Applications of Intelligent Control to Engineering Systems: by Kimon P. Valavanis

By Kimon P. Valavanis

This e-book displays the paintings of most sensible scientists within the box of clever keep watch over and its functions, prognostics, diagnostics, situation dependent upkeep and unmanned platforms. It contains effects, and provides how concept is utilized to unravel actual problems.

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Additional resources for Applications of Intelligent Control to Engineering Systems: In Honour of Dr. G. J. Vachtsevanos (Intelligent Systems, Control and Automation: Science and Engineering)

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29. W. Weibull, A statistical distribution function of wide applicability, Journal of Applied Mechanics 18, 293, 1951. 30. S. A. Gershenfeld, Time Series Prediction: Forecasting the Future and Understanding the Past, Addison-Wesley, MA, 1993. 31. J. Werbos, Generalization of back propagation with application to recurrent gas market model, Neural Networks 1, 339–356, 1988. Chapter 2 Advances in Uncertainty Representation and Management for Particle Filtering Applied to Prognostics∗ Marcos Orchard, Gregory Kacprzynski, Kai Goebel, Bhaskar Saha and George Vachtsevanos Abstract Particle filters (PF) have been established as the de facto state of the art in failure prognosis.

Liu and R. Chen, Sequential Monte Carlo methods for dynamical systems, Journal for American Statistical Association 93, 1032–1044, 1998. 15. L. , Prentice-Hall, New Jersey, 1999. 16. A. V. M. V. A. Feldkamp and D. Roller, Applications of neural networks to the construction of virtual sensors and model-based diagnostics, in Proceedings of ISATA 29th International Symposium on Automotive Technology and Automation, 3–6 June, pp. 133–138, 1996. 17. L. Minsky, Step toward artificial intelligence, Proceedings IRE 49, 8–30, 1961.

Shiroishi, Y. Li, S. Liang, T. Kurfess and S. Danyluk, Bearing condition diagnostics via vibration and acoustic emission measurements, Mechanical Systems and Signal Processing 11(5), 693–705, September 1997. 24. F. Specht, A general regression neural network, IEEE Transactions on Neural Networks 2(6), 568–576, November 1991. 25. L. Studer and F. Masulli, On the structure of a neuro-fuzzy system to forecast chaotic time series, in Proceedings of the International Symposium on Neuro-Fuzzy Systems, 29–31 August, pp.

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