Simultaneous cyclic scheduling and optimal control of polymerization reactors

Terrazas-Moreno, Sebastian; Flores‐Tlacuahuac, Antonio; Grossmann, Ignacio E.

doi:10.1002/aic.11247

Cited by 73 publications

(53 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Economic benefit has also been shown for simultaneous selection of linear controllers for grade transitions and scheduling, ensuring that the process dynamics from the controller selection are accounted for in the scheduling problem [23]. Terrazas-Moreno et al also demonstrate the benefits of process dynamics in cyclic scheduling for continuous chemical processes [45]. Capon-Garcia et al prove the benefit of implementing process dynamics in batch scheduling via an MIDO problem [6].…”

Section: Previous Workmentioning

confidence: 97%

Economic Benefit from Progressive Integration of Scheduling and Control for Continuous Chemical Processes

et al. 2017

View full text Add to dashboard Cite

Performance of integrated production scheduling and advanced process control with disturbances is summarized and reviewed with four progressive stages of scheduling and control integration and responsiveness to disturbances: open-loop segregated scheduling and control, closed-loop segregated scheduling and control, open-loop scheduling with consideration of process dynamics, and closed-loop integrated scheduling and control responsive to process disturbances and market fluctuations. Progressive economic benefit from dynamic rescheduling and integrating scheduling and control is shown on a continuously stirred tank reactor (CSTR) benchmark application in closed-loop simulations over 24 h. A fixed horizon integrated scheduling and control formulation for multi-product, continuous chemical processes is utilized, in which nonlinear model predictive control (NMPC) and continuous-time scheduling are combined.

show abstract

Section: Previous Workmentioning

confidence: 97%

Economic Benefit from Progressive Integration of Scheduling and Control for Continuous Chemical Processes

et al. 2017

View full text Add to dashboard Cite

show abstract

“…The dynamic, discrete and continuous behaviour of these systems give rise to mixed integer dynamic optimization (MIDO). This type of problems typically occur in the scheduling and control of polymerization reactors [255][256][257][258][259]. The the most common approach for solving MIDO problems is to discretize the system of differential equations through orthogonal collocation, yielding large scale MINLP models.…”

Section: Planning and Schedulingmentioning

confidence: 99%

“…The dynamic models with mixed discrete and continuous variables are called hybrid systems (which are MIDO problems in general). Start-up and shut-down operations [262], batch systems [263], and grade transitions [258,259] are some of the main applications of optimization of hybrid systems. Several hybrid formulations have been developed and implemented in recent years [264][265][266][267][268][269][270][271].…”

Section: Process Controlmentioning

confidence: 99%

Review of Mixed‐Integer Nonlinear and Generalized Disjunctive Programming Methods

Trespalacios

Grossmann

2014

Chemie Ingenieur Technik

155

View full text Add to dashboard Cite

This work presents a review of the applications of mixed-integer nonlinear programming (MINLP) in process systems engineering (PSE). A review on the main deterministic MINLP solution methods is presented, including an overview of the main MINLP solvers. Generalized disjunctive programming (GDP) is an alternative higher-level representation of MINLP problems. This work reviews some methods for solving GDP models, and techniques for improving MINLP methods through GDP. The paper also provides a high-level review of the applications of MINLP in PSE, particularly in process synthesis, planning and scheduling, process control and molecular computing.

show abstract

“…As the complexity of the addressed production system grows, so does the solution of the underlying optimization problem. In previous works [2,5] we have addressed the efficient solution of SC problems by casting as Mixed-Integer Dynamic Optimization (MIDO) problem that upon proper transformation can be transformed into Mixed-Integer Non-Linear Programs (MINLP).…”

Section: Introductionmentioning

confidence: 99%

Simultaneous Cyclic Scheduling and Control of Tubular Reactors: Parallel Production Lines

Flores‐Tlacuahuac

Grossmann

2011

Ind. Eng. Chem. Res.

Self Cite

View full text Add to dashboard Cite

In this work we propose a simultaneous scheduling and control optimization formulation to address both optimal steady-state production and dynamic product transitions in multiproduct tubular reactors working in several parallel production lines. Because the problem involves integer and continuous variables and the dynamic behavior of the underlying system the resulting optimization problem is cast as a Mixed-Integer Dynamic Optimization (MIDO) problem. Moreover, because spatial and temporal variations are considered when modeling the addressed systems, the dynamic systems give rise to a system of one-dimensional partial differential equations. For solving the MIDO problems we transform them into a mixed-integer nonlinear programs (MINLP). We use the method of lines for spatial discretization, whereas orthogonal collocation on finite elements was used for temporal discretization. The proposed simultaneous scheduling and control formulation is tested using three multiproduct continuous tubular reactors featuring complex nonlinear behavior.2

show abstract

Simultaneous cyclic scheduling and optimal control of polymerization reactors

Abstract: 2

Cited by 73 publications

References 16 publications

Economic Benefit from Progressive Integration of Scheduling and Control for Continuous Chemical Processes

Economic Benefit from Progressive Integration of Scheduling and Control for Continuous Chemical Processes

Review of Mixed‐Integer Nonlinear and Generalized Disjunctive Programming Methods

Simultaneous Cyclic Scheduling and Control of Tubular Reactors: Parallel Production Lines

Contact Info

Product

Resources

About