Advertisement

Neural networks as controllers

  • Avner Friedman
Part of the The IMA Volumes in Mathematics and its Applications book series (IMA, volume 67)

Abstract

Control of automobile engine operating under idle conditions, must operate far away from its optimal region of operation. The idling is highly nonlinear time-varying process influenced by electric loads, shifting from neutral to drive in automatic transmissions, and other periodic or random disturbances. Regulating the engine control by using physical modeling and traditional adaptive control is a difficult problem, because there are a number of unknown variables in the physical model, and because of random disturbances. This is precisely a situation where neural network control might offer an alternate and more effective approach.

Keywords

Neural Network Hide Layer Automatic Transmission Recurrent Network Neural Network Control 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    K.S. Narendra and K. Parthasarathy, Identification and control of dynamical systems using neural networks, IEEE Trans. on Neural Networks, 1 (1990), 4–227.CrossRefGoogle Scholar
  2. [2]
    K.S. Narendra and K. Parthasarathy, Gradient methods for the optimization of dynamical systems containing neural networks, IEEE Trans. on Neural Networks, 2 (1991), 252–262.CrossRefGoogle Scholar
  3. [3]
    G.V. Puskorius and L.A. Feldkamp, Neurocontrol on nonlinear dynamical systems with Kalman filter-trained recurrent networks, IEEE Trans. on Neural Networks, to appear.Google Scholar
  4. [4]
    Handbook of Intelligent Control. Neural, Fuzzy and Adaptive Approaches. Edited by D.A. White and D.A. Sofge, Van Nostrand, New York (1992).Google Scholar
  5. [5]
    B.K. Powell and J.A. Cook, Nonlinear low frequency phenomenological engine modeling and analysis, in “Proceedings of the 1987 American Control Conference,” vol 1 (1987), 336–340.Google Scholar
  6. [6]
    J.A. Cook and B.K. Powell, Modeling of an internal combustion engine for control analysis, IEEE Control Systems Magazine, 8 (1988), 20–26.CrossRefGoogle Scholar
  7. [7]
    G. Vachtsevanos, S.S. Farinwata and D.K. Pirvolvu-Fuzzy logic control of an automotive engine, IEEE Control system Magazine, 13 (1993), 62–68.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag New York, Inc. 1995

Authors and Affiliations

  • Avner Friedman
    • 1
  1. 1.Institute for Mathematics and its ApplicationsUniversity of MinnesotaMinneapolisUSA

Personalised recommendations