Skip to main content
SpringerLink
Log in

A variable structure passivity control method for elastic joint robots based on cascaded high-order state estimation

  • Article
  • Published:
Science China Technological Sciences Aims and scope Submit manuscript

Abstract

Passivity-based controllers are widely used to facilitate physical interaction between humans and elastic joint robots, as they enhance the stability of the interaction system. However, the joint position tracking performance can be limited by the structures of these controllers when the system is faced with uncertainties and rough high-order system state measurements (such as joint accelerations and jerks). This study presents a variable structure passivity (VSP) control method for joint position tracking of elastic joint robots, which combines the advantages of passive control and variable structure control. This method ensures the tracking error converges in a finite time, even when the system faces uncertainties. The method also preserves the passivity of the system. Moreover, a cascaded observer, called CHOSSO, is also proposed to accurately estimate high-order system states, relying only on position and velocity signals. This observer allows independent implementation of disturbance compensation in the acceleration and jerk estimation channels. In particular, the observer has an enhanced ability to handle fast time-varying disturbances in physical human-robot interaction. The effectiveness of the proposed method is verified through simulations and experiments on a lower limb rehabilitation robot equipped with elastic joints.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Huo W, Mohammed S, Moreno J C, et al. Lower limb wearable robots for assistance and rehabilitation: A state of the art. IEEE Syst J, 2016, 10: 1068–1081

    Article  Google Scholar 

  2. Yu H, Huang S, Chen G, et al. Human-robot interaction control of rehabilitation robots with series elastic actuators. IEEE Trans Robot, 2015, 31: 1089–1100

    Article  Google Scholar 

  3. Zimmermann Y, Kücüktabak E B, Farshidian F, et al. Towards dynamic transparency: Robust interaction force tracking using multisensory control on an arm exoskeleton. In: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Las Vegas: IEEE, 2020. 7417–7424

    Chapter  Google Scholar 

  4. Wang C, Sheng B, Li Z, et al. A lightweight series elastic actuator with variable stiffness: Design, modeling, and evaluation. In: IEEE/ASME Transactions on Mechatronics. New York: IEEE, 2023. 1–10

    Google Scholar 

  5. Cao R, Cheng L, Yang C G, et al. Iterative assist-as-needed control with interaction factor for rehabilitation robots. Sci China Tech Sci, 2021, 64: 836–846

    Article  Google Scholar 

  6. Pratt G A, Williamson M M. Series elastic actuators. In: Proceedings of 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots. Pittsburgh: IEEE, 1995. 399–406

    Google Scholar 

  7. Zhang T, Tran M, Huang H. Admittance shaping-based assistive control of SEA-driven robotic hip exoskeleton. IEEE ASME Trans Mechatron, 2019, 24: 1508–1519

    Article  Google Scholar 

  8. Chen T, Casas R, Lum P S. An elbow exoskeleton for upper limb rehabilitation with series elastic actuator and cable-driven differential. IEEE Trans Robot, 2019, 35: 1464–1474

    Article  Google Scholar 

  9. Li S, Shi Y, Hu L, et al. A generalized model predictive control method for series elastic actuator driven exoskeleton robots. Comput Electrical Eng, 2021, 94: 107328

    Article  Google Scholar 

  10. Wu J, Yu G, Gao Y, et al. Mechatronics modeling and vibration analysis of a 2-DOF parallel manipulator in a 5-DOF hybrid machine tool. Mech Mach Theor, 2018, 121: 430–445

    Article  Google Scholar 

  11. Khan RFA, Rsetam K, Cao Z, et al. Singular perturbation-based adaptive integral sliding mode control for flexible joint robots. IEEE Trans Ind Electron, 2023, 70: 10516–10525

    Article  Google Scholar 

  12. Albu-Schäffer A, Ott C, Hirzinger G. A unified passivity-based control framework for position, torque and impedance control of flexible joint robots. Int J Robot Res, 2007, 26: 23–39

    Article  Google Scholar 

  13. Luca AD, Flacco F. A pd-type regulator with exact gravity cancellation for robots with flexible joints. In: 2011 IEEE International Conference on Robotics and Automation. Shanghai: IEEE, 2011. 317–323

    Chapter  Google Scholar 

  14. Keppler M, Lakatos D, Ott C, et al. Elastic structure preserving (ESP) control for compliantly actuated robots. IEEE Trans Robot, 2018, 34: 317–335

    Article  Google Scholar 

  15. Keppler M, Raschel C, Wandinger D, et al. Robust stabilization of elastic joint robots by ESP and PID control: Theory and experiments. IEEE Robot Autom Lett, 2022, 7: 8283–8290

    Article  Google Scholar 

  16. Ramuzat N, Boria S, Stasse O. Passive inverse dynamics control using a global energy tank for torque-controlled humanoid robots in multi-contact. IEEE Robot Autom Lett, 2022, 7: 2787–2794

    Article  Google Scholar 

  17. Giusti A, Malzahn J, Tsagarakis N G, et al. On the combined inverse-dynamics/passivity-based control of elastic-joint robots. IEEE Trans Robot, 2018, 34: 1461–1471

    Article  Google Scholar 

  18. Spong M W. Modeling and control of elastic joint robots. J Dyn Syst Measurement Control, 1987, 109: 310–318

    Article  Google Scholar 

  19. Rsetam K, Cao Z, Wang L, et al. Practically robust fixed-time convergent sliding mode control for underactuated aerial flexible join- trobots manipulators. Drones, 2022, 6: 428

