When is constrained control necessary for large scale processes?

It is of significant practical interest to identify which processes will benefit from the use of constrained control algorithms, such as model predictive control, and which will not. Explicit conditions are derived that identify whether constraint-handling is needed for a particular process. The conditions can be computed directly from a transfer function model, a simulation model (ordinary/partial differential equations), or experimental input-output data. The formulation considers the effects of measurement noise, process disturbances, model uncertainties, plant directionality, and the quantity of experimental data