Author
James J. Downs
Bio: James J. Downs is an academic researcher from Eastman Chemical Company. The author has contributed to research in topics: Fractionating column & Distillation. The author has an hindex of 6, co-authored 11 publications receiving 2394 citations.
Papers
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TL;DR: In this article, a model of an industrial chemical process for the purpose of developing, studying and evaluating process control technology is presented, which is well suited for a wide variety of studies including both plantwide control and multivariable control problems.
2,603 citations
TL;DR: In this article, the authors stress the importance of selecting the right plantwide control structure and the need for a formalized approach that can encompass the many issues that arise in plant-wide control design.
67 citations
TL;DR: The roles of simulation and laboratory experiments are highlighted, and alternative ways of teaching control in the future are described, including problem-based learning, case studies, and use of multimedia classrooms.
40 citations
TL;DR: In this paper, the authors focus on DWCs as a ternary separation technology for hydrocarbon mixtures relevant to the chemical and refining industries and conclude that, although achieving stable DWC operation is certainly possible, the development of a comprehensive framework that incorporates (multiple and often conflicting) process operating objectives, and equipment and process constraints, into a transparent control strategy remains an open research question.
Abstract: Dividing wall columns (DWC) are an energy-efficient distillation setup that promises capital cost and energy savings. This review focuses on DWCs as a ternary separation technology for hydrocarbon mixtures relevant to the chemical and refining industries. One of the reasons industry adoption of DWCs tends to be slow is the unique control challenge resulting from DWCs’ highly integrated nature. This review summarizes available literature on DWC control approaches, from multi-loop linear structures to advanced model-based control. We conclude that, although achieving stable DWC operation is certainly possible, the development of a comprehensive framework that incorporates (multiple and often conflicting) process operating objectives, and equipment and process constraints, into a transparent control strategy remains an open research question.
35 citations
01 Jan 1992
TL;DR: The role of distillation columns as a unit operation that separates components usually makes the operation of the distillation column central to the control of component inventories within a process as discussed by the authors.
Abstract: The development of distillation column control strategies involves not only the understanding of how to control columns as isolated unit operations but also the understanding of how its operation influences and is influenced by the other unit operations that comprise a chemical process. The role of distillation as a unit operation that separates components usually makes the operation of the distillation column central to the control of component inventories within a process. This can be contrasted with unit operations that do not change stream compositions such as heat exchangers and heat exchanger networks.
25 citations
Cited by
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TL;DR: This paper uses a well-known ‘time lag shift’ method to include dynamic behavior in the PCA model and demonstrates the effectiveness of the proposed methodology on the Tennessee Eastman process simulation.
1,299 citations
TL;DR: A comparison study on the basic data-driven methods for process monitoring and fault diagnosis (PM–FD) based on the original ideas, implementation conditions, off-line design and on-line computation algorithms as well as computation complexity are discussed in detail.
1,116 citations
30 Apr 2009
TL;DR: This work presents a semi-definite programming based solution for solving the problem of security constrained optimal control for discrete-time, linear dynamical systems in which control and measurement packets are transmitted over a communication network.
Abstract: We consider the problem of security constrained optimal control for discrete-time, linear dynamical systems in which control and measurement packets are transmitted over a communication network. The packets may be jammed or compromised by a malicious adversary. For a class of denial-of-service (DoS) attack models, the goal is to find an (optimal) causal feedback controller that minimizes a given objective function subject to safety and power constraints. We present a semi-definite programming based solution for solving this problem. Our analysis also presents insights on the effect of attack models on solution of the optimal control problem.
676 citations
TL;DR: In this paper, a nonlinear principal component analysis (NLPCA) method which integrates the principal curve algorithm and neural networks is presented. But when applied to data sets the algorithm does not yield an NLPCA model in the sense of principal loadings.
635 citations