Skip to main content
SpringerLink
Log in

ADRC-Based Trajectory Tracking Control for a Planar Continuum Robot

  • Regular paper
  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

Due to their inherent deformability, controlling continuum robots (CRs) comes with many challenges, including strong nonlinearity, uncertainty, and disturbance. In this paper, a planar CR is modeled as a general multi-input multi-output (MIMO) system with internal uncertainty and external disturbance. To improve the trajectory tracking performance, an active disturbance rejection control (ADRC)-based control strategy for the CR is proposed. The proposed method can regard the internal uncertainty and external disturbance of the CR as an overall disturbance. In the ADRC framework, a linear extended state observer (ESO) is designed to timely estimate the overall disturbance, and a closed-loop control with disturbance compensation and feedback control law is implemented. The convergence of the designed ESO and the stability of the ADRC-based controller are studied. Simulations and experiments are performed to verify the effectiveness of the proposed approach.

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. Robinson, G., Davies, J.B.C. Continuum robots- a state of the art. In: Proc. IEEE Int. Conf. Robot. Autom., pp. 2849–2854 (1999). https://doi.org/10.1109/ROBOT.1999.774029

  2. Webster, R.J., Jone, B.A.: Design and kinematic modeling of constant curvature continuum robots : a review. Int. J. Robot. Res. 29(13), 1661–1683 (2010). https://doi.org/10.1177/0278364910368147

    Article  Google Scholar 

  3. Burgner-Kahrs, J., Rucker, D.C., Choset, H.: Continuum robots for medical applications : A survey. IEEE Trans. Robot. 31(6), 1261–1280 (2015). https://doi.org/10.1109/TRO.2015.2489500

    Article  Google Scholar 

  4. Thomas, T.L., Venkiteswaran, V.K., Ananthasuresh, G.K., Misra, S.: Surgical applications of compliant mechanisms : A review. J. Mech. Robot. 13(2), 1–21 (2021). https://doi.org/10.1115/1.4049491

    Article  Google Scholar 

  5. Dong, X., Axinte, D., Palmer, D., Cobos, S., Raffles, M., Rabani, A., Kell, J.: Development of a slender continuum robotic system for on-wing inspection/repair of gas turbine engines. Robot. Comput. Manuf. 44, 218–229 (2017). https://doi.org/10.1016/j.rcim.2016.09.004

    Article  Google Scholar 

  6. Wang, C., Frazelle, C.G., Wagner, J.R., Walker, I.D.: Dynamic control of multisection three-dimensional continuum manipulators based on virtual discrete-jointed robot models. IEEE/ASME Trans. Mechatron. 26(2), 777–788 (2021). https://doi.org/10.1109/TMECH.2020.2999847

    Article  Google Scholar 

  7. Ha, J., Park, F.C., Dupont, P.E.: Optimizing tube precurvature to enhance the elastic stability of concentric tube robots. IEEE Trans. Robot. 33(1), 22–37 (2017). https://doi.org/10.1109/TRO.2016.2622278

    Article  Google Scholar 

  8. Zhao, B., Zhang, W., Zhang, Z., Zhu, X., Xu, K.: Continuum manipulator with redundant backbones and constrained bending curvature for continuously variable stiffness. In: Proc. IEEE/RSJ Int. Conf. Intell. Robots and Syst., pp. 7492–7499 (2018). https://doi.org/10.1109/IROS.2018.8593437

  9. Hu, Y., Zhang, L., Li, W., Yang, G.-Z.: Design and fabrication of a 3-D printed metallic flexible joint for snake-like surgical robot. IEEE Robot. Autom. Lett. 4(2), 1557–1563 (2019). https://doi.org/10.1109/LRA.2019.2896475

    Article  Google Scholar 

  10. Li, M., Kang, R., Branson, D.T., Dai, J.S.: Model-free control for continuum robots based on an adaptive kalman filter. IEEE/ASME Trans. Mechatron. 23(1), 286–297 (2018). https://doi.org/10.1109/TMECH.2017.2775663

    Article  Google Scholar 

  11. Hannan, M.W., Walker, I.D.: Kinematics and the implementation of an elephant’s trunk manipulator and other continuum style robots. J. Robot. Syst. 20(2), 45–63 (2003). https://doi.org/10.1002/rob.10070

    Article  MATH  Google Scholar 

  12. Della Santina, C., Bicchi, A., Rus, D.: On an improved state parametrization for soft robots with piecewise constant curvature and its use in model based control. IEEE Robot. Autom. Lett. 5(2), 1001–1008 (2020). https://doi.org/10.1109/LRA.2020.2967269

