Skip to main content

State of the Art in Parameter and State Estimation of Complex Systems by Simulation

  • Conference paper
First European Simulation Congress ESC 83

Part of the book series: Informatik-Fachberichte ((INFORMATIK,volume 71))

  • 107 Accesses

Summary

A review of the parameter and state estimation schemes, based on adjustable model technique will be given as well as some optimal filtering algorithms suitable to solve the same identification problems by simulation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Anderson, B.D.O. and Moore, J.B.: Optimal Filtering, Prentice-Hall, Englewood Cliffs, N.J., 1979.

    MATH  Google Scholar 

  • Aström, K. J.: The Role of System Identification in Process Modeling. VDI-Berichte, Nr. 276, 1977, pp. 13–30.

    Google Scholar 

  • Carson, E.R., Cobelli, C., and Finkelstein, L.: Integrated Methodology for Model Formulation, Identification and Validation of Metabolic and Endocrine Systems. IFAC Symp. on Identif. and System Param. Estim., Washington, 1982, pp. 884–889.

    Google Scholar 

  • Cellier, F.E.: Progress in Modelling and Simulation. Academic Press, New York, 1982.

    Google Scholar 

  • Cyre, W.R.,et a.l WISPAC: A parallel array computer for large- scale system simulation. Simulation, Nov. 1977, pp. 165–172.

    Google Scholar 

  • Derese, I., P. Stevens and Noldus, E.: The design of state observers of bilinear systems, Journal A, vol. 20, No. 4, 1979, pp. 183–202.

    Google Scholar 

  • Eykhoff, P.: System Identification. John Wiley, New York, 1974.

    Google Scholar 

  • Eykhoff, P.: Trends and Progress in System Identification, Pergamon Press, New York, 1981.

    MATH  Google Scholar 

  • Faro, A., Fortuna, L., and Gallo, A.: About the problem of estimating the System Order. IFAC Symp. on Identif. and Param. Estim., Washington, 1982, pp. 449–454.

    Google Scholar 

  • Fossard, H.J.: Multivariable System Control, North-Holland Publ. Co., Amsterdam, 1979.

    Google Scholar 

  • Goss, S.I.: Evaluation of Complex Models. Computers and Operations Research, vol. 4, 1977, pp. 27–35.

    Article  Google Scholar 

  • George, E.B. and Youngblood, J.N.: Parameter Estimation state Re-construction. (In: Multivariable Technological Systems, Atherton, D.P., Editor, Pergamon Press, New York, 1978, pp. 593–608 ).

    Google Scholar 

  • Goodwin, G.C. and Pyne, R.L.: Dynamic System Identification: Experiment Design and Data Analysis, Aca e ic Press, New York, 1977.

    MATH  Google Scholar 

  • Guidorzi, R.: Canonical Structures in the Identification of Multi- variable Systems. Automatica, vol. 11, 1975, pp. 361–374.

    Article  MathSciNet  MATH  Google Scholar 

  • Guidorzi, R.P. and Beghelli, S.: Input-output Multistructural Models in Multivariable Systems Identification, IFAC Symp. on Identif. and Param. Estim., Washington, 1982, pp. 461–465.

    Google Scholar 

  • Gupta, S.C.: Transport and State Variable Methods in Linear Systems. Wiley, New York, 1966.

    Google Scholar 

  • Hang, C.C.: A new form of stable adaptive observer. IEEE Trans. Autom. Contrl., vol. AC-21, No. 4, 1976, pp. 544–547.

    Article  Google Scholar 

  • Hu Yang-Zeng: Determination of the structure of multivariable system and its parameter estimation in canonical form. IFAC Symp. on Identif. and Param. Estim., Washington, 1982.

    Google Scholar 

  • Ioannou, P.A. and Kokotovic, P-V.: Adaptive Systems with Reduced Models. Springer, Berlin, 1983.

    Book  MATH  Google Scholar 

  • Johnson, C.R. Jr.: The common parameter estimation basis of adaptive filtering, idenfification and control. Proc. IEEE Conf. Decision and Control, Albuqueque, New Mexico, Dec. 1980, pp. 447–452.

    Google Scholar 

  • Kaczorek, T.: Proportional-integral observers for linear multivariable time-varying systems. Regelungstechnik, vol. 27, 1980, pp. 359–363.

    Google Scholar 

  • Kalman, R.E.: A New Approach to Linear Filtering and Prediction Problems. J. Basic Eng., Trans. ASME, Series D., vol. 82, No. 1, March 1960, pp. 35 - 45.

