Skip to main content
SpringerLink
Log in

Adaptive Event-triggered Control of a Class of Series Elastic Actuator System

  • Control Theory and Applications
  • Published:
International Journal of Control, Automation and Systems Aims and scope Submit manuscript

Abstract

In this paper, the event-triggered adaptive control for a class of series elastic actuator systems is considered. To solve this problem, firstly we propose an adaptive control scheme with a novel one-step design framework such that both the controller expression and parameter estimator are much simpler than related existing recursive design approaches. Then a set of event-triggering conditions is designed which is updated for each triggering. The ISS assumption is not needed for control design. It is shown that the proposed control schemes guarantee that all the closed-loop signals are semi-globally bounded and the stabilization error converges to the origin asymptotically. The zeno behavior is avoided. Simulation results illustrate the effectiveness of our scheme.

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. Y. Yu and C. Lan, “Design of a miniature series elastic actuator for bilateral teleoperations requiring accurate torque sensing and control,” IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 500–507, 2019.

    Article  Google Scholar 

  2. S. Wolf, G. Grioli, O. Eiberger, W. Friedl, M. Grebenstein, H. Höppner, E. Burdet, D. G. Caldwell, R. Carloni, M. G. Catalano, D. Lefeber, S. Stramigioli, N. Tsagarakis, M. van Damme, R. van Ham, B. Vanderborght, L. C. Visser, A. Bicchi, and A. Albu-Schäffer, “Variable stiffness actuators: Review on design and components,” IEEE/ASME Trans. Mechatronics, vol. 21, no. 5, pp. 2418–2430, Oct. 2016.

    Article  Google Scholar 

  3. S. Oh and K. Kong, “High-precision robust force control of a series elastic actuator,” IEEE/ASME Trans. Mechatronics, vol. 22, no. 1, pp. 71–80, 2017.

    Article  Google Scholar 

  4. G. Mathijssen, D. Lefeber, and B. Vanderborght, “Variable recruitment of parallel elastic elements: Series-parallel elastic Actuators, no. SPEA) with dephased mutilated gears,” IEEE/ASME Trans. Mechatron., vol. 20, no. 2, pp. 594–602, Apr. 2015.

    Article  Google Scholar 

  5. K. Kong, J. Bae, and M. Tomizuka, “A compact rotary series elastic actuator for human assistive systems,” IEEE/ASME Trans. Mechatron., vol. 17, no. 2, pp. 288–297, Apr. 2012.

    Article  Google Scholar 

  6. A. Calanca and P. Fiorini, “Human-adaptive control of series elastic actuators,” Robotica, vol. 32, no. 8, pp. 1301–1316, Dec. 2014.

    Article  Google Scholar 

  7. J. Pratt, B. Krupp, and C. Morse, “Series elastic actuators for high fidelity force control,” Int. J. Ind. Robot, vol. 29, no. 3, pp. 234–241, 2002.

    Article  Google Scholar 

  8. N. Paine, S. Oh, and L. Sentis, “Design and control considerations for high performance series elastic actuators,” IEEE/ASME Trans. Mechatronics, vol. 19, no. 3, pp. 1080–1091, 2014.

    Article  Google Scholar 

  9. J. Lu, K. Haninger, W. Chen, and M. Tomizuka, “Design and torque-mode control of a cable-driven rotary series elastic actuator for subject-robot interaction,” Proc. IEEE Int. Conf. Adv. Intell. Mechatronics, pp. 158–164, 2015.

  10. M. Laffranchi, L. S. Chen, N. Kashiri, J. Lee, N. G. Tsagarakis, and D. G. Caldwell, “Development and control of a series elastic actuator equipped with a semi active friction damper for human friendly robots,” Robot. Autonom. Syst., vol. 62, no. 12, pp. 1827–1836, Dec. 2014.

    Article  Google Scholar 

  11. M. Wang, L. Sun, W. Yin, S. Dong, and J. Liu, “Continuous robust control for series elastic actuator with unknown payload parameters and external disturbances,” IEEE/CAA J. of Autom. Sinica, vol. 4, no. 4, pp. 620–627, Oct. 2017.

    Article  MathSciNet  Google Scholar 

  12. C. H. Zhang and G. H. Yang, “Event-triggered adaptive output feedback control for a class of uncertain nonlinear systems with actuator failures,” IEEE Trans. on Cybernetics, vol. 50, no. 1, pp. 201–210, 2020.

    Article  Google Scholar 

  13. H. Wang and G. H. Yang, “Decentralized event-triggered H-infinity control for affine fuzzy large-scale systems,” IEEE trans. on Fuzzy Systems, vol. 27, no. 11, pp. 2215–2226, 2019.

    Article  Google Scholar 

  14. X. Li, D. Ma, X. Hu, and D. Ho, “Dynamic event-triggered control for heterogeneous leader-following consensus of multi-agent systems based on input-to-state stability,” International Journal of Control, Automation, and Systems, vol. 18, no. 2, pp. 293–302, 2020.