    Article  Google Scholar 

  13. Buss, S.R. : Introduction to inverse kinematics with Jacobian transpose, pseudoinverse and damped least squares methods. [Online] Available : https://mathweb.ucsd.edu/~sbuss/ResearchWeb/ikmethods/iksurvey.pdf, 1–19 (2004)

  14. Liu, T., et al.: Iterative Jacobian-based inverse kinematics and open-loop control of an MRI-guided magnetically actuated steerable catheter system. IEEE/ASME Trans. Mechatron. 22(4), 1765–1776 (2017). https://doi.org/10.1109/TMECH.2017.2704526

    Article  Google Scholar 

  15. Li, M., Kang, R., Geng, S., Guglielmino, E.: Design and control of a tendon-driven continuum robot. Trans. Inst. Meas. Control 40(11), 3263–3272 (2018). https://doi.org/10.1177/0142331216685607

    Article  Google Scholar 

  16. Colom, A., Torras, C.: Closed-loop inverse kinematics for redundant robots: comparative assessment and two enhancements. IEEE/ASME Trans. Mechatron. 20(2), 944–955 (2015). https://doi.org/10.1109/TMECH.2014.2326304

    Article  Google Scholar 

  17. Braganza, D., Dawson, D.M., Walker, I.D., Nath, N.: A neural network controller for continuum robots. IEEE Trans. Robot. 23(6), 1270–1277 (2007). https://doi.org/10.1109/TRO.2007.906248

    Article  Google Scholar 

  18. Wang, Z., Wang, T., Zhao, B., He, Y., Hu, Y., Li, B., Zhang, P., Meng, M.Q.-H.: Hybrid adaptive control strategy for continuum surgical robot under external load. IEEE Robot. Autom. Lett. 6(2), 1407–1414 (2021). https://doi.org/10.1109/LRA.2021.3057558

    Article  Google Scholar 

  19. Jakes, D., Ge, Z., Wu, L.: Model-less active compliance for continuum robots using recurrent neural networks. In: Proc. IEEE/RSJ Int. Conf. Intell. Robots and Syst., pp. 2167–2173 (2019). https://doi.org/10.1109/IROS40897.2019.8968141

  20. Melingui, A., Mvogo Ahanda, J.J.-B., Lakhal, O., Mbede, J.B., Merzouki, R.: Adaptive algorithms for performance improvement of a class of continuum manipulators. IEEE Trans. Syst., Man, Cybern. Syst. 48(9), 1531–1541 (2018). https://doi.org/10.1109/TSMC.2017.2678605

    Article  Google Scholar 

  21. Jin, Y., Wang, Y., Chen, X., Wang, Z., Liu, X., Jiang, H., Chen, X.: Model-less feedback control for soft manipulators. In: Proc. IEEE/RSJ Int. Conf. Intell. Robots and Syst., pp. 2916–2922 (2017). https://doi.org/10.1109/IROS.2017.8206124

  22. Li, G., Song, D., Xu, S., Sun, L., Liu, J.: A hybrid model and model-free position control for a reconfigurable manipulator. IEEE/ASME Trans. Mechatron. 24(2), 785–795 (2019). https://doi.org/10.1109/TMECH.2019.2893227

    Article  Google Scholar 

  23. Yang, G.-Z., et al.: The grand challenges of science robotics. Sci. Robot. 3, 7650 (2018). https://doi.org/10.1126/scirobotics.aar7650

    Article  Google Scholar 

  24. Gao, X., Li, X., Sun, Y., Hao, L., Yang, H., Xiang, C.: Model-free tracking control of continuum manipulators with global stability and assigned accuracy. IEEE Trans. Syst., Man, Cybern. Syst. (2021). https://doi.org/10.1109/TSMC.2020.3018756

  25. Chen, W., Yang, J., Guo, L., Li, S.: Disturbance-observer-based control and related methods-an overview. IEEE Trans. Ind. Electron. 63(2), 1083–1095 (2016). https://doi.org/10.1109/TIE.2015.2478397

    Article  Google Scholar 

  26. Han, J.: From PID to active disturbance rejection control. IEEE Trans. Ind. Electron. 56(3), 900–906 (2009). https://doi.org/10.1109/TIE.2008.2011621

    Article  Google Scholar 

  27. Xia, Y., Fu, M., Li, C., Pu, F., Xu, Y.: Active disturbance rejection control for active suspension system of tracked vehicles with gun. IEEE Trans. Ind. Electron. 65(5), 4051–4060 (2018). https://doi.org/10.1109/TIE.2017.2772182

