Abstract
Straight pull single crystal furnaces temperature control system has problem of the long time lag and nonlinearity, so the precise mathematic mode that is hard to build. Advanced control strategies show strong advantages for resolving these problems. This paper use artificial neural network modeling approach to establish single crystal furnace temperatures neural network control BP structure model, use adaptive method to control the temperature of the single crystal furnace.
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