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Fuzzy predictive R2R control to CMP process

机译:CMP过程的模糊预测R2R控制

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摘要

For chemical mechanical polishing (CMP) process characteristics of nonlinear, time-varying and not easily being in-situ measured, this paper proposes a CMP process fuzzy predictive run-to-run (R2R) controller named FPR2R. CMP T-S fuzzy predictive model is off-line and on-line identified by algorithms of fuzzy clustering and recursive least squares with forgetting factor, thus problem of constructing accurate mathematical model of complicated CMP is solved and error of modeling is reduced. Recipe is calculated by multivariable generalized predictive control (GPC) method, therefore it improves control precision. Simulation results illustrate that proposed CMP FPR2R controller is better than EWMA control scheme about performance, variation in various runs of products is reduced substantially, process drifts and shifts is suppressed significantly. Compared to EWMA, root mean squared error for material removal rate(MRR) is decreased.
机译:针对非线性,时变且不易现场测量的化学机械抛光(CMP)工艺特征,提出了一种名为FPR2R的CMP工艺模糊预测运行对运行(R2R)控制器。通过模糊聚类和具有遗忘因子的递推最小二乘算法离线和在线识别CMP T-S模糊预测模型,从而解决了构建复杂CMP精确数学模型的问题,减少了建模误差。配方是通过多变量广义预测控制(GPC)方法计算的,因此可以提高控制精度。仿真结果表明,所提出的CMP FPR2R控制器在性能上优于EWMA控制方案,大大减少了产品各种运行中的偏差,显着抑制了工艺漂移和偏移。与EWMA相比,材料去除率(MRR)的均方根误差降低了。

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