    Article  Google Scholar 

  15. J. Huang, L. Chen, X. Xie, M. Wang, and B. Xu. “Distributed event-triggered consensus control for heterogeneous multi-agent systems under fixed and switching topologies,” International Journal of Control, Automation, and Systems, vol. 17, no. 8, pp. 1945–1956, 2019.

    Article  Google Scholar 

  16. G. Xu, J. Huang, and X. Su, “Decentralized adaptive control of interconnected nonlinear systems with unknown control directions and actuator failure,” International Journal of Control, Automation, and Systems, vol. 17, no. 1, pp. 29–37, 2019.

    Article  Google Scholar 

  17. J. Li, X. Chen, F. Hao, and J. Xie. “Event-triggered bipartite consensus for multi-agent systems with antagonistic interactions,” International Journal of Control, Automation, and Systems, vol. 17, no. 8, pp. 2046–2058, 2019.

    Article  Google Scholar 

  18. J. Huang, W. Wang, C. Wen, and G. Li, “Adaptive event-triggered control of nonlinear systems with controller and parameter estimator triggering,” IEEE Transactions on Automatic Control, vol. 65, no. 1, pp. 318–324, 2020.

    Article  MathSciNet  Google Scholar 

  19. J. Huang and Q.-G. Wang, “Event-triggered adaptive control of a class of nonlinear systems,” ISA Transactions, vol. 94, pp. 10–16, 2019.

    Article  Google Scholar 

  20. J. Huang, C. Wen, W. Wang, and Z.-P. Jiang, “Adaptive output feedback tracking control of a nonholonomic mobile robot,” Automatica, vol. 50, pp. 821–831, 2014.

    Article  MathSciNet  Google Scholar 

  21. J. Huang and Q.-G. Wang, “Decentralized adaptive control of interconnected nonlinear systems with unknown control directions,” ISA Transactions, vol. 74, pp. 60–66, 2018.

    Article  Google Scholar 

  22. J. Huang, L. Zhao, and Q.-G. Wang, “Adaptive control of a class of strict feedback nonlinear systems under replay attacks,” ISA Transactions, vol. 107, pp. 134–142, 2020.

    Article  Google Scholar 

  23. J. Huang, Y.-D. Song, W. Wang, and C. Wen, “Smooth control design for adaptive leader-following consensus control of a class of high-order nonlinear systems with time-varying reference,” Automatica, vol. 83, pp. 361–367, 2017.

    Article  MathSciNet  Google Scholar 

  24. J. Huang, C. Wen, W. Wang, and Y.-D. Song, “Adaptive finite-time consensus control of a group of uncertain nonlinear mechanical systems,” Automatica, vol. 51, pp. 292–301, 2015.

    Article  MathSciNet  Google Scholar 

  25. K. Johansson, M. Egerstedt, J. Lygeros, and S. Sastry, “On the regularization of Zeno hybrid automata,” Systems Control Letters, vol. 38, pp. 141–150, 1999.

    Article  MathSciNet  Google Scholar 

  26. J. Huang, W. Wang, C. Wen, J. Zhou, and G. Li, “Distributed adaptive leader-follower and leaderless consensus control of a class of strict-feedback nonlinear systems: A unified approach,” Automatica, vol. 118, 109021, 2021.

    Article  MathSciNet  Google Scholar 

  27. J. Huang, Y.-D. Song, W. Wang, and C. Wen, “Fully distributed adaptive consensus control of a class of high-order nonlinear systems with a directed topology and unknown control directions,” IEEE Trans. Cybernetics, vol. 48, no. 8, pp. 2349–2356, 2018.

    Article  Google Scholar 

  28. L. Hao and W. Lin, “Universal adaptive control of nonlinear systems with unknown growth rate by output feedback,” Automatica, vol. 42, pp. 1783–1789, 2006.

    Article  MathSciNet  Google Scholar 

  29. N. Fischer, R. Kamalapurkar, and W. E. Dixon, “LaSalle-Yoshizawa corollaries for nonsmooth systems,” IEEE Transactions on Automatic Control, vol. 58, no. 9, pp. 2333–2340, 2013.

    Article  MathSciNet  Google Scholar 

  30. J. Huang, W. Wang, C. Wen, and J. Zhou, “Adaptive control of a class of strict-feedback time-varying nonlinear systems with unknown control coefficients,” Automatica, vol. 93, pp. 98–105, 2018.

    Article  MathSciNet  Google Scholar 

  31. L. Xing, C. Wen, Z. Liu, H. Su, and J. Cai. “Event-triggered adaptive control for a class of uncertain nonlinear systems,” IEEE Transactions on Automatic Control, vol. 62, no. 4, pp. 2071–2076. 2017.

