Assessing plant design with regard to MPC performance

•The economic disturbance cost index for zone constrained MPC is proposed.•The methodology is used to find the most profitable steady-state point within the range of all feasible operating points available for a given plant.•An optimal trajectory between the initial and the best operating point is d...

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Veröffentlicht in:Computers & chemical engineering 2016-11, Vol.94, p.180-211
Hauptverfasser: Strutzel, F.A.M., Bogle, I. David L.
Format: Artikel
Sprache:eng
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Zusammenfassung:•The economic disturbance cost index for zone constrained MPC is proposed.•The methodology is used to find the most profitable steady-state point within the range of all feasible operating points available for a given plant.•An optimal trajectory between the initial and the best operating point is defined.•Performing comparison between the index values of candidate flowsheets enable the control engineer to select the most appropriate design.•The use of the index is shown for an oil distillation column. Model Predictive Control is ubiquitous in the chemical industry and offers great advantages over traditional controllers. Notwithstanding, new plants are being projected without taking into account how design choices affect the MPC’s ability to deliver better control and optimization. Thus a methodology to determine if a certain design option favours or hinders MPC performance would be desirable. This paper presents the economic MPC optimization index whose intended use is to provide a procedure to compare different designs for a given process, assessing how well they can be controlled and optimised by a zone constrained MPC. The index quantifies the economic benefits available and how well the plant performs under MPC control given the plant’s controllability properties, requirements and restrictions. The index provides a monetization measure of expected control performance. This approach assumes the availability of a linear state-space model valid within the control zone defined by the upper and lower bounds of each controlled and manipulated variable. We have used a model derived from simulation step tests as a practical way to use the method. The impact of model uncertainty on the methodology is discussed. An analysis of the effects of disturbances on the index illustrates how they may reduce profitability by restricting the ability of a MPC to reach dynamic equilibrium near process restrictions, which in turn increases product quality giveaway and costs. A case of study consisting of four alternative designs for a realistically sized crude oil atmospheric distillation plant is provided in order to demonstrate the applicability of the index.
ISSN:0098-1354
1873-4375
DOI:10.1016/j.compchemeng.2016.07.007