Kimon P. Valavanis's Applications of Intelligent Control to Engineering Systems: PDF

By Kimon P. Valavanis

ISBN-10: 9048130174

ISBN-13: 9789048130177

This ebook displays the paintings of most sensible scientists within the box of clever regulate and its purposes, prognostics, diagnostics, dependent upkeep and unmanned platforms. It comprises effects, and offers how concept is utilized to unravel actual problems.

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Read Online or Download Applications of Intelligent Control to Engineering Systems: In Honour of Dr. G. J. Vachtsevanos (Intelligent Systems, Control and Automation: Science and Engineering) PDF

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Extra info 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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The range for short-term predictions depends on the system under analysis, although a 5-step is recommended to ensure rapid adaptation of the scheme. Outer correction loops may be also implemented using neural networks, fuzzy expert systems, PID controllers, among others. Additional correction loops include the modification of the number of particles used for 1-step or long-term prediction purposes and the reduction of the threshold for the use of the importance resampling algorithm. 4 An Illustrative Example As an illustrative example, consider the case of propagating fatigue crack on a critical component in a rotorcraft transmission system.

Khiripet, G. Vachtsevanos, A. Thakker and T. Galie, A new confidence prediction neural network for machine failure prognosis, in Proceedings of Intelligent Ships Symposium IV, Philadelphia, PA, April 2–3, 2001. 3. , A general regression neural network, IEEE Transactions on Neural Networks 2(6), 568–576, November 1991. 4. A. A. Kramer, Radial basis function networks for classifying process faults, IEEE Control Systems 11, 31–38, 1991. 5. A. Cruse, Probabilistic Systems Modeling and Validation, HCF 2004, March 16–18, 2004.

1 = 2 M N m=1 n=−N ⎛ αn βm ⎝ Np −1 ⎞ αn βm sin((mNt + n)θ¯ ) + sin((mNt + n)(θ¯ + δ))⎠ . 11) Due to this phase shift, when mNt + n is not a multiple of Np , the vibration components from different gears are not evenly spaced. 10a. It is obvious that the vibration components are not canceled in this case. This results in higher NonRMC frequency components. On the other hand, when mNt + n is a multiple of Np , the vibration components from different gears are not exactly in phase. 10b. 11. The components in the circles are the NonRMC.

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Applications of Intelligent Control to Engineering Systems: In Honour of Dr. G. J. Vachtsevanos (Intelligent Systems, Control and Automation: Science and Engineering) by Kimon P. Valavanis


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