    Article  MathSciNet  Google Scholar 

  32. M. Krstic, I. Kanellakopoulos, and P. Kokotovic, Nonlinear and Adaptive Control Design, John Wiley and Sons, 1995.

  33. J. Yook, D. M. Tilbury, and N. R. Soparkar. “Trading computation for bandwidth: Reducing communication in distributed control systems using state estimators,” IEEE Transactions on Control Systems Technology, vol. 10, no. 4, pp. 503–518. 2002.

    Article  Google Scholar 

  34. P. Tabuada, “Event-triggered real-time scheduling of stabilizing control tasks,” IEEE Transactions on Automatic Control, vol. 52, no. 9, pp. 1680–1685, 2007.

    Article  MathSciNet  Google Scholar 

  35. P. Tallapragada and N. Chopra, “On event triggered tracking for nonlinear systems,” IEEE Transactions on Automatic Control, vol. 58, no. 9, pp. 2343–2349. 2013.

    Article  MathSciNet  Google Scholar 

  36. W. Heemels, J. Sandee, and P. van Den Bosch, “Analysis of event-driven controllers for linear systems,” International Journal of Control, vol. 81, no. 4, pp. 571–590, 2008.

    Article  MathSciNet  Google Scholar 

  37. Y. Gao, J. Liu, Z. Wang, and L. Wu, “Interval type-2 FNN-based quantized tracking control for hypersonic flight vehicles with prescribed performance,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 51, no. 3, pp. 1981–1993, 2021.

    Google Scholar 

  38. C.-M. Lin, T.-L. Le, and T.-T. Huynh, “Self-evolving function-link interval type-2 fuzzy neural network for nonlinear system identification and control,” Neurocomputing, vol. 275, no. 31, pp. 2239–2250, 2018.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Mechanical and Electrical Engineering, Zhejiang Textile Fashion College, Ningbo Zhejiang, China, 315211

    Tingting Gao

  2. School of Automation, Chongqing University, Chongqing, 400044, China

    Jiangshuai Huang & Rui Ling

  3. Key Laboratory for Optimization and Control of the Ministry of Education, Chongqing Normal University, Chongqing, 400047, China

    Jiangshuai Huang

  4. Yiheng Technol Co Ltd, Ningbo, Zhejiang, China

    Yong Zhou

Authors
  1. Tingting Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jiangshuai Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rui Ling
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yong Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jiangshuai Huang.

Additional information

This work was partially supported by National Key Research and Development Program of China under grant no.2019YFB1312002, partially by National Natural Science Foundation of China under Grants 61703061, partially by Chongqing Key Laboratory on IFBDA under Grant CSSXKFKTZ201802, partially by the Basic Science and Frontier Technology Research Projects of Chongqing Science and Technology Program (General Projects) under Grants no. cstc2018jcyjAX0498 and no. cstc2018jcyjAX0297, partially by the Natural Science Foundation of Ningbo (No.2018A610074), partially by General Scientific Research Project of Department of Education of Zhejiang Province (No.Y201942413) and partially by Ningbo 2025 Major Science and Technology Innovation Project (No.2018B10009).

Tingting Gao received her B.S. and M.S. degrees in mathematics from Northeastern University, Shenyang, China, in 2005 and 2008, respectively, and a Ph.D. degree in the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. Her research interests include high precision motion control and integrative approach for controller design for optimal performance.

Jiangshuai Huang received his B.Eng. and M.Sc. degrees in the School of Automation from Huazhong University of Science & Technology, Wuhan, China in July 2007 and August 2009, respectively, and a Ph.D. from Nanyang Technological University in 2015. He was a Research Fellow in the Department of Electricity and Computer Engineering, National University of Singapore from August 2014 to September 2016. He is currently a professor in the School of Automation, Chongqing University, Chongqing, China. His research interests include adaptive control, nonlinear systems control, underactuated mechanical system control and multi-agent system control.

Rui Ling received his B.S., M.S., and Ph.D. degrees in automation from Chongqing University, Chongqing, China, in 2002, 2009, and 2015, respectively. He is currently a professor with the College of Automation, Chongqing University. He became a Visiting Scholar at the Colorado Power Electronics Center, Boulder, CO, USA, in 2012. He has published more than 30 publications and holds eight Chinese patents. His current research interests include model and control of renewable energy systems and digital control of switchedmode power converters.

Yong Zhou received his B.Eng. and M.Eng. degrees in electrical engineering from Zhejiang University, Hangzhou, China, in 2003 and 2006, respectively, and a Ph.D. degree in the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore in 2014. His research interests includes robust nonlinear control, sliding-mode control, and precision motion control. Now he is with Yiheng Technol Co Ltd, Ningbo, Zhejiang, China.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gao, T., Huang, J., Ling, R. et al. Adaptive Event-triggered Control of a Class of Series Elastic Actuator System. Int. J. Control Autom. Syst. 19, 2536–2543 (2021). https://doi.org/10.1007/s12555-020-0220-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12555-020-0220-4

Keywords

Search

Navigation