The synthesis of plant-wide control structures has resurfaced as the most important design problem in processcontrol. In this paper we provide a comparative analysis of various approaches, with an emphasis on how wel...
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The synthesis of plant-wide control structures has resurfaced as the most important design problem in processcontrol. In this paper we provide a comparative analysis of various approaches, with an emphasis on how well they address the inherent theoretical and practical issues associated with the design of such controlsystems. Starting with a formal statement of the problem, which corresponds to a multi-objective optimization problem, this paper argues that the central issue to be resolved is the translation of implicit operating objectives to sets of feedback-controlled variables. The principle of the Optimizing Feedback control Structures is proposed as the formal medium for the identification of controlled variables. Furthermore, it is shown that the selection of the best sets of input (manipulated) and output (measured) variables for the formation of the controllers' structures is governed by classical control-theoretical aspects, such as;open-loop gains, model uncertainty, and nonminimum-phase process characteristics. Hierarchical viewing of a plant is proposed as an effective mechanism to contain the complexities of the problem by streamlining the (i) specification of control objectives at different time-scales, (ii) modeling needs and model uncertainties, (iii) selection of measured and manipulated variables, and (iv) formation of the control structures. (C) 2000 IFAC, Published by Elsevier Science Ltd. All rights reserved.
The inherent trade off between model accuracy and computational tractability for model-based control applications is addressed in this article by the development of reduced order nonlinear models. Traveling wave pheno...
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The inherent trade off between model accuracy and computational tractability for model-based control applications is addressed in this article by the development of reduced order nonlinear models. Traveling wave phenomena is used to develop low order models for multicomponent reactive distillation columns. A motivational example of batch esterification column is used to demonstrate the synthesis procedure. Tight control of the column is obtained with the use of reduced model in a model predictive control algorithm. (C) 2000 Published by Elsevier Science Ltd. All rights reserved.
This study proposes a novel dynamic approach for supply chain management based on the development of a dynamic framework to model supply chains, and on the application of ideas from processdynamics and control to man...
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This study proposes a novel dynamic approach for supply chain management based on the development of a dynamic framework to model supply chains, and on the application of ideas from processdynamics and control to manage it. This novel framework models the flow of information and material within the supply chain, and uses them to capture its dynamic behavior. Moreover, the use of ideas from dynamics and control allows the design of systematic decision-making processes for the supply chain as if they were control laws for a dynamic system. The study tests several heuristic control laws for the model and analyzes their impact on the behavior of the supply chain. The result is the reproduction of interesting trade offs found in real systems, which give valuable insights for the future direction of this research towards finding a near optimal decision-making process for a supply chain. (C) 2000 Elsevier Science Ltd. All rights reserved.
Detailed first-principles models of transport and reaction (based on partial differential equations) lead, after discretization, to dynamical systems of very high order. Systematic methodologies for model order reduct...
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Detailed first-principles models of transport and reaction (based on partial differential equations) lead, after discretization, to dynamical systems of very high order. Systematic methodologies for model order reduction are vital in exploiting such fundamental models in the analysis, design and real-time control of distributed reacting systems. We briefly review some approaches to model order reduction we have successfully used in recent years, and illustrate their capabilities through (a) the design of an observer and stabilizing controller of a reaction-diffusion problem and (b) two-dimensional simulations of the transient behavior of a horizontal MOVPE reactor. (C) 2000 IFAC. Published by Elsevier Science Ltd. All rights reserved.
The practicality of model predictive control (MPC) is partially limited by the ability to solve optimization problems in real time. This requirement limits the viability of MPC as a control strategy for large scale pr...
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The practicality of model predictive control (MPC) is partially limited by the ability to solve optimization problems in real time. This requirement limits the viability of MPC as a control strategy for large scale processes. One strategy for improving the computational performance is to formulate MPC using a linear program. While the linear programming formulation seems appealing from a numerical standpoint, the controller does not necessarily yield good closed-loop performance. In this work, we explore MPC with an II performance criterion. We demonstrate how the non-smoothness of the objective function may yield either dead-beat or idle control performance. (C) 2000 IFAC. Published by Elsevier Science Ltd. All rights reserved.
In order to control product compositions in a multicomponent distillation column, the distillate and bottom compositions are estimated from on-line measured process variables. In this paper, inferential models for est...
