A detailed dynamic simulator of a propylene/propane (C-3) splitter, which was bench-marked against industrial data, has been used to compare dual composition control performance for a diagonal PI controller and several advanced controllers. The advanced controllers considered are DMC, nonlinear process model based control, and artificial neural networks. Each controller was tuned based upon setpoint changes in the overhead product composition using 50% changes in the impurity levels. Overall, there was not a great deal of difference in controller performance based upon the setpoint and disturbance tests. Periodic step changes in feed composition were also used to compare controller performance. In this case, oscillatory variations of the product composition were observed and the variabilities of the DMC and nonlinear process model based controllers were substantially smaller than that of the PI controller. The sensitivity of each controller to the frequency of the periodic step changes in feed composition was also investigated.