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Records with Keyword: Model Predictive Control
Showing records 223 to 228 of 228. [First] Page: 1 6 7 8 9 10 Last
Economic Benefit from Progressive Integration of Scheduling and Control for Continuous Chemical Processes
Logan D. R. Beal, Damon Petersen, Guilherme Pila, Brady Davis, Sean Warnick, John D. Hedengren
July 31, 2018 (v1)
Keywords: dynamic market, integration, market fluctuations, Model Predictive Control, nonlinear, process disturbances, Scheduling
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.
A Validated Model for Design and Evaluation of Control Architectures for a Continuous Tablet Compaction Process
Fernando Nunes de Barros, Aparajith Bhaskar, Ravendra Singh
July 31, 2018 (v1)
Keywords: continuous manufacturing, critical quality attributes, Model Predictive Control, nonlinear model, quality by control, tablet press
The systematic design of an advanced and efficient control strategy for controlling critical quality attributes of the tablet compaction operation is necessary to increase the robustness of a continuous pharmaceutical manufacturing process and for real time release. A process model plays a very important role to design, evaluate and tune the control system. However, much less attention has been made to develop a validated control relevant model for tablet compaction process that can be systematically applied for design, evaluation, tuning and thereby implementation of the control system. In this work, a dynamic tablet compaction model capable of predicting linear and nonlinear process responses has been successfully developed and validated. The nonlinear model is based on a series of transfer functions and static polynomial models. The model has been applied for control system design, tuning and evaluation and thereby facilitate the control system implementation into the pilot-plant wi... [more]
A General State-Space Formulation for Online Scheduling
Dhruv Gupta, Christos T. Maravelias
July 31, 2018 (v1)
Keywords: bio-manufacturing, mixed-integer linear programming, Model Predictive Control, state-space model, uncertainty
We present a generalized state-space model formulation particularly motivated by an online scheduling perspective, which allows modeling (1) task-delays and unit breakdowns; (2) fractional delays and unit downtimes, when using discrete-time grid; (3) variable batch-sizes; (4) robust scheduling through the use of conservative yield estimates and processing times; (5) feedback on task-yield estimates before the task finishes; (6) task termination during its execution; (7) post-production storage of material in unit; and (8) unit capacity degradation and maintenance. Through these proposed generalizations, we enable a natural way to handle routinely encountered disturbances and a rich set of corresponding counter-decisions. Thereby, greatly simplifying and extending the possible application of mathematical programming based online scheduling solutions to diverse application settings. Finally, we demonstrate the effectiveness of this model on a case study from the field of bio-manufacturin... [more]
Dynamical Scheduling and Robust Control in Uncertain Environments with Petri Nets for DESs
Dimitri Lefebvre
July 31, 2018 (v1)
Keywords: discrete event systems, Model Predictive Control, scheduling problems, stochastic Petri nets, timed Petri nets
This paper is about the incremental computation of control sequences for discrete event systems in uncertain environments where uncontrollable events may occur. Timed Petri nets are used for this purpose. The aim is to drive the marking of the net from an initial value to a reference one, in minimal or near-minimal time, by avoiding forbidden markings, deadlocks, and dead branches. The approach is similar to model predictive control with a finite set of control actions. At each step only a small area of the reachability graph is explored: this leads to a reasonable computational complexity. The robustness of the resulting trajectory is also evaluated according to a risk probability. A sufficient condition is provided to compute robust trajectories. The proposed results are applicable to a large class of discrete event systems, in particular in the domains of flexible manufacturing. However, they are also applicable to other domains as communication, computer science, transportation, an... [more]
Integration of RTO and MPC in the Hydrogen Network of a Petrol Refinery
Cesar de Prada, Daniel Sarabia, Gloria Gutierrez, Elena Gomez, Sergio Marmol, Mikel Sola, Carlos Pascual, Rafael Gonzalez
July 31, 2018 (v1)
Keywords: hydrogen networks, Model Predictive Control, petrol refineries, real-time optimization
This paper discusses the problems associated with the implementation of Real Time Optimization/Model Predictive Control (RTO/MPC) systems, taking as reference the hydrogen distribution network of an oil refinery involving eighteen plants. This paper addresses the main problems related to the operation of the network, combining data reconciliation and a RTO system, designed for the optimal generation and redistribution of hydrogen, with a predictive controller for the on-line implementation of the optimal policies. This paper describes the architecture of the implementation, showing how RTO and MPC can be integrated, as well as the benefits obtained in terms of improved information about the process, increased hydrocarbon load to the treatment plants and reduction of the hydrogen required for performing the operations.
Model Predictive Control of the Exit Part Temperature for an Austenitization Furnace
Hari S. Ganesh, Thomas F. Edgar, Michael Baldea
July 30, 2018 (v1)
Keywords: austenitization, Energy Efficiency, iron and steel, Model Predictive Control
Quench hardening is the process of strengthening and hardening ferrous metals and alloys by heating the material to a specific temperature to form austenite (austenitization), followed by rapid cooling (quenching) in water, brine or oil to introduce a hardened phase called martensite. The material is then often tempered to increase toughness, as it may decrease from the quench hardening process. The austenitization process is highly energy-intensive and many of the industrial austenitization furnaces were built and equipped prior to the advent of advanced control strategies and thus use large, sub-optimal amounts of energy. The model computes the energy usage of the furnace and the part temperature profile as a function of time and position within the furnace under temperature feedback control. In this paper, the aforementioned model is used to simulate the furnace for a batch of forty parts under heuristic temperature set points suggested by the operators of the plant. A model predict... [more]
Showing records 223 to 228 of 228. [First] Page: 1 6 7 8 9 10 Last
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