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PD-based trajectory tracking control in automatic cell injection system

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Abstract

Trajectory tracking technology has been the focus of industrial manipulatory applications for many years, and its research has been found in micromanipulation in bioengineering recently. In this paper, a hybrid vision and force control method is applied to the automatic cell injection. The three-dimensional cell injection process involves the trajectory tracking in free space and the force control in contact space. A PD plus feedforward compensation control method is applied to the trajectory tracking in 3D space. Further, a PD-based robust controller is introduced into trajectory tracking while the systemic uncertainty of the cell injection is additionally considered. Both of the two control methods are theoretically proved to be exponential convergent. Finally, the effectiveness of the proposed method is verified as compared with other control methods by its application to trajectory tracking problem.

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References

  1. J. Kuncova, P. Kallio. Challenges in Capillary pressure microinjection. IEEE Conference on Engineering in Medicine and Biology Society (EMBS). San Francisco: IEEE, 2004: 4998–5001.

    Chapter  Google Scholar 

  2. Y. Sun, B. J. Nelson. Biological cell injection using an autonomous microrobotics system. International Journal of Robotics Research, 2002, 21(10/11): 861–868.

    Google Scholar 

  3. K. K. Tan, D. C. Ng, Y. Xie. Optical intra-cytoplasmic sperm injection with a piezo micromanipulator. The 4th World Congress on Intelligent Control and Automation. Shanghai, 2002: 1120–1123.

    Google Scholar 

  4. H. Huang, D. Sun, J. K. Mills, et al. A visual impedance force control of a robotic cell injection system. IEEE Conference on Robotics and Biomimetics. Kunming: IEEE, 2006: 233–238.

    Chapter  Google Scholar 

  5. J. C. Spall, J. A. Cristion. Model-free control of nonlinear stochastic systemswith discrete-timemeasurements. IEEE Transactions on Automatic Control, 1998, 43(9): 1198–1210.

    Article  MathSciNet  MATH  Google Scholar 

  6. X. Zhao. A robust trajectory tracking method of the robotic system. Journal of Taiyuan Teachers College, 2004, 20(3): 4–8.

    Google Scholar 

  7. Q. Chen, Y. Wang, H. Chen. Comparative research of trajectory tracking performance of robotic manipulator based on PD control scheme. Journal of Control and Design, 2003, 18(1): 53–57.

    Google Scholar 

  8. T. Yu, T. Yu, J. Lan, et al. Design of robust trajectory tracking controller for robotic systems. Journal of Liaoning University of Technology, 2008, 28(2): 5–78.

    MathSciNet  Google Scholar 

  9. S. Jin, K. Watanabe, M. Nakamura. Multiple fuzzy control of a robot manipulator. Journal of Solid Mechanics and Materials Engineering, 1993, 557(59): 158–164.

    Google Scholar 

  10. Y. Wan, S. Wang, H. Du. Dynamic neural network control of hydraulic parallel robot. Journal of Xi’an Jiaotong University, 2004, 38(9): 955–958.

    Google Scholar 

  11. R. P. Paul. Modeling Trajectory Calculation and Servoing of a Computer Controlled Arm. Stanford University Artificial Intelligence Laboratory, 1972.

    Google Scholar 

  12. A. K. Bejczy. Robot Arm Dynamics and Control. Pasadena: NASAJet Propulsion Lab, 1974.

    Google Scholar 

  13. J. J. E. Slotine, S. S. Sastry. Tracking control of nonlinear systemsusing sliding surfaces with application to robot manipulators. International Journal of Control, 1983, 38(2): 465–492.

    Article  MathSciNet  MATH  Google Scholar 

  14. C. Huang, L. Fu. Adaptive backstepping tracking control of the Stewart platform. IEEE Conference on Decision and Control. Bahamas: IEEE, 2004: 5228–5233.

    Google Scholar 

  15. L. Ren, J. K. Mills, D. Sun. Controller design applied to planar parallel manipulators for trajectory tracking control. IEEE Conference on Robotics and Automation. Barcelona: IEEE, 2005: 980–985.

    Google Scholar 

  16. H. Huang, D. Sun, J. K. Mills, et al. Automatic suspended cell injection under vision and force control biomanipulation. IEEE Conference on Robotics and Biomimetics. Sanya: IEEE, 2007: 71–76.

