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2002 | 12 | 2 | 235-240
Tytuł artykułu

Neural network-based NARX models in non-linear adaptive control

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The applicability of approximate NARX models of non-linear dynamic systems is discussed. The models are obtained by a new version of Fourier analysis-based neural network also described in the paper. This constitutes a reformulation of a known method in a recursive manner, i.e. adapted to account for incoming data on-line. The method allows us to obtain an approximate model of the non-linear system. The estimation of the influence of the modelling error on the discrepancy between the model and real system outputs is given. Possible applications of this approach to the design of BIBO stable closed-loop control are proposed.
Słowa kluczowe
Rocznik
Tom
12
Numer
2
Strony
235-240
Opis fizyczny
Daty
wydano
2002
otrzymano
2002-01-21
poprawiono
2002-03-22
Twórcy
  • Institute of Control and Industrial Electronics, Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warsaw, Poland
Bibliografia
  • Chen S. and Billings S.A. (1989): Representation of non-linear Systems: The NARMAX Model. - Int. J. Contr., Vol. 49, No. 3, pp. 1013-1032.
  • Dwyer R.A. (1991): Higher-dimensional Voronoi diagrams in linear expectedtime. - Discr. Comput. Geom., Vol. 6, No. 4, pp. 343-367.
  • Dzieliński A. (1999): Bibo Stability of Approximate NARX Models. - Proc. Amer. Contr. Conf., ACC'99, San Diego, USA, pp. 4000-4002.
  • Dzieliński A. and Żbikowski R. (1995): Feedforward neural networks: n-D systems theoretic aspects. - Proc. Europ. Contr. Conf., Rome, Italy, Vol. 2, pp. 1595-1600.
  • Dzieliński A. and Żbikowski R. (1996): A new approach to neurocontrol based on Fourier analysis and non-uniform multi-dimensional sampling. - Appl. Math. Comp. Sci., Vol. 6, No. 3, pp. 463-483.
  • Leontaritis I.J. and Billings S.A. (1985): Input-output parametric models for non-linear systems. Part I: Deterministic non-linear systems. - Int. J. Contr., Vol. 41, No. 2, pp. 303-328.
  • Okabe A., Boots B. and Sugihara K. (1992): Spatial Tessellations. Concepts and Applications of Voronoi Diagrams. - Chichester: Wiley.
  • Pachpatte B.G. (1970): On some n-th order finite difference inequalities. - Proc. Nat. Acad. Sci., India, Sec. A, Vol. 40, No. IV, pp. 235-240.
  • Papoulis A. (1962): The Fourier Integral and Its Applications. - New York: McGraw-Hill.
  • Petersen D.P. and Middleton D. (1962): Sampling and Reconstruction of Wave-Number-Limited Functions in N-Dimensional Euclidean Spaces. - Inf. Contr., Vol. 5, No. 1-4, pp. 279-323.
  • Sanner R.M. and Slotine J.-J.E. (1992): Gaussian Networks for Direct Adaptive Control. - IEEE Trans. Neural Netw., Vol. 3, No. 6, pp. 837-863.
  • Stein E.M. and Weiss G. (1971): Introduction to Fourier Analysis on Euclidean Spaces. - Princeton: Princeton University Press.
  • Stroud A.H. (1971): Approximate Calculation of Multiple Integrals. - Englewood Cliffs: Prentice-Hall.
  • Tikhonov A.N. and Arsenin V.Y. (1977): Solution of Ill-posed Problems. - New York: Wiley.
  • Żbikowski R. and Dzieliński A. (1996): Non-uniform Sampling Approachto Control Systems Modelling with Feedforward Networks, In: Neural Adaptive Control Technology (R. Żbikowski and K.J. Hunt, Eds.). - Singapore, London: World Scientific, pp. 71-112.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.bwnjournal-article-amcv12i2p235bwm
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