Time Constant and Model-Free Signal Prediction in Communication Channel of Teleoperation System

  • Mateusz SakówEmail author
  • Arkadiusz Parus
  • Mirosław Pajor
  • Karol Miądlicki
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 934)


In the paper a sensor-less control scheme for a bilateral teleoperation system with a force-feedback based on a model-free prediction in the communication channel by prediction blocks was presented. The prediction block was designed to minimize the effect of the transport delay in the communication channel of bilateral teleoperation system. The single prediction block has been a phase shifter with a specific behavior. The specific behavior of the prediction block is a strongly linear phase diagram in a useful frequency spectrum which allows the system to predict the manipulator motion and the force with a close to constant time shift. Another important feature is a gain of the block which is close to a unity when system operates in the useful frequency spectrum. The solution is an alternative to complex and mostly non-linear methods presented in the literature. The effectiveness of the method has been verified on the hydraulic manipulator test stand under control of many operators.


Signal prediction Remote control Telemanipulation Time delay 



The work was carried out as part of the PBS3/A6/28/2015 project, “The use of augmented reality, interactive voice systems and operator interface to control a crane”, financed by NCBiR.


  1. 1.
    Arcara, P., Melchiorri, C., Stramigioli, S.: Intrinsically passive control in bilateral teleoperation mimo systems. In: 2001 European Control Conference (ECC) (2001)Google Scholar
  2. 2.
    Atashzar, S.F., Polushin, I.G., Patel, R.V.: Projection-based force reflection algorithms for teleoperated rehabilitation therapy. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (2013)Google Scholar
  3. 3.
    Chang, M.-K.: An adaptive self-organizing fuzzy sliding mode controller for a 2-DOF rehabilitation robot actuated by pneumatic muscle actuators. Control Eng. Pract. 18(1), 13–22 (2010)CrossRefGoogle Scholar
  4. 4.
    Ferrell, W.R.: Remote manipulation with transmission delay. IEEE Trans. Hum. Fact. Electron. HFE-6(1), 24–32 (1965)CrossRefGoogle Scholar
  5. 5.
    Ferrell, W.R.: Delayed force feedback. Hum. Fact.: J. Hum. Fact. Ergon. Soc. 8(5), 449–455 (1966)CrossRefGoogle Scholar
  6. 6.
    Ferrell, W.R., Sheridan, T.B.: Supervisory control of remote manipulation. IEEE Spectr. 4(10), 81–88 (1967)CrossRefGoogle Scholar
  7. 7.
    Ge, X., et al.: Analysis of a model-free predictor for delay compensation in networked systems. In: Time Delay Systems, pp. 201–215. Springer, Heidelberg (2017)Google Scholar
  8. 8.
    Hastrudi-Zaad, K., Salcudean, S.E.: On the use of local force feedback for transparent teleoperation. In: Proceedings of 1999 IEEE International Conference on Robotics and Automation (1999)Google Scholar
  9. 9.
    Hulin, T., Albu-Schäffer, A., Hirzinger, G.: Passivity and stability boundaries for haptic systems with time delay. IEEE Trans. Control Syst. Technol. 22(4), 1297–1309 (2014)CrossRefGoogle Scholar
  10. 10.
    Kaya, I.: Obtaining controller parameters for a new PI-PD Smith predictor using autotuning. J. Process Control 13(5), 465–472 (2003)CrossRefGoogle Scholar
  11. 11.
    Kim, W.S.: Developments of new force reflecting control schemes and an application to a teleoperation training simulator. In: Proceedings of 1992 IEEE International Conference on Robotics and Automation (1992)Google Scholar
  12. 12.
    Kim, W.S., Hannaford, B., Fejczy, A.K.: Force-reflection and shared compliant control in operating telemanipulators with time delay. IEEE Trans. Robot. Autom. 8(2), 176–185 (1992)CrossRefGoogle Scholar
  13. 13.
    Lawrence, D.A.: Stability and transparency in bilateral teleoperation. IEEE Trans. Robot. Autom. 9(5), 624–637 (1993)CrossRefGoogle Scholar
  14. 14.
    Lichiardopol, S., Van De Wouw, N., Nijmeijer, H.: Control scheme for human-robot co-manipulation of uncertain, time-varying loads. In: 2009 American Control Conference (2009)Google Scholar
  15. 15.
    Miądlicki, K., Pajor, M.: Overview of user interfaces used in load lifting devices. Int. J. Sci. Eng. Res. 6(9), 1215–1220 (2015)Google Scholar
  16. 16.
    Miądlicki, K., Pajor, M.: Real-time gesture control of a CNC machine tool with the use Microsoft Kinect sensor. Int. J. Sci. Eng. Res. 6(9), 538–543 (2015)Google Scholar
