Feasibility of on-line reoptimization in batch processes

This work points out some serious drawbacks of the standard procedure for on-line optimization of batch processes. Commonly, at any given batch time, on-line measurement information is used to improve the estimate of the current state and the objective function is optimized again based on the estimated state. This strategy is useful when only the initial state is in error, but is unreliable in the more common case of an inaccurate dynamic model. Reoptimization based on the state estimates may then constitute a poor policy, even if perfect state estimates were available. Simulation examples of a semi-batch reactor are used to illustrate the associated pitfalls and to demonstrate what can be done to possibly detect and circumvent them.