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In order to control product compositions in a multicomponent distillation column, the distillate and bottom compositions are estimated from on-line measured process variables. In this paper, inferential models for estimating product compositions are constructed using dynamic Partial Least Squares (PLS) regression, on the basis of simulated time series data. II is found that the use of past measurements is effective for improving the accuracy of the estimation. The influence of selection of measurements and sampling intervals on the performance is also investigated. From the detailed dynamic simulation results, it is found that the cascade control system based on the proposed dynamic PLS model works much better than the usual tray temperature control system. (C) 2000 IFAC. Published by Elsevier Science Ltd. All rights reserved.
The operating conditions for a heat-integrated ethylene quench column are optimized and diagnosed for controllability and resiliency. Since a bank of seawater coolers largely meets the column's cooling duty requir...
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The operating conditions for a heat-integrated ethylene quench column are optimized and diagnosed for controllability and resiliency. Since a bank of seawater coolers largely meets the column's cooling duty requirements, the heat-exchanger by-pass flow fractions were optimized as a function of seawater temperature, using a specially adapted genetic algorithm. The controllability and resiliency of the quench column are studied and two alternative MIMO control configurations are investigated. Of particular interest was the impact of the nominal operating position of the bypass on disturbance rejection capacity. It was found that the resiliency of the column could be significantly enhanced by repositioning the nominal operating point of the main bypass valve and at the same time, the overall heat recovery in the seawater coolers could be enhanced, leading to significant savings in operating costs. (C) 2000 IFAC. Published by Elsevier Science Ltd. All rights reserved.
The pilot plant under study is designed for determining the kinetics of the heterogeneous non-catalytic reaction of chemical pulping of wood and for teaching system dynamics and batch processcontrol in an appropriate...
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The pilot plant under study is designed for determining the kinetics of the heterogeneous non-catalytic reaction of chemical pulping of wood and for teaching system dynamics and batch processcontrol in an appropriate university course. The natural complexity of the system includes time varying dynamics and stepwise behavior and this makes it attractive for highlighting some important features of the real world of processcontrol. Due to its specific design, the pilot plant is also very useful for kinetic studies of heterogeneous reactions involving wood, ensuring a high level of the repeatability of results. The pilot plant and its control system have been used in teaching of chemical kinetics of heterogeneous reactions and are also part of the experimental program in a processcontrol course. (C) 2000 Elsevier Science Ltd. All rights reserved.
Computational fluid dynamics (CFD) and process simulation are widely used in the process industry. The two technologies are largely complementary, each being able to capture and analyse some of the important process c...
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Computational fluid dynamics (CFD) and process simulation are widely used in the process industry. The two technologies are largely complementary, each being able to capture and analyse some of the important process characteristics. Their combined application can, therefore, lead to significant industrial benefits. This is especially true for systems, such as chemical reactors, in which steady-state performance, dynamics and control strategy depend on mixing and fluid flow behaviour. This paper presents a new approach for the integration of the capabilities of CFD technology and process simulation via a general interface that allows the automatic exchange of critical variables between the two packages, leading to a simultaneous solution of the overall problem. The approach applies to both steady-state and dynamic problems. The feasibility of the approach and its first practical implementation are demonstrated by integrating a widely used CFD package (Fluent 4.5, by Fluent Inc.) within a general-purpose advanced process simulator (gPROMS 1.7, by processsystems Enterprise Ltd. (1999)). One case study involving a batch reactor is used to illustrate the ability of the combined tool to provide information on the detailed interactions between fluid mechanics, heat transfer, reaction and control strategy, and to provide insights on important design and operational decisions. (C) 2000 Elsevier Science Ltd. All rights reserved.
The control structure selection for an air separation plant is discussed using the robust performance number (RPN) as a controllability index. The RPN indicates how potentially difficult it is for a given system to ac...
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The control structure selection for an air separation plant is discussed using the robust performance number (RPN) as a controllability index. The RPN indicates how potentially difficult it is for a given system to achieve the desired performance robustly. It reflects both the attainable performance of a system and its degree of directionality. The RPN criterion is compared with other well-known and new methodologies. These other criteria do not take the dynamic characteristics of the plant into account, hence they can be misleading. The predictions made by RPN are verified by closed loop simulations. The analysis was performed using a linear nominal model, but can be extended to include nonlinearities and uncertainties. (C) 2000 IFAC. Published by Elsevier Science Ltd. All rights reserved.
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