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Energy flow control system based on neural compensator in the feedback path for autonomous energy source
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| Author(s) |
Lech M. Grzesiak, Jakub Sobolewski |
| Abstract |
In this paper an artificial neural network, which
realizes a nonlinear adaptive control algorithm, has been applied
in a control system of variable speed generating system. The
speed is adjusted automatically as a function of load power
demand. The controller employs a single layer neural network to
estimate the unknown plant nonlinearities online. Optimization
of the controller is difficult because the plant is nonlinear and no
stationary. Furthermore it deals with the situation where the
plant becomes uncontrollable without any restrictive
assumptions. In contrast to previous work [1] on the same
subject, the number of neural networks has been reduced to only
one network. The number of the neurons in a network structure
as well as choosing certain design parameters was specified a
priori. The computer test results have been presented to show
performance of proposed neural controller. |
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| Filename: | 039 |
| Filesize: | 771.4 KB |
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| Type |
Members Only |
| Date |
Last modified 2006-02-08 by System |
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