A PROBABILISTIC APPROACH TO RUN-TO-RUN CONTROL

This paper considers model uncertainty in the run-to-run control probl em from a probabilistic viewpoint. The methodology assumes that the mo del parameters are stochastic and uses experimental input-output data off-line to characterize the probability distribution of the model par ameters. This naturally leads to the notions of probability of stabili ty and probability of performance as a means of evaluating run-to-run controllers, Analytic formulas for the probability of stability are gi ven for the particular case of an EWMA controller. When considering a more general notion of performance, the Monte Carlo method is used to approximate the probability of performance to a high degree of confide nce, This probabilistic approach to run-to-run control is then illustr ated on a virtual plasma etching reactor. Finally, the reliability of the method is investigated.