Self-Optimizing Steady-State Back-Off Approach for Control Structure Selection

The selection of suitable control structures has an important influence on the economic performance of process systems in the presence of disturbances. Economics has been incorporated in the control structure selection problem using different formulations based on different criteria. The back-off approach is based on the idea of minimizing the economic loss that results from the need to back off from the active constraints to avoid violating them in the presence of disturbances. On the other hand, self-optimizing control schemes aim at selecting controlled variables and constant setpoint values, such that the economic loss with respect to optimal operation is minimized in the presence of disturbances. This paper presents a comprehensive study of different formulations of the back-off approach that pays attention to steady-state feasibility in the presence of disturbances. We argue that the back-off approach that selects controlled variables and optimal setpoint values by minimizing the average cost in the presence of disturbances is a global self-optimizing control approach. The performance of the different formulations is compared by means of three different case studies.