Process profitability is an yes or no criterion for the successful long-term operation of industrial processes. This article describes the use of dynamic online economic process optimization to improve the performance of chemical processes. Different model-predictive control techniques have progressively been applied to coupled multivariable control problems and in many cases, especially in the petrochemical industry, the reference values are adjusted infrequently by stationary optimization based upon a rigorous nonlinear, stationary plant model (real-time optimization, RTO). In between these optimizations, however, the process may be operated suboptimally due to the presence of disturbances. Nonlinear,dynamic model-based optimization has been proposed recently to combine optimal operation and feedback control. In this paper, a model of the complex dynamics of a pilot-scale continuous catalytic distillation process is used to explore the potential benefits of online economics optimizing control strategies. We compare the direct economic optimization scheme with a compromise scheme, the economics-oriented tracking controller. The outcome of this work indicates that by using direct economics optimizing NMPC the plant economics can be handled better while guaranteeing the product specifications which are formulated as explicit constraints. (C) 2012 Elsevier Ltd. All rights reserved.