  28. Cao, Y., Zhao, Q., Ye, Y., Xiong, Y.: ADRC-based current control for grid-tied inverters: design, analysis, and verification. IEEE Trans. Ind. Electron. 67(10), 8428–8437 (2020). https://doi.org/10.1109/TIE.2019.2949513

  29. Zuo, Y., Mei, J., Jiang, C., Yuan, X., Xie, S., Lee, C.H.T.: Linear active disturbance rejection controllers for PMSM speed regulation system considering the speed filter. IEEE Trans. Power Electron. 36(12), 14579–14592 (2021). https://doi.org/10.1109/TPEL.2021.3098723

    Article  Google Scholar 

  30. Fareh, R., Khadraoui, S., Abdallah, M.Y., Baziyad, M., Bettayeb, M.: Active disturbance rejection control for robotic systems : A review. Mechatronics 80, 102671 (2021). https://doi.org/10.1016/j.mechatronics.2021.102671

    Article  Google Scholar 

  31. Truong, T.N., Kang, H.-J., Vo, A.T.: An active disturbance rejection control method for robot manipulators. In: Intell. Comput. Metho., pp. 190–201 (2020). https://doi.org/10.1007/978-3-030-60796-8_16

  32. Shi, D., Zhang, J., Sun, Z., Shen, G., Xia, Y.: Composite trajectory tracking control for robot manipulator with active disturbance rejection. Control Eng. Pract. 106, 104670 (2021). https://doi.org/10.1016/j.conengprac.2020.104670

    Article  Google Scholar 

  33. Mo, H., Ouyang, B., Xing, L., Dong, D., Liu, Y., Sun, D.: Automated 3- D deformation of a soft object using a continuum robot. IEEE Trans. Autom. Sci. Eng. 18(4), 2076–2086 (2021). https://doi.org/10.1109/TASE.2020.3033558

    Article  Google Scholar 

  34. Yoo, D., Yau, S.S.-T., Gao, Z.: Optimal fast tracking observer bandwidth of the linear extended state observer. Int. J. Control 80(1), 102–111 (2007). https://doi.org/10.1080/00207170600936555

    Article  MathSciNet  MATH  Google Scholar 

  35. Gao, Z.: Scaling and bandwidth-parameterization based controller tuning. In: Proc. of Amer. Control Conf., pp. 4989–4996 (2003). https://doi.org/10.1109/ACC.2003.1242516

  36. Tian, G., Gao, Z.: Frequency response analysis of active disturbance rejection based control system. In: IEEE Int. Conf. Control Appl., pp. 1595–1599 (2007). https://doi.org/10.1109/CCA.2007.4389465

  37. Hong, W., Feng, F., Xie, L., Yang, G.-Z. : A two-segment continuum robot with piecewise stiffness for maxillary sinus surgery and its decoupling method. IEEE/ASME Trans. Mechatron., pp. 1–11 (2022). https://doi.org/10.1109/TMECH.2022.3157041

Download references

Funding

This work was supported in part by the National Natural Science Foundation of China (Grant 62133009, Grant 61973211, Grant M-0221, and Grant 62211540723), in part by the Science and Technology Commission of Shanghai Municipality (Grant 21550714200 and Grant 20DZ2220400), in part by the project of Institute of Medical Robotics of Shanghai Jiao Tong University, in part by the Foreign Cooperation Project of Fujian Province Science and Technology Program (Grant 2022I0041), in part by the Project of Quanzhou High-level Talent Innovation and Entrepreneurship (Grant 2021C003R), in part by the Hospital-local Cooperation Project of Xuhui District Artificial Intelligence Medical (Grant 2021-008), and in part by the Joint Project of Xinhua Hospital and Institute of Medical Robotics of Shanghai Jiao Tong University(Grant 21XJMR03).

Author information

Authors and Affiliations

  1. School of Materials Science and Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China

    Yongfeng Cao, Zhenggang Cao, Fan Feng & Le Xie

  2. Institute of Medical Robotics, Shanghai Jiao Tong University, 200240, Shanghai, China

    Yongfeng Cao, Zhenggang Cao, Fan Feng & Le Xie

Authors
  1. Yongfeng Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhenggang Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fan Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Le Xie
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Yongfeng Cao, Zhenggang Cao, Fan Feng, and Le Xie. The first draft of the manuscript was written by Yongfeng Cao and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Le Xie.

Ethics declarations

Competing Interest

The authors have no relevant financial or non-financial interests to disclose.

Additional information

Publisher's Note

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

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cao, Y., Cao, Z., Feng, F. et al. ADRC-Based Trajectory Tracking Control for a Planar Continuum Robot. J Intell Robot Syst 108, 1 (2023). https://doi.org/10.1007/s10846-023-01852-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10846-023-01852-z

Keywords

Search

Navigation