Share This Article:

Adaptation in Stochastic Dynamic Systems—Survey and New Results II

Abstract Full-Text HTML Download Download as PDF (Size:1859KB) PP. 266-285
DOI: 10.4236/ijcns.2011.44032    3,244 Downloads   6,988 Views   Citations

ABSTRACT

This paper surveys the field of adaptation in stochastic systems as it has developed over the last four decades. The author’s research in this field is summarized and a novel solution for fitting an adaptive model in state space (instead of response space) is given.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

I. Semushin, "Adaptation in Stochastic Dynamic Systems—Survey and New Results II," International Journal of Communications, Network and System Sciences, Vol. 4 No. 4, 2011, pp. 266-285. doi: 10.4236/ijcns.2011.44032.

References

[1] L. Ljung, “Perspectives on System Identification,” Annual Reviews in Control, Vol. 34, No. 1, 2010, pp. 1-12. doi:10.1016/j.arcontrol.2009.12.001
[2] M. Gevers, “System Identification without Lennart Ljung: What Would Have Been Different?” In: T. Glad and G. Hendeby, Eds., Forever Ljung in System Identification, Studentlitteratur AB, Norrtalje, 2006.
[3] B. D. O. Anderson, “Two Decades of Adaptive Control Pitfalls,” Proceedings of the 8th International Conference on Control, Automation, Robotics and Vision, Kunming, December 2004.
[4] V. V. Terekhov and I. Y. Tyukin, “Adaptive Control Systems: Issues and Tendencies,” Control and Information Technology, St. Petersburg University of Information Technology, St. Petersburg, 2003, pp. 146-154.
[5] L. Ljung, “Convergence Analysis of Parametric Identification Methods,” IEEE Transactions on Automatic Control, Vol. AC-23, No. 5, 1978, pp. 770-783. doi:10.1109/TAC.1978.1101840
[6] L. Ljung, “System Identification: Theory for the User,” Prentice-Hall, Inc., Englewood Cliffs, 1987.
[7] I. V. Semushin, “Adaptation in Stochastic Dynamic Systems—Survey and New Results I,” International Journal of Communications, Network and System Sciences, Vol. 4, No. 1, 2011, pp. 17-23. doi:10.4236/ijcns.2011.41002
[8] R. K. Mehra, “Approaches to Adaptive Filtering,” IEEE Transactions on Automatic Control, Vol. AC-17, No. 5, 1972, pp. 693-698. doi:10.1109/TAC.1972.1100100
[9] R. E. Kalman, P. L. Falb and M. A. Arbib, “Topics in Mathematical System Theory,” McGraw Hill, Boston, 1969.
[10] L. Prouza, “Bemerkung Zur Linearen Prediktoren Mittels Eines Lernenden Filters,” Transactions of the 1st Prague Conference on the Information Theory and Statistical Decision Functions, Prague, 28-30 November 1956, pp. 37-41.
[11] O. Sefl, “Filters and Predictors Which Adapt Their Values to Unknown Parameters of the Input Process,” Transactions of the 2nd Prague Conference on the Information Theory and Statistical Decision Functions, Prague, 1961, pp. 597-608.
[12] A. A. Gorsky, “Automatic Optimal Filtering,” Transactions on Power Engineering and Automation, USSR Academy of Sciences, Engineering Division, Moscow, No. 4, 1962, pp. 3-30.
[13] I. V. Semushin, “Use of Active Principle for Filtering Non-stationary Random Processes,” Proceedings of the 3rd Science and Technology Conference—Novgorod LETI Branch, St. Petersburg, 1968, p. 64.
[14] I. V. Semushin, “Multi-Channel Adaptive Filter of Active Type,” Transactions on Instrument Making, USSR University, Moscow, Vol. 12, No. 10, 1969, pp. 47-50.
