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Random disturbance inputs cause state uncertainty. The consequence becomes more severe when the disturbance input is time-correlated, hence non-white. Run Out Table (ROT) cooling is a complex multistage process with inherent long time delay. This intrinsic characteristic of such extensive time lag, which triggers time-correlation, makes the run out table cooling process attractive to investigate stochastic optimization methods for tracking the temperature trajectory along its stages. The merit of this approach is demonstrated by simulation experiments. The results show the state propagation and robust tracking performance in the presence of stochastic timecorrelated disturbance inputs.

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