Application of plantwide control to the HDA process. I—steady-state optimization and self-optimizing control

This paper describes the application of self-optimizing control to a large-scale process, the HDA plant. The idea is to select controlled variables which when kept constant lead to minimum economic loss. First, the optimal active constraints need to be controlled. Next, controlled variables need to be found for the remaining unconstrained degrees of freedom. In order to avoid the combinatorial problem related to the selection of outputs/measurements for such large plants, a local (linear) analysis based on singular value decomposition (SVD) is used for pre-screening. This is followed by a more detailed analysis using the nonlinear model. Note that a steady-state model, in this case one built in Aspen Plus, is sufficient for selecting controlled variables. A dynamic model is required to design and test the complete control system which include regulatory control. This is considered in the part II of the series. r 2006 Elsevier Ltd. All rights reserved.