Networked Control Based on Fuzzy Logic. An Application to a High-Performance Milling Process

  • Rodolfo E. Haber
  • Michael Schmittdiel
  • Angel Alique
  • Andrés Bustillo
  • Ramón Galán
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4507)

Abstract

Network-based applications are essential to providing intelligence to complex electromechanical processes through networked control systems (NCS). The focus of this paper is the design and application of fuzzy logic control for a type of NCSs. In order to assess its feasibility, a networked control system for high-performance milling process, a type of a complex electromechanical process, is implemented on a multi-point interface (MPI) bus, a proprietary programming interface port for peer-to-peer communications that resembles the PROFIBUS protocol. The manipulated input variable the feed rate as well as the control output variable, spindle torque, are transmitted through this network. A simple computational procedure can run remotely as an optimization function without requiring additional hardware. The results demonstrate that the Fuzzy Logic-based strategy provides accuracy, and adequate machining production time thus increasing the metal removal rate.

Keywords

networked control fuzzy logic high-performance machining 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Zhang, K., Huang, H., Zhang, J.: MPC-based control methodology in networked control systems. In: Wang, T.-D., Li, X.-D., Chen, S.-H., Wang, X., Abbass, H.A., Iba, H., Chen, G.-L., Yao, X. (eds.) SEAL 2006. LNCS, vol. 4247, pp. 814–820. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  2. 2.
    Fidge, C.J., Tian, Y.-C.: Functional Analysis of a Real-Time Protocol for Networked Control Systems. In: Graf, S., Zhang, W. (eds.) ATVA 2006. LNCS, vol. 4218, pp. 446–460. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  3. 3.
    Yang, T., Fei, M., Xue, D., Tan, Y., Zhou, X.: A Proposed Case Study for Networked Control System. In: Huang, D.-S., Li, K., Irwin, G.W. (eds.) ICIC 2006. LNCS (LNAI), vol. 4114, pp. 1026–1036. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  4. 4.
    Haber, R.E., Cantillo, K., Jiménez, J.E.: Networked sensing for high-speed machining processes based on CORBA. Sensors and Actuators A: Physics 119, 418–426 (2005)CrossRefGoogle Scholar
  5. 5.
    Aoki, S., Kawachi, S., Sugeno, M.: Application of fuzzy control logic for dead-time processes in a glass melting furnace. Fuzzy Sets and Systems 38, 251–265 (1990)CrossRefGoogle Scholar
  6. 6.
    Zhang, L., Huag-Jing, F.: A novel controller design and evaluation for networked control systems with time-variant delays. Journal of the Franklin Institute 343, 161–167 (2006)MATHCrossRefGoogle Scholar
  7. 7.
    Almutairi, N.B., Chow, M.-Y.: PI parameterization using adaptive fuzzy modulation (AFM) for networked control systems. II. Full adaptation. In: Proc. of 28th Annual Conference of the Industrial Electronics Society (IECON02), vol. 4, November 5-8, 2002, pp. 3158–3163 (2002)Google Scholar
  8. 8.
    Furness, R.J., Tsao, T.T., Rankin, J.S., Muth, M.J., Manes, K.W.: Torque control for a form tool drilling operation. IEEE Transactions on Control Systems Technology 7(1), 22–30 (1999)CrossRefGoogle Scholar
  9. 9.
    Liang, M., Yeap, T., Hermansyah, A., Rahmati, S.: Fuzzy control of spindle torque for industrial CNC machining. International Journal of Machine Tools and Manufacture 43, 1497–1508 (2003)CrossRefGoogle Scholar
  10. 10.
    Vitturi, S.: Stochastic model of the PROFIBUS-DP cycle time. IEE Proceedings on Science Measurement Technology 151(5), 335–342 (2004)CrossRefGoogle Scholar
  11. 11.
    Haber, R.E., Alique, J.R., Ros, S., Haber, R.H.: Modeling and Simulation of High-Speed Machining Processes Based on Matlab/Simulink. In: Sunderam, V.S., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2005. LNCS, vol. 3516, pp. 627–634. Springer, Heidelberg (2005)Google Scholar
  12. 12.
    Lee, K.-C., Lee, S., Lee, M.-H.: Remote fuzzy logic control of networked control system via PROFIBUS-DP. IEEE Transactions on Industrial Electronics 50(4), 784–792 (2003)CrossRefGoogle Scholar
  13. 13.
    Haber, R.E., Liang, S.Y., Alique, J.R., Haber-Haber, R.: Fuzzy control of spindle torque in high-speed milling processes. Journal of Manufacturing Science and Engineering 128(4), 1014–1018 (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Rodolfo E. Haber
    • 1
    • 2
  • Michael Schmittdiel
    • 1
  • Angel Alique
    • 1
  • Andrés Bustillo
    • 3
  • Ramón Galán
    • 4
  1. 1.Instituto de Automática Industrial (CSIC)., km. 22,800 N-III. 28500. MadridSpain
  2. 2.Escuela Politécnica Superior, Calle Francisco Tomás y Valiente, 11, 28049 – MadridSpain
  3. 3.Nicolás Correa S.A., C/ Alcalde Martin Cobos s/n. 09007Spain
  4. 4.Escuela Técnica Superior de Ingenieros Industriales., Universidad Politécnica de Madrid. MadridSpain

Personalised recommendations