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Abstract
Active control of jets exhausting into a two dimensional channel with insulated suction near the wall during monitoring with a neural network is described. The aim of this work is to simulate the possibility of controlling the flow pattern with a flip-flop phenomenon by suitable suction. In this case, output of a neural network is estimated satisfactorily based on 3 flow patterns from the teaching data. The periodic flow pattern at Reynolds number Re=1.0×103 is reduced by a less than 10% suction rate for primary jets. Then stable flow emerges as a result of feedback gain of the neural network. Since the control with suction does not have to be continuous, the power cost is reduced. The nonperiodic case at Re=1.0×104 is hard to control, but we achieved good control by use of a suitable suction rate with the neural network.
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