TY - JOUR N2 - 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. L1 - http://journals.pan.pl/Content/111726/PDF-MASTER/(54-3)335.pdf L2 - http://journals.pan.pl/Content/111726 PY - 2006 IS - No 3 EP - 340 KW - neural networks KW - neurocontrollers KW - control systems KW - power electronics A1 - Grzesiak, L.M. A1 - Sobolewski, J. VL - vol. 54 DA - 2006 T1 - Energy flow control system based on neural compensator in the feedback path for autonomous energy source SP - 335 UR - http://journals.pan.pl/dlibra/publication/edition/111726 T2 - Bulletin of the Polish Academy of Sciences Technical Sciences ER -