ポンプ-管路系のリカレントニューラルネットワークによる特性同定を用いた多変数最適プログラム制御

概要

論文の詳細を見る
Fluctuation waves of pressure and flow rate in closed pipe-system are obtained by a pump and a valve controlled with cyclic and arbitrary operation of rotational speed and valve opening. A recurrent neural-network computer program learns response characteristics of the system. Rotational speed of pump and valve opening are obtained from this neural-network computing so that pressure and flow rate achieves required variation. This control method is studied in this report. And this method is investigated on computing simulation of the pipe system as preliminary step toward applying experimental apparatus. It made clear that, if variable time-series are measured from the operated system, target fluctuations can generate with high accuracy by using the recurrent neural network computing which has learned the response characteristics, without using characteristics of each device.
2004-12-08