Advertisement

Basic Data-Based Measures

  • Paweł D. DomańskiEmail author
Chapter
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 245)

Abstract

Apart of the step response, the raw time data for the loop variables are frequently used to evaluate integral indexes. Mean Square Error (MSE) is the classical example, being used by almost everybody. Actually, hardly anybody things about integral measure formulation—MSE is just selected. Its story started in the beginning of the 19th century and continues. However, there are much more integral indexes that might be used, like Integral Absolute Error (IAE), which history is not shorter. Despite all the deficiencies of the squared error, its lack of robustness we use it. This chapter brings forward various integral measures existing in the CPA research. The integral measures are using one dimensional trends, however 2-D data representation might be useful for the loop analysis as well. The short discussion about X-Y plots concludes the chapter.

References

  1. 1.
    Åström, K.J., Hägglund, T.: PID Controllers: Theory, Design, and Tuning, 2nd edn. International Society for Measurement and Control, Research Triangle Park, N.C, ISA (1995)Google Scholar
  2. 2.
    Domański, P.D.: Statistical measures for proportional-integral-derivative control quality: simulations and industrial data. Proc. Inst. Mech. Eng. Part I J. Syst. Control Eng. 232(4), 428–441 (2018)CrossRefGoogle Scholar
  3. 3.
    Domański, P.D., Plamowski, S., Warchoł, M., Świrski, K.: (2004) Sensor validation and recovery. In: Proceedings of International Conference on Complex Systems Intelligence and Modern Technological Applications CSIMTA 2004, Cherbourg, France, pp. 766–771 (2004)Google Scholar
  4. 4.
    Fortuna, L., Graziani, S., Rizzo, A., Xibilia, M.G.: Soft Sensors for Monitoring and Control of Industrial Processes (Advances in Industrial Control). Springer-Verlag, New York (2006)zbMATHGoogle Scholar
  5. 5.
    Gao, X., Yang, F., Shang, C., Huang, D.: A novel data-driven method for simultaneous performance assessment and retuning of PID controllers. Ind. Eng. Chem. Res. 56(8), 2127–2139 (2017)CrossRefGoogle Scholar
  6. 6.
    Jelali, M.: Control Performance Management in Industrial Automation: Assessment. Diagnosis and Improvement of Control Loop Performance. Springer-Verlag, London (2013)CrossRefGoogle Scholar
  7. 7.
    Levine, W.S.: The Control Handbook. Jaico Publishing House (1996)Google Scholar
  8. 8.
    Mehrotra, K.G., Mohan, C.K., Huang, H.M.: Anomaly Detection Principles and Algorithms, 1st edn. Terrorism, Security, and Computation. Springer Publishing Company, Inc (2017)Google Scholar
  9. 9.
    Mitchell, W., Shook, D., Shah, S.L.: A picture worth a thousand control loops: an innovative way of visualizing controller performance data. Invited Plenary Presentation, Control Systems (2004)Google Scholar
  10. 10.
    Nishikawa, Y., Sannomiya, N., Ohta, T., Tanaka, H.: A method for auto-tuning of PID control parameters. Automatica 20(3), 321–332 (1984)CrossRefGoogle Scholar
  11. 11.
    Seborg, D., Edgar, T.F., Mellichamp, D.: Process Dynamics & Control. Wiley, New York (2006)Google Scholar
  12. 12.
    Seborg, D.E., Mellichamp, D.A., Edgar, T.F., Doyle, F.J.: Process Dynamics and Control. Wiley (2010)Google Scholar
  13. 13.
    Shinskey, F.G.: Process control: as taught vs as practiced. Ind. Eng. Chem. Res. 41, 3745–3750 (2002)CrossRefGoogle Scholar
  14. 14.
    Skogestad, S.: Simple analytic rules for model reduction and PID controller tuning. J. Process Control 13(4), 291–309 (2003)MathSciNetCrossRefGoogle Scholar
  15. 15.
    Tavazoei, M.S.: Notes on integral performance indices in fractional-order control systems. J. Process Control 20(3), 285–291 (2010)CrossRefGoogle Scholar
  16. 16.
    Unbehauen, H.: Controller design in time domain. In: Unbehauen, H. (ed.) Encyclopedia of Life Support Systems (EOLSS). Eolss Publishers, Oxford (2009)Google Scholar
  17. 17.
    Yu, Z., Wang, J.: Performance assessment of static lead-lag feedforward controllers for disturbance rejection in PID control loops. ISA Trans. 64, 67–76 (2016)CrossRefGoogle Scholar
  18. 18.
    Yu, Z., Wang, J., Huang, B., Li, J., Bi, Z.: Design and performance assessment of setpoint feedforward controllers to break tradeoffs in univariate control loops. In: 19th IFAC World Congress, IFAC Proceedings vol. 47(3), pp. 5740–5745 (2014)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Institute of Control and Computation EngineeringWarsaw University of TechnologyWarsawPoland

Personalised recommendations