[15] I. V. Semushin, “Closed Loop Adaptive Filters Investigation,” Ph.D. Thesis, V. I. Ulyanov (Lenin) Saint Petersburg Electrotechnical University, St. Petersburg, 1970.
[16] P. E. Caines, “Linear Stochastic Systems,” John Wiley and Sons, Inc., Hoboken, 1988.
[17] P. Lancaster and L. Rodman, “Algebraic Riccati Equations,” Oxford University Press, Inc., Oxford, 1995.
[18] V. N. Fomin, “Reccurent Estimation and Adaptive Filtering,” Nauka, Moscow, 1984.
[19] W. M. Wohnam, “Linear Multivariable Control—A Geomentic Approach,” Springer-Verlag, Berlin, 1974.
[20] P. S. Maybeck, “Stochastic Models, Estimation, and Control,” Vol. 1, Academic Press, Cambridge, 1979.
[21] B. D. O. Anderson and J. V. Moore, “Optimal Filtering,” Prentice-Hall, Inc., Englewood Cliffs, 1979.
[22] J. S. Meditch, “Stochastic Optimal Linear Filtering and Control,” McGraw Hill, Boston, 1969.
[23] S. Sherman, “Non-Mean-Square Error Criteria,” IRE Transactions on Information Theory, Vol. IT-4, 1958, p. 125. doi:10.1109/TIT.1958.1057451
[24] I. V. Semushin, “Active Methods of Adaptation and Control for Discrete-Time Systems,” D.Sc. Dissertation, Leningrad State University of Aerospace Instrumentation “LIAP”, St. Petersburg, April 1987.
[25] I. V. Semushin, “Identification of Linear Stochastic Plants from the Incomplete Noisy Measurements of the State Vector,” Automation and Remote Control, USSR Academy of Sciences, Moscow, Vol. 45, No. 8, 1985, pp. 61-71.
[26] R. L. T. Hampton, “Unsupervised Learning of the Kalman Filter,” Electronics Letters, Vol. 9, No. 17, 1971, pp. 383-384.
[27] R. L. T. Hampton, “On Unknown State-Dependent Noise, Modeling Errors and Adaptive Filtering,” Electronics Letters, Vol. 2, No. 2-3, 1975, pp. 195-201.
[28] D. Perriot-Mathonna, “The Use of Ljung’s Results for Studuing the Convergence Properties of Hampton’s Adaptive Filter,” IEEE Transactions on Automatic Control, Vol. AC-25, No. 6, 1980, pp. 1165-1169.
[29] I. V. Semushin, “Adaptive Identification and Fault Detection Methods in Random Signal Processing,” Saratov University Publishers, Saratov, 1985.
[30] I. V. Semushin, “Active Adaptation of the Optimal Discrete Filters,” Transactions on Engineering Cybernetics, USSR Academy of Sciences, Moscow, No. 5, 1975, pp. 192-198.
[31] P. Van Overschee and B. De Moor, “Subspace Identification for Linear Systems: Theory—Implementation—Applications,” Kluwer Academic Publishers, Norwell, 1996.
[32] C. Broxmeyer, “Inertial Navigation Systems,” McGraw-Hill Book Company, Boston, 1956.
[33] I. V. Semushin, “Identifying Parameters of Linear Stochastic Differential Equations from Incomplete Noisy Measurements,” Recent Developments in Theories & Numerics—International Conference on Inverse Problems, Hong Kong, January 2002, pp. 281-290.
[34] O. Yu. Gorokhov and I. V. Semushin , “Developing a Simulation Toolbox in MATLAB and Using It for Non-linear Adaptive Filtering Investigation,” Lecture Notes in Computer Science, Vol. 2658, 2003, pp. 436-445. doi:10.1007/3-540-44862-4_46
[35] V. I. Denisov, et al., “Active Parameter Identification of Stochastic Linear Systems,” NSTU Publisher, Novosibirsk, 2009.
[36] R. K. Mehra, “Optimal Input Signals for Parameter Estimation in Dynamic Systems—Survey and New Results,” IEEE Transactions on Automatic Control, Vol. AC-19, No. 6, 1974, pp. 753-768. doi:10.1109/TAC.1974.1100701

  
comments powered by Disqus

Copyright © 2018 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.