    Google Scholar 

  • King. R.E.: Parametric Sensitivity of Physiological System: Prognostic Analysis. IEEE Trans, on Biomed. Eng., vol. BME-14, 1967, No. 4, pp. 209–215.

    Article  Google Scholar 

  • Kudva, P. and Narendra, K.S.: Synthesis of an Adaptive Observer Using Lyapunov’s Direct Method, Int. J. Contr., vol. 18, pp. 1201–1210, Dec. 1973.

    Article  MathSciNet  MATH  Google Scholar 

  • Landau, I’.D.: Hyperstability and Identification. Proc. of the IEEE Symp. on Adaptive Processes, Univ. of Texas, Austin, Dec. 1970.

    Google Scholar 

  • Landau, I.D.: A Survey of Model Reference Adaptive Techniques- Theory and Applications. Automatica, vol. 13, 1977, pp. 507–517.

    Article  Google Scholar 

  • Landau, Y.D.: Adaptive Control: The Model Reference Approach. Marcel Dekker Inc., New York, 1979.

    MATH  Google Scholar 

  • Leondes, C.T. (Editor): Control and Dynamic Systems: Advances in Theory and Application., vol. 15, Academic Press, Neu York, 1979.

    Google Scholar 

  • Liu, Y.A. and Lapidus, L.: Observer Theory for Distributed-Parameter Systems. Internat. J. of Scie. Syst., voo. 7, 1976, pp. 731–742.

    Google Scholar 

  • Luders, G. and Narendra, K.S.: An Adaptive Observer and Identifier for Linear Systems. IEEE Trans. on Autom. Contr. vol. AC-19, 1974, pp. 117-119.

    Google Scholar 

  • Luders, G. and Narendra, K.S.: Stable adaptive Schemes for State Estimation and Identification of Linear Systems, IEEE Trans. on Autom. Contr., vol. AC-19, Dec. 1974, pp. 841-847.

    Google Scholar 

  • Luenberger, D.G.: Observers for Multivariable Systems. IEEE Trans. on Autom. Contr., vol. AC-11, 1966, pp. 190-197.

    Google Scholar 

  • Maybeck, P.S.: Stochastic Models, Estimation, and Control. Vol. 1,2. Academic Press, New York, 1979, 1982.

    Google Scholar 

  • Mehra, R.K. and Lainiotis, D.G.: System Identification: Advances and Case Studies, Academic Press, New York, 1976.

    Google Scholar 

  • Mendel, J.: Discrete Techniques of Parameter Estimations. Marcel Decker, Neu York, 1973.

    Google Scholar 

  • Möller, D., Popovic, D., and Thiele, G.: Modeling Simulation and Parameteter-Estimation of Human Cardiovascular Systems. Vieweg, Wiesbaden, 1983.

    Google Scholar 

  • Narendra,K.S., and P. Kudva: Stable Adaptive Schemes for System Identification and Control. Part I: IEEE Trans, on Systems Man and Cybernetics, vol. SMC-4, No. 6, 1974, pp. 542–551.

    Google Scholar 

  • Niemann, R.E., Fisher, D.G., and Seborg, D.E.: A revieu of process identification and parameter estimation techniques. Int. J. Control, vol. 13, 1971, pp. 209–264.

    Article  Google Scholar 

  • Paulsen, R.A. Jr. : Sensitivity Analysis and Improved Identification of a Systemic Arterial Model. IEEE Trans. on Biomed. Eng., vol. BME-29, 1982, pp. 164-177.

    Google Scholar 

  • Sage, A.P. and Melsa, J.L.: System Identification, Academic Press, Neu York, 1971.

    MATH  Google Scholar 

  • Schöne, A.: Simulation technischer Systeme. Carl Hanser Uerlag, München, 1974.

    MATH  Google Scholar 

  • Tank-Nielsen, C.: Sensitivity Analysis in System Dynamics. In: Elements of the System Dynamics Method. M.I.T. Press, 1980, pp. 185–201.

    Google Scholar 

  • Undink Ten Gate, A.J.: Improvement of Ljapunov model reference adaptive control systems in a noisy environment. Int. J. Contr., 1975, pp. 977 - 996.

    Google Scholar 

  • Zeitz, M.: Nichtlineare Beobachter, Regelungstechnik, Vol. 27, Heft 8, 1979, pp. 241–249.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1983 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Popović, D. (1983). State of the Art in Parameter and State Estimation of Complex Systems by Simulation. In: Ameling, W. (eds) First European Simulation Congress ESC 83. Informatik-Fachberichte, vol 71. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-69295-6_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-69295-6_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-12723-9

  • Online ISBN: 978-3-642-69295-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics