首页> 外文会议>IMECE2009;ASME international mechanical engineering congress and exposition >STUDY ON MODEL PREDICTIVE CONTROL TO MINIMIZE TEMPERATURE CHANGE OF VERTICAL PLATE WITH VARYING HEAT GENERATION
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STUDY ON MODEL PREDICTIVE CONTROL TO MINIMIZE TEMPERATURE CHANGE OF VERTICAL PLATE WITH VARYING HEAT GENERATION

机译:产生热量变化最小化垂直板温度变化的模型预测控制研究

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Precise process temperature control of 0.001°C under circumstances of noise-temperature change of 0.1 °C is required in semiconductor manufacturing process. We studied optimum control method to minimize temperature change at an object position in a 2-dimensional vertical plate with a varying noise-heat-generation and a control-heater. We numerically calculated 2-dimensional unsteady thermal conduction in the plate with feedback control, feedforward control, and model predictive control of the control-heat-generation. The temperature change at the object position can be decreased 1/80 times smaller than that without control-heat-generation using the feedback control with two monitoring temperatures. The temperature change at the object position can be decreased 1/1000 times (0.002°C) using the model predictive control of 5 s interval with step response pattern as a dynamic predictive model. We found that the accuracy of the dynamic predictive model is very important for precise temperature control. Experiment was performed for the model predictive control with a network model as the dynamic predictive model, and the experimental result agreed with the calculation result.
机译:在半导体制造工艺中,在噪声温度变化为0.1°C的情况下,需要将工艺温度精确控制在0.001°C。我们研究了一种最佳控制方法,该方法可以最大程度地降低二维垂直板中物体位置处的温度变化,并具有可变的噪声生热和控制加热器。我们用反馈控制,前馈控制和模型预测控制来控制热量的产生,以二维方式计算板中的二维非稳态热传导。使用带有两个监控温度的反馈控制,与没有控制发热的情况相比,物体位置的温度变化可以减小1/80倍。使用5 s间隔的模型预测控制以及阶跃响应模式作为动态预测模型,可以降低目标位置的温度变化1/1000倍(0.002°C)。我们发现动态预测模型的准确性对于精确的温度控制非常重要。以网络模型为动态预测模型对模型预测控制进行了实验,实验结果与计算结果吻合。

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