Advertisement

An approach based on an adaptive multi-rate smith predictor and gain scheduling for a networked control system: Implementation over Profibus-DP

  • Angel Cuenca
  • Julián Salt
  • Vicente Casanova
  • Ricardo Pizá
Technical Notes and Correspondence

Abstract

This paper presents a control strategy to face time-varying delays induced in a Networked Control System (NCS). The delay is divided into two parts: the largest one (an integer multiple of the bus cycle) is compensated by means of an adaptive multi-rate Smith predictor, and the smallest one (whose value is strictly smaller than the bus cycle) via a gain scheduling approach based on root locus contour and linearization techniques. The gains to be scheduled belong to a multi-rate PID controller. Control system stability is studied by means of Lyapunov theory. Simulation results and the implementation on a test-bed Profibus-DP environment illustrate that this control structure can maintain NCS performance and stability, despite the considered delays.

Keywords

Networked control system network-induced delay Smith predictor PID controller tuning Lyapunov theory 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    W.-J. Kim, K. Ji, and A. Ambike, “Real-time operating environment for networked control systems,” IEEE Trans. on Automation Science and Engineering, vol. 3, no. 3, pp. 287–296, July 2006.CrossRefGoogle Scholar
  2. [2]
    T. C. Yang, “Networked control system: a brief survey,” IEE Proc. of Control Theory and Applications, vol. 153, no. 4, pp. 403–412, July 2006.CrossRefGoogle Scholar
  3. [3]
    Y. Halevi and A. Ray, “Integrated communication and control systems: part I-analysis,” Journal of Dynamic Systems, Measurement and Control, vol. 110, pp. 367–373, December 1988.CrossRefGoogle Scholar
  4. [4]
    J. Nilsson, Real-time Control Systems with Delays, Ph.D. Dissertation, Lund Institute of Technology, Lund, Sweden, 1998.Google Scholar
  5. [5]
    Y. Tipsuwan and M.-Y. Chow, “Control methodologies in networked control systems,” Control Engineering Practice, vol. 11, no. 10, pp. 1099–1111, February 2003.CrossRefGoogle Scholar
  6. [6]
    A. Cuenca, J. Salt, and P. Albertos, “Implementation of algebraic controllers for non-conventional sampled-data systems,” Real-Time Systems, vol. 35, pp. 59–89, January 2007.zbMATHCrossRefGoogle Scholar
  7. [7]
    T. P. Sim, G. S. Hong, and K. B. Lim, “Multirate predictor control scheme for visual servo control,” IEE Proc. of Control Theory and Applications, vol. 149, no. 2, pp. 117–124, March 2002.CrossRefGoogle Scholar
  8. [8]
    Y. Tipsuwan and M.-Y. Chow, “Gain scheduler middleware: a methodology to enable existing controllers for networked control and teleoperation-part I: networked control,” IEEE Trans. on Industrial Electronics, vol. 51, no. 6, pp. 1218–1227, December 2004.CrossRefGoogle Scholar
  9. [9]
    H. Li, Z. Sun, B. Chen, H. Liu, and F. Sun, “Intelligent scheduling control of networked control systems with networked-induced delay and packet dropout,” International Journal of Control, Automation, and Systems, vol. 6, no. 6, pp. 915–927, December 2008.Google Scholar
  10. [10]
    J. Salt, A. Cuenca, V. Casanova, and V. Mascarós, “A PID dual rate controller implementation over a networked control system,” Proc. of the IEEE CCA/CACSD/ISIC, pp. 1343–1349, 2006.Google Scholar
  11. [11]
    J. Salt and P. Albertos, “Model-based multirate controllers design,” IEEE Trans. on Control Systems Technology, vol. 13, no. 6, pp. 988–997, November 2005.CrossRefGoogle Scholar
  12. [12]
    C. M. Vélez and J. Salt, “Simulation of irregular multirate systems,” Proc. of the 8th Symp. on Computer Aided Control System Design. 2000.Google Scholar
  13. [13]
    K. J. Astrom and B. Wittenmark, Computer-Controlled Systems: Theory and Design, Prentice Hall, 1997.Google Scholar
  14. [14]
    P. Martí, J. Yépez, M. Velasco, R. Villà, and J. M. Fuertes, “Managing quality of control in networked-based control systems by controller and message scheduling co-design,” IEEE Trans. on Industrial Electronics, vol. 51, no. 6, pp. 1159–1167, December 2004.CrossRefGoogle Scholar
  15. [15]
    M. Fei, J. Yi, and H. Hu, “Robust stability analysis of an uncertain nonlinear networked control system category,” International Journal of Control, Automation, and Systems, vol. 4, no. 2, pp. 172–177, April 2006.Google Scholar
  16. [16]
    Z. Li, W. Wang, and Y. Jiang, “Managing qualityof-control and requirement-of-bandwidth in networked control systems via fuzzy bandwidth scheduling,” International Journal of Control, Automation, and Systems, vol. 7, no. 2, pp. 289–296, April 2009.CrossRefGoogle Scholar

Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Angel Cuenca
    • 1
  • Julián Salt
    • 1
  • Vicente Casanova
    • 1
  • Ricardo Pizá
    • 1
  1. 1.Departamento de Ingeniería de Sistemas y Automática, Instituto Universitario de Automática e Informática IndustrialUniversidad Politécnica de ValenciaValenciaSpain

Personalised recommendations