Approximation of closed-loop dynamics for dynamic real-time optimization calculations

Competitive global market conditions and demand-driven production are characteristics of the present day environment that industries face. In order to operate in a cost-optimal fashion, industrial plant economic optimization has conventionally been addressed via a multilevel process automation architecture with a time-scale separation. At the upper level, a real-time optimization (RTO) system performs economic optimization in response to demand changes or slow-varying disturbances affecting profit (Marlin and Hrymak, 1997; Darby et al., 2011). RTO interacts with the lower level process automation activities in a cascade fashion by providing economically optimal set-points for the underlying regulatory control system, which is typically model predictive control (Qin and Badgwell, 2003; Darby and Nikolaou, 2012).