  17. 17.
    Moreau, R., et al.: Sliding-mode bilateral teleoperation control design for master–slave pneumatic servo systems. Control Eng. Pract. 20(6), 584–597 (2012)CrossRefGoogle Scholar
  18. 18.
    Nguyen, T., et al.: Accurate sliding-mode control of pneumatic systems using low-cost solenoid valves. IEEE/ASME Trans. Mechatron. 12(2), 216–219 (2007)CrossRefGoogle Scholar
  19. 19.
    Niemeyer, G., Slotine, J.J.E.: Stable adaptive teleoperation. IEEE J. Ocean. Eng. 16(1), 152–162 (1991)CrossRefGoogle Scholar
  20. 20.
    Pajor, M., Miądlicki, K., Saków, M.: Kinect sensor implementation in FANUC robot manipulation. Arch. Mech. Technol. Autom. 34(3), 35–44 (2014)Google Scholar
  21. 21.
    Polushin, I.G., Takhmar, A., Patel, R.V.: Projection-based force-reflection algorithms with frequency separation for bilateral teleoperation. IEEE/ASME Trans. Mechatron. 20(1), 143–154 (2015)CrossRefGoogle Scholar
  22. 22.
    Rakotondrabe, M., et al.: Simultaneous displacement/force self-sensing in piezoelectric actuators and applications to robust control. IEEE/ASME Trans. Mechatronics. 20(2), 519–531 (2015)CrossRefGoogle Scholar
  23. 23.
    Saków, M., Miądlicki, K., Parus, A.: Self-sensing teleoperation system based on 1-DoF pneumatic manipulator. J. Autom. Mob. Robot. Intell. Syst. 11(1), 64–76 (2017)Google Scholar
  24. 24.
    Saków, M., Pajor, M., Parus, A.: Estymacja siły oddziaływania środowiska na układ zdalnie sterowany ze sprzężeniem siłowym zwrotnym o kinematyce kończyny górnej. Modelowanie Inzynierskie 58, 113–122 (2016)Google Scholar
  25. 25.
    Saków, M., Parus, A.: Sensorless control scheme for teleoperation with force-feedback, based on a hydraulic servo-mechanism, theory and experiment. Meas. Autom. Monit. 62(12) (2016)Google Scholar
  26. 26.
    Sheridan, T.B.: Space teleoperation through time delay: review and prognosis. IEEE Trans. Robot. Autom. 9(5), 592–606 (1993)CrossRefGoogle Scholar
  27. 27.
    Sheridan, T.B., Ferrell, W.R.: Human control of remote computer-manipulators. In: Proceedings of the 1st International Joint Conference on Artificial Intelligence, pp. 483–494. Morgan Kaufmann Publishers Inc., Washington, DC 1969Google Scholar
  28. 28.
    Stuart, K.D., Majewski, M.: Intelligent opinion mining and sentiment analysis using artificial neural networks. In: International Conference on Neural Information Processing. Springer, Heidelberg (2015)Google Scholar
  29. 29.
    Stuart, K.D., Majewski, M., Trelis, A.B.: Intelligent semantic-based system for corpus analysis through hybrid probabilistic neural networks. In: International Symposium on Neural Networks. Springer, Heidelberg (2011)Google Scholar
  30. 30.
    Tadano, K., Kawashima, K.: Development of 4-DOFs forceps with force sensing using pneumatic servo system. In: Proceedings 2006 IEEE International Conference on Robotics and Automation, ICRA 2006 (2006)Google Scholar
  31. 31.
    Tavakoli, M., Patel, R.V., Moallem, M.: A force reflective master-slave system for minimally invasive surgery. In: Proceedings of 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (2003)Google Scholar
  32. 32.
    Tomovic, R., Boni, G.: An adaptive artificial hand. IRE Trans. Autom. Control 7(3), 3–10 (1962)CrossRefGoogle Scholar
  33. 33.
    Wen-Hong, Z., Salcudean, S.E.: Stability guaranteed teleoperation: an adaptive motion/force control approach. IEEE Trans. Autom. Control 45(11), 1951–1969 (2000)MathSciNetCrossRefGoogle Scholar
  34. 34.
    Zhai, D.H., Xia, Y.: Adaptive control for teleoperation system with varying time delays and input saturation constraints. IEEE Trans. Industr. Electron. 63(11), 6921–6929 (2016)CrossRefGoogle Scholar
  35. 35.
    Zhai, D.H., Xia, Y.: Adaptive control of semi-autonomous teleoperation system with asymmetric time-varying delays and input uncertainties. IEEE Trans. Cybern. 47, 3621–3633 (2017)CrossRefGoogle Scholar
  36. 36.
    Zhou, M., Ben-Tzvi, P.: RML glove - an exoskeleton glove mechanism with haptics feedback. IEEE/ASME Trans. Mechatron. 20(2), 641–652 (2015)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Mateusz Saków
    • 1
    Email author
  • Arkadiusz Parus
    • 1
  • Mirosław Pajor
    • 1
  • Karol Miądlicki
    • 1
  1. 1.Institute of Mechanical TechnologyWest Pomeranian University of TechnologySzczecinPoland

Personalised recommendations