A Kalman filter-based R2R control system with parallel stochastic disturbance models for semiconductor manufacturing processes

作者：Kim Huiyong; Park Jun Hyung; Lee Kwang Soon^*

来源：Journal of Process Control, 2014, 24(12): 119-124.

DOI：10.1016/j.jprocont.2014.09.001

• Semiconductor process
• R2R control
• EWMA filter
• Kalman filter
• IAR(1,1)
• IMA(1,1)

A Kalman filter-based run-to-run control system has been proposed for minimum variance control of semiconductor manufacturing process. In the proposed control system, both gain- and bias-varying process models combined with different stochastic disturbance models were considered and identified in parallel. The best-fit model is selected and used for the R2R controller design. Sub-models of the ARIMA(1,1,1) process were considered for stochastic modeling of the bias and gain variation, and the Kalman filters are used to find the optimum model parameter estimation. The control performance was analyzed for each case of the disturbance model to investigate the expected benefit from the control system in comparison with the EWMA filter-based controller.

• 出版日期2014-12