Journal of Bionic Engineering

, Volume 15, Issue 1, pp 114–125 | Cite as

The impulse excitation joint servo drive design and adaptive backstepping control of humanoid robots

  • Keqiang Bai
  • Minzhou Luo
  • Tao Li
  • Jue Wu


This study aims to explore the humanoid robot joint servo drive integration design and adaptive backstepping control. To make the humanoid robot have explosive power as the human does, simply increasing the power output of the motor of a lightweight design cannot meet the demand of moving heavy objects and so on. Moreover, the backstepping control algorithm is designed to implement the dual-arm cooperative control. The joint servo drive is redesigned in the present study, which can drive the motor at a limitation state when needed output high-voltage pulse can stimulate the motor so that the motor can produce an instantaneous large torque. A miniature design scheme is presented in this study for the servo drive, explaining the design method of each part module. The experimental data illustrate that the servo drive can produce an output torque greater than the rate of the high-voltage pulse that stimulates the motor. Knowledge of the control of humanoid robot moving a heavy object has important practical significance. The present study provides a complete actual problem and exhibits a real practical use case which can be used to speed up the explosive humanoid robot arms.


adaptive backstepping control bionic robot drive integration design impulse excitation servo drive 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.



This study was supported by the National Natural Science Foundation of China (grant no. 51405469) and the Project (Grant no. 17zx7157) of Scientific Research Foundation of Southwest University of Science and Technology.


