Advertisement

Adaptive Hybrid Impedance Control Algorithm Based on Subsystem Dynamics Model for Robot Polishing

  • Zihao LuoEmail author
  • Jianfei Li
  • Jie Bai
  • Yaobing Wang
  • Li Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11745)

Abstract

With the continuous application of robots, the accuracy requirements of robot control have been continuously improved. In the past, robot position control systems that can perform good palletizing, clamping, sorting, etc., have been unable to meet people’s needs. Therefore, based on theory, simulation and experimental verification, this paper proposes an adaptive hybrid impedance control algorithm based on subsystem dynamics model design, which reduces the computational complexity of the algorithm and solves the problem of inaccurate modeling. Related research and discussion in combination with grinding experiments for different surfaces.

Keywords

Subsystem kinetic model Adaptive control Hybrid impedance control Robot polishing system 

References

  1. 1.
    Anderson, R.J., Spong, M.W.: Hybrid impedance control of robotic manipulators. IEEE J. Robot. Autom. 4(5), 549–556 (1988)CrossRefGoogle Scholar
  2. 2.
    Luh, J.Y.S., Walker, M.W., Paul, R.P.C.: On-line computational scheme for mechanical manipulators. J. Dyn. Syst. Measur. Control 102(2), 69–76 (1980)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Zhu, W.H.: Virtual Decomposition Control: Toward Hyper Degrees of Freedom Robots. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-10724-5CrossRefGoogle Scholar
  4. 4.
    Hosseinzadeh, M., Aghabalaie, P., Talebi, H.A., et al.: Adaptive hybrid impedance control of robotic manipulators. In: IECON 2010-36th Annual Conference on IEEE Industrial Electronics Society, pp. 1442–1446. IEEE (2010)Google Scholar
  5. 5.
    Li, J., Liu, L., Wang, Y., et al.: Adaptive hybrid impedance control of robot manipulators with robustness against environment’s uncertainties. In: 2015 IEEE International Conference on Mechatronics and Automation (ICMA), pp. 1846–1851. IEEE (2015)Google Scholar
  6. 6.
    Wannagat, A., Vogel-Heuser, B.: Increasing flexibility and availability of manufacturing systems-dynamic reconfiguration of automation software at runtime on sensor faults. IFAC Proc. Vol. 41(3), 278–283 (2008)CrossRefGoogle Scholar
  7. 7.
    Chen, Y.H., Pandey, S.: Robust hybrid control of robot manipulators. In: Proceedings of IEEE International Conference on Robotics and Automation, vol. 1, pp. 236–241, 14–19 May 1989Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Zihao Luo
    • 1
    Email author
  • Jianfei Li
    • 1
  • Jie Bai
    • 1
  • Yaobing Wang
    • 1
  • Li Liu
    • 1
  1. 1.Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and ApplicationsBeijing Institute of Spacecraft System EngineeringBeijingChina

Personalised recommendations