inversion control laws applied to nonlinear aircraft pitch axis models, Institute for Mathematics and applications, IMA preprint series, University of Minnesota, vol. 1245 (1994)Google Scholar
  30. 30.
    Guruganesh, R., Viswanathan, S.: A Report on Evaluation of Autopilot Control Laws for 300 Mm Wing Span Blackkite MAV, Report No. D-1-153/TM004, 15th March 2012 Flight Mechanics and Controls Division, CSIR-NAL, India (2012)Google Scholar
  31. 31.
    Stengel, R.F.: Flight dynamics. Princeton University Press, New Jersey (2004)Google Scholar
  32. 32.
    Derek, R.N., Blake, D.B., Mc, T., Randal, B.: Vector field path following for miniature air vehicles. IEEE Trans. Robot. 23(3), 519–529 (2007)CrossRefGoogle Scholar
  33. 33.
    Dileep, K., Borkar, A.V.: Hemendra Arya An elegant hardware in loop simulation for cooperative missions of MAVs. In: Proceedings of AIAA Infotech Aerospace Conference, Garden Grove, California, USA, June 19-21, pp. 1–15 (2012)Google Scholar
  34. 34.
    Gade, M.M.: Implementation of Obstacle Avoidance Algorithms for MAVs in HILS, Master’s Thesis (Roll No:133014010) Department of Aerospace Engineering. Indian Institute of Technology, Bombay (2015)Google Scholar
  35. 35.
    ESC100 - Quatech serial card (website), Quatech ESC100 D9 RS 232 serial card, BB electronics,, Documentation number: XSC-100-200-300x-0813, pp.1-3
  36. 36.
    PCI-6229 ADC (website), NI PCI 6229 data acquisition card, National Instruments,
  37. 37.
    Pixhawk Open Source Autopilot (website): PX4 based Pixhawk Autopilot (PX4FMU + PX4IO),
  38. 38.
    Honegger, M.L., Pollefeys, M.: PX4: A Node-based multithreaded open source robotics framework for deeply embedded platforms. In: Proceedings of IEEE International Conference on Robotics and Automation, Seattle, WA, pp. 6235–6240 (2015)Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  • R. Guruganesh
    • 1
  • B. Bandyopadhyay
    • 2
  • Hemendra Arya
    • 3
  • G. K. Singh
    • 1
  1. 1.Flight Mechanics and Control DivisionCSIR-NALBangaloreIndia
  2. 2.IDP in Systems and Control EngineeringIndian Institute of Technology BombayPowaiIndia
  3. 3.Aerospace Engineering DepartmentIndian Institute of Technology BombayPowaiIndia

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