  1. [1]
    Sathyan A, Milivojevic N, Lee Y J, Krishnamurthy M, Emadi A. An FPGA-based novel digital PWM control scheme for BLDC motor drives. IEEE Transactions on Industrial Electronics, 2009, 56, 3040–3049.CrossRefGoogle Scholar
  2. [2]
    Emadi A. Handbook of Automotive Power Electronics and Motor Drive, FL: CRC Press, Boca Raton, USA, 2005.CrossRefGoogle Scholar
  3. [3]
    Aboulnaga A A, Desai P C, Rodriguez F, Cooke T R, Emadi A. A novel, low-cost, high-performance single-phase adjustable- speed motor drive using PM brush-less DC machine: IIT’s design for 2003 future energy challenge. Applied Power Electronics Conference and Exposition, 2004, 3, 1595–1603.Google Scholar
  4. [4]
    Lu C W. Torque controller for brushless DC motors. IEEE Transactions on Industrial Electronics, 1999, 46, 471–473.CrossRefGoogle Scholar
  5. [5]
    Xia C L, Li Z Q, Shi T N. A control strategy for four-switch three phase brushless DC motor using single current sensor. IEEE Transactions on Industrial Electronics, 2009, 56, 2058–2066.CrossRefGoogle Scholar
  6. [6]
    Dubey R, Agarwal P, Vasantha M K. Programmable logic devices for motion control–A review. IEEE Transactions on Industrial Electronics, 2007, 54, 559–566.CrossRefGoogle Scholar
  7. [7]
    Jing Z H, Gao X S, Li H, Zeng Z. Observation of load torque and auto-tuning of pd regulator for space robot servo system based on a linear driver. Proceedings of IEEE International Conference on Mechatronics and Automation, Takamatsu, Japan, 2008, 622–626.Google Scholar
  8. [8]
    Lee J W, Kim T W. Design and experimental analysis of embedded servo motor driver for robot finger joints. Proceedings of IEEE International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), Incheon, Korea, 2011, 548–551.Google Scholar
  9. [9]
    Bahari M S, Jaffar A, Low C Y, Jaafar R, Roese K, Yussof H. Design and development of a multifingered prosthetic hand. International Journal of Social Robotics, 2012, 4, 59–66.CrossRefGoogle Scholar
  10. [10]
    Azidehak A, Hoshyari M, Sharbafi M A. Design and implementation of minimal components brushless DC motor driver for mobile robots. Proceedings of IEEE International Conference on Mechatronics (ICM), Istanbul, Turkey, 2011, 642–647.Google Scholar
  11. [11]
    Chen C Y, Lim K C, Li T H S. Design and implementation of intelligent driving controller for car-like mobile robot. Proceedings of IEEE International Conference on System Science and Engineering (ICSSE), Taipei, China, 2010, 463–468.Google Scholar
  12. [12]
    Kim D U, Hwang S W, Kang H J, Hong D S. Kinematic analysis of a humanoid robot CHP-1 and selection of motors in consideration of cooperative motion. Journal of Central South University of Technology, 2011, 18, 627–632.CrossRefGoogle Scholar
  13. [13]
    Książek M A, Łacny Ł. A comparison of the human body-seat model responses to several types of impulse excitations. Journal of Theoretical and Applied Mechanics, 2014, 52, 839–845.Google Scholar
  14. [14]
    Liebschner M A, Chun K, Kim N, Ehni B. In vitro biomechanical evaluation of single impulse and repetitive mechanical shockwave devices utilized for spinal manipulative therapy. Annals of Biomedical Engineering, 2014, 42, 2524–2536.CrossRefGoogle Scholar
  15. [15]
    Wang Y L, Jin Z L. Dynamics modeling and robust trajectory tracking control for a class of hybrid humanoid arm based on neural network. Chinese Journal of Mechanical Engineering, 2009, 22, 355–363.CrossRefGoogle Scholar
  16. [16]
    Tee K P, Yan R, Chua Y, Huang Z, Li H. Modular IK: A robust inverse kinematic algorithm for gesture imitation in upper-body humanoid robot. International Journal of Humanoid Robotics, 2012, 9, 1250010.CrossRefGoogle Scholar
  17. [17]
    Figueroa N B, Schmidt F, Ali H, Mavridis N. Joint origin identification of articulated robots with marker-based multi-camera optical tracking systems. Robotics and Autonomous Systems, 2013, 61, 580–592.CrossRefGoogle Scholar
  18. [18]
    Paine N, Mehling J S, Holley J, Radford N A, Johnson G, Fok C L, Sentis L. Actuator control for the NASA-JSC valkyrie humanoid robot: A decoupled dynamics approach for torque control of series elastic robots. Journal of Field Robotics, 2015, 32, 378–396.CrossRefGoogle Scholar
  19. [19]
    Gonçalves V M, Fraisse P, Crosnier A, Adorno B V. Parsimonious kinematic control of highly redundant robots. IEEE Robotics and Automation Letters, 2016, 1, 65–72.CrossRefGoogle Scholar
  20. [20]
    Qiu J, Wei Y, Karimi H R. New approach to delay- dependent H8 control for continuous-time Markovian jump systems with time-varying delay and deficient transition descriptions. Journal of the Franklin Institute, 2015, 352, 189–215.MathSciNetCrossRefzbMATHGoogle Scholar
  21. [21]
    Qiu J, Gao H, Ding S X. Recent advances on fuzzymodel- based nonlinear networked control systems: A survey. IEEE Transactions on Industrial Electronics, 2016, 63, 1207–1217.CrossRefGoogle Scholar
  22. [22]
    He J, Luo M Z, Zhang Q Q, Zhao J H, Xu L S. Adaptive fuzzy sliding mode controller with nonlinear observer for redundant manipulators handling varying external force. Journal of Bionic Engineering, 2016, 13, 600–611.CrossRefGoogle Scholar
  23. [23]
    He W, Chen Y, Yin Z. Adaptive neural network control of an uncertain robot with full-state constraints. IEEE Transactions on Cybernetics, 2016, 46, 620–629.CrossRefGoogle Scholar
  24. [24]
    He W, Dong Y, Sun C. Adaptive neural impedance control of a robotic manipulator with input saturation. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2016, 46, 334–344.CrossRefGoogle Scholar
  25. [25]
    He W, Ouyang Y, Hong J. Vibration control of a flexible robotic manipulator in the presence of input dead zone. IEEE Transactions on Industrial Informatics, 2017, 13, 48–59.CrossRefGoogle Scholar
  26. [26]
    He W, Dong Y. Adaptive fuzzy neural network control for a constrained robot using impedance learning. IEEE Transactions on Neural Networks and Learning Systems, 2017, 99, 1–13.CrossRefGoogle Scholar
  27. [27]
    Gan Y, Dai X. Human-like manipulation planning for articulated manipulator. Journal of Bionic Engineering, 2012, 9, 434–445.CrossRefGoogle Scholar
  28. [28]
    He W, Ge W, Li Y, Liu Y J, Yang C, Sun C. Model identification and control design for a humanoid robot. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017, 47, 45–57.CrossRefGoogle Scholar
  29. [29]
    Dai J, Ludois D C. Single active switch power electronics for kilowatt scale capacitive power transfer. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2015, 3, 315–323.CrossRefGoogle Scholar
  30. [30]
    Subramanian V, Manimaran S. Design of parallel-operated SEPIC converters using coupled inductor for load-sharing. Journal of Power Electronics, 2015, 15, 327–337.CrossRefGoogle Scholar
  31. [31]
    Bai K Q, Luo M Z, Liu M L, Jiang G W. Dynamics model and adaptive backstepping control on the 7-DOF manipulators of a humanoid robot. Proceedings of IEEE International Conference on Information and Automation, Ningbo, China, 2016, 1032–1038.Google Scholar

Copyright information

© Jilin University 2018

Authors and Affiliations

  1. 1.Southwest University of Science and TechnologyMianyangChina
  2. 2.Department of Automation, School of Information Science of TechnologyUniversity of Science and Technology of ChinaHefeiChina
  3. 3.Institute of Advanced Manufacturing and Technology, Hefei Institute of Physical ScienceChinese Academy of SciencesChangzhouChina

Personalised recommendations