The common attribute in horizon-predictive control is the use of a dynamic model of the process and optimization to plan a sequence of future control actions to best make the model match a desired future path, while avoiding constraints. This paper describes a structure to use first-principles process models in horizonpredictive control, which contrasts the conventional use of linear empirical models derived from step-testing the process.