(629c) A Multiparametric Programming Based Approach to Integrate Design, Scheduling, and Control of a Batch Process | AIChE

(629c) A Multiparametric Programming Based Approach to Integrate Design, Scheduling, and Control of a Batch Process


Burnak, B. - Presenter, Texas A&M University
Pistikopoulos, E., Texas A&M Energy Institute, Texas A&M University
Integrating short term (control), middle term (schedule), and long term (design) decisions has been shown to improve the operability and profitability of batch processes [1]. The interactions between these distinct time-scale decisions allow for opportunities to (i) replace fixed recipe-based schedules with detailed model-based schedules, (ii) build design dependent schedule aware controllers, and (iii) reduce capital costs by circumventing overdesigned processing units. While the efficiency of simultaneous decision making in process systems is greatly acknowledged, the methodology/procedure to achieve an effective integration is still an open question due to the order of magnitude differences in the time scales of the constituent problems, as well as their respective objectives. The most recent advances within the last decade [2-7] depict a promising basis for further improvement.

In this work, we present a unified framework to simultaneously determine the optimal codependent short term and middle term operating strategies of a batch process for a range of market conditions, while minimizing the capital costs. A single high fidelity model is utilized to develop (i) multiparametric rolling horizon optimization (mpRHO) strategies as a function of process states and time variant market conditions, and (ii) multiparametric Model Predictive Control (mpMPC) for effective set-point tracking, following a similar methodology described in Burnak et al [8]. The design of the process is accounted for as an additional unknown bounded parameter in the offline operational strategies. The offline nature of mpRHO and mpMPC strategies allows for integration in the design optimization of the process, i.e. minimizing the capital costs. The framework is showcased on (i) a single non-isothermal batch reactor, and (ii) a batch process comprising a preprocessing unit, a reactor, and a post-processing unit.

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