    Article  Google Scholar 

  20. Rsetam K, Al-Rawi M, Cao Z, et al. Sliding mode control based on high-order extended state observer for flexible joint robot under time-varying disturbance. AIP Conf Proc, 2023, 2651: 050011

    Article  Google Scholar 

  21. Rsetam K, Al-Rawi M, Cao Z. Robust continuous sliding mode controller for uncertain canonical brunovsky systems using reduced order extended state observer. In: 2022 IEEE 20th International Conference on Industrial Informatics (INDIN). Perth: 2022. 407–412

  22. Wang H, Zhang Z, Tang X, et al. Continuous output feedback sliding mode control for underactuated flexible-joint robot. J Frank Inst, 2022, 359: 7847–7865

    Article  MathSciNet  Google Scholar 

  23. Rsetam K, Cao Z, Man Z. Cascaded-extended-state-observer-based sliding-mode control for underactuated flexible joint robot. IEEE Trans Ind Electron, 2020, 67: 10822–10832

    Article  Google Scholar 

  24. Rsetam K, Cao Z, Man Z. Design of robust terminal sliding mode control for underactuated flexible joint robot. In: IEEE Transactions on Systems, Man, and Cybernetics: Systems. New York: IEEE, 2022. 4272–4285

    Google Scholar 

  25. Garofalo G, Mansfeld N, Jankowski J, et al. Sliding mode momentum observers for estimation of external torques and joint acceleration. In: 2019 International Conference on Robotics and Automation (ICRA). Montreal: 2019. 6117–6123

  26. Talole S E, Kolhe J P, Phadke S B. Extended-state-observer-based control of flexible-joint system with experimental validation. IEEE Trans Ind Electron, 2010, 57: 1411–1419

    Article  Google Scholar 

  27. Wu J, Zhang B B, Wang L P, et al. An iterative learning method for realizing accurate dynamic feedforward control of an industrial hybrid robot. Sci China Tech Sci, 2021, 64: 1177–1188

    Article  Google Scholar 

  28. Lynch KM, Park FC. Modern Robotics. Cambridge: Cambridge University Press, 2017

    Google Scholar 

  29. Han L, Mao J, Cao P, et al. Towards sensorless interaction force estimation for industrial robots using high-order finite-time observers. In: IEEE Transactions on Industrial Electronics. New York: IEEE, 2021. 1

    Google Scholar 

  30. Luca A D, Mattone R. Actuator failure detection and isolation using generalized momenta. In: 2003 IEEE International Conference on Robotics and Automation. New York: IEEE, 2003. 634–639

    Google Scholar 

  31. Feng Y, Han F, Yu X. Chattering free full-order sliding-mode control. Automatica, 2014, 50: 1310–1314

    Article  MathSciNet  Google Scholar 

  32. Hong Y, Xu Y, Huang J. Finite-time control for robot manipulators. Syst Control Lett, 2002, 46: 243–253

    Article  MathSciNet  Google Scholar 

  33. Bhat S P, Bernstein D S. Geometric homogeneity with applications to finite-time stability. Math Control Signals Syst, 2005, 17: 101–127

    Article  MathSciNet  Google Scholar 

  34. Bhat S P, Bernstein D S. Finite-time stability of homogeneous systems. In: Proceedings of the 1997 American Control Conference. Albuquerque: IEEE, 1997. 2513–2514

    Google Scholar 

  35. Wang Y S, Chen Z Q, Sun M W, et al. Design and stability analysis of a generalized reduced-order active disturbance rejection controller. Sci China Tech Sci, 2022, 65: 361–374

    Article  Google Scholar 

  36. Zhang J, Nie P, Chen Y, et al. A joint acceleration estimation method based on a high-order disturbance observer. IEEE Robot Autom Lett, 2022, 7: 12615–12622

    Article  Google Scholar 

  37. Han J. From PID to active disturbance rejection control. IEEE Trans Ind Electron, 2009, 56: 900–906

    Article  Google Scholar 

  38. Kong K, Bae J, Tomizuka M. Control of rotary series elastic actuator for ideal force-mode actuation in human-robot interaction applications. IEEE ASME Trans Mechatron, 2009, 14: 105–118

    Article  Google Scholar 

  39. Wu J, Wang J, You Z. An overview of dynamic parameter identification of robots. Robot Comput-Integr Manufact, 2010, 26: 414–419

    Article  Google Scholar 

  40. Gautier M, Khalil W. Direct calculation of minimum set of inertial parameters of serial robots. IEEE Trans Robot Automat, 1990, 6: 368–373

    Article  Google Scholar 

  41. Zhang J, Zhang B. An iterative identification method for the dynamics and hysteresis of robots with elastic joints. Nonlin Dyn, 2023, 111: 13939–13953

    Article  Google Scholar 

  42. Tien L L, Albu-Schaffer A, Luca A D, et al. Friction observer and compensation for control of robots with joint torque measurement. In: 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems. Nice: IEEE, 2008. 3789–3795

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    JieXin Zhang, PingYun Nie & Bo Zhang

Authors
  1. JieXin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. PingYun Nie
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bo Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bo Zhang.

Additional information

This work was supported by the National Natural Science Foundation of China (Grant Nos. 91648112, 52375506).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, J., Nie, P. & Zhang, B. A variable structure passivity control method for elastic joint robots based on cascaded high-order state estimation. Sci. China Technol. Sci. 67, 395–407 (2024). https://doi.org/10.1007/s11431-023-2479-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11431-023-2479-5

Search

Navigation