    Google Scholar 

  17. H. Huang, D. Sun, J. K. Mills, et al. A visual impedance force control of a robotic cell injection system. IEEE Conference on Robotics and Biomimetics. Kunming: IEEE, 2006: 233–238.

    Chapter  Google Scholar 

  18. H. Huang, D. Sun, J. K. Mills, et al. Integrated vision and force control in suspended cell injection system: towards automatic batch biomanipulation. IEEE Conference on Robotics and Automation. Pasadena: IEEE, 2008: 3413–3418.

    Google Scholar 

  19. H. Seraji, R. Colbaugh. Force tracking in impedance control. International Journal of Robotics Research, 1997, 16(1): 97–117.

    Article  Google Scholar 

  20. J. Lu, J. Yan, J. Chen. Peg-in-hole insertion method based on adaptive impedance control. Journal of Control Theory & Applications, 2003, 20(1): 85–88.

    Google Scholar 

  21. H. B. Huang. Towards Automatic Batch Biomanipulation: Study on Robotic Suspended Cell Injection System. Hongkong: City University of Hong Kong, 2008.

    Google Scholar 

  22. M. W. Spong, S. Hutchinson, M. Vidyasagar. Robot Dynamics and Control. New York: John Wiley & Sons, 1989.

    Google Scholar 

  23. L. Shen. Foundation of Robust Control for Robots. Beijing: Tsinghua, 2000.

    Google Scholar 

  24. M. Takegaki, S. Arimoto. A new feedback method for dynamic control of manipulators. Journal of Dynamic Systems, Measurement, and Control, 1981, 103(2): 119–125.

    Article  MATH  Google Scholar 

  25. D. Koditschek. Natural motion for robot arms. IEEE Conference on Decision and Control. Las Vegas: IEEE, 1984: 733–735.

    Chapter  Google Scholar 

  26. Y. Wang, Y. Sun. Robotic robust trajectory tracking control system. Journal of Dynamics and Control, 2004, 2(2): 75–81.

    Google Scholar 

  27. W. Xu, M. Yin, C. Cai, et al. Time-varying force tracking in impedance control. IEEE Annual Conference on Decision and Control. Hawaii: IEEE, 2012: 344–349.

    Google Scholar 

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Authors and Affiliations

  1. School of Automation, Nanjing University of Science and Technology, Nanjing Jiangsu, 210094, China

    Wenkang Xu, Chenxiao Cai & Yun Zou

Authors
  1. Wenkang Xu
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  2. Chenxiao Cai
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  3. Yun Zou
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Corresponding author

Correspondence to Chenxiao Cai.

Additional information

This work was supported by the National Natural Science Foundation of China (No. 60874007), the Research Foundation for the Doctoral Program of Higher Education under Grant (No. 20070288055), the China Postdoctoral Science Foundation (No. 20090440084), and the Nanjing University of Science and Technology Special Research Program (No. 2010GJPY017).

Wenkang XU was born in Jiangsu, China, in 1986. He is a Ph. D. candidate at Nanjing University of Science and Technology. His research interests include robotics, adaptive control and robust control.

Chenxiao CAI was born in Shandong, China, in 1975. She received her Ph.D. degree in Control Theory and Control Engineering from Automatic School, Nanjing University of Science and Technology in 2004. Currently, she is an associate professor at Department of Automation, Nanjing University of Science and Technology. Her research interests cover analysis and synthesis about singularly perturbed system.

Yun ZOU was born in Jiangsu, China, in 1962. He received his B.S. degree from Northwestern University, China, in 1983, majored in Numerical Mathematics, and his Ph.D. degree from Nanjing University of Science and Technology, China, in 1990, majored in Automatic Control. He is currently a professor of the Department of Automation, Nanjing University of Science and Technology, and a mathematical reviewer of Mathematical Reviews. His research interests include singular systems, 2-D systems, nonlinear systems and power systems.

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Xu, W., Cai, C. & Zou, Y. PD-based trajectory tracking control in automatic cell injection system. J. Control Theory Appl. 11, 207–214 (2013). https://doi.org/10.1007/s11768-013-1037-y

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  • DOI: https://doi.org/10.1007/s11768-013-1037-y

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