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Optimization strategy

Since the control calculations are based on optimizing control system performance, MFC can be readily integrated with on-line optimization strategies to optimize plant performance. [Pg.739]

In practice, most attention is given to accuracy when the measured variable is the basis for billing, such as in custody transfer applications. However, whenever a measurement device provides data to any type of optimization strategy, accuracy is veiy impoi tant. [Pg.758]

Self-Organizing Fuzzy Logic Control (SOFLC) is an optimization strategy to create and modify the control rulebase for a FLC as a result of observed system performance. The SOFLC is particularly useful when the plant is subject to time-varying parameter changes and unknown disturbances. [Pg.344]

N. Eundell and K. Mar kides, Two-dimensional liquid cliromatography of peptides an optimization strategy , Chromatographia 34 369-375 (1992). [Pg.291]

Proll T, Kusters E. (1998) Optimization Strategy for Simulated Moving Bed Systems, J. Chromatogr. A 800 135-150. [Pg.251]

For this model the frequency function of the bomber s optimal strategy, as obtained through game theoretic analysis, is... [Pg.314]

Hellinger FJ (2006) Economic models of antiretroviral therapy searching for the optimal strategy, Pharmacoeconomics 24 631-642... [Pg.372]

Based on the model described in the previous section, an optimization strategy has been developed for substrate feeding with maximum PAC production as its objective fimction. A molar ratio of pyruvate benzaldehyde of 1.2 1 was maintained in the feed as some of the pyruvate is converted also to by-products acetaldehyde and acetoin. [Pg.26]

Biegler, L., Optimization strategies for complex process models. Adv. Chem. Eng. 18, 197 (1992). [Pg.154]

Lorenz T. Biegler, Optimization Strategies for Complex Process Models... [Pg.345]

It is the main aim of semiempirical chromatographic models to couple the empirical parameters of retention with the established thermodynamic quantities generally used in physical chemistry. The validity of a model for chromatographic practice can hardly be overestimated, because it often and successfully helps to overcome the old trial-and-error approach to running the analyses, especially when incorporated in the separation selectivity oriented optimization strategy. [Pg.17]

The variables that control the extent of a chromatographic separation are conveniently divided into kinetic and thermodynamic factors. The thermodynamic variables control relative retention and are embodied in the selectivity factor in the resolution equation. For any optimization strategy the selectivity factor should be maximized (see section 1.6). Since this depends on an understandino of the appropriate retention mechanism further discussion. .Jll be deferred to the appropriate sections of Chapters 2 and 4. [Pg.23]

Any optimization strategy that considered only efficiency is inadequate to describe accurately resolution, which is a strong function of the capacity factor at low capacity factor values. The... [Pg.542]

The first step in developing an optimization strategy is to define the parameter space to be searched for an acceptable... [Pg.752]

A broad class of optimization strategies does not require derivative information. These methods have the advantage of easy implementation and little prior knowledge of the optimization problem. In particular, such methods are well suited for quick and dirty optimization studies that explore the scope of optimization for new problems, prior to investing effort for more sophisticated modeling and solution strategies. Most of these methods are derived from heuristics that naturally spawn numerous variations. As a result, a very broad literature describes these methods. Here we discuss only a few important trends in this area. [Pg.65]

For optimization problems that are derived from (ordinary or partial) differential equation models, a number of advanced optimization strategies can be applied. Most of these problems are posed as NLPs, although recent work has also extended these models to MINLPs and global optimization formulations. For the optimization of profiles in time and space, indirect methods can be applied based on the optimality conditions of the infinite-dimensional problem using, for instance, the calculus of variations. However, these methods become difficult to apply if inequality constraints and discrete decisions are part of the optimization problem. Instead, current methods are based on NLP and MINLP formulations and can be divided into two classes ... [Pg.70]

As mentioned earlier, biological systems have developed optimized strategies to design materials with elaborate nanostructures [6]. A straightforward approach to obtaining nanoparticles with controlled size and organization should therefore rely on so-called biomimetic syntheses where one aims to reproduce in vitro the natural processes of biomineralization. In this context, a first possibility is to extract and analyze the biological (macro)-molecules that are involved in these processes and to use them as templates for the formation of the same materials. Such an approach has been widely developed for calcium carbonate biomimetic synthesis [13]. In the case of oxide nanomaterials, the most studied system so far is the silica shell formed by diatoms [14]. [Pg.160]

Optimization strategies and a number of generalized limitations to the design of gas-phase chemiluminescence detectors have been described based on exact solutions of the governing equations for both exponential dilution and plug-flow models of the reaction chamber by Mehrabzadeh et al. [12, 13]. However, application of this approach requires a knowledge of the reaction mechanism and rate coefficients for the rate-determining steps of the chemiluminescent reaction considered. [Pg.354]

Figure 2.1. Processing stages in chemical solution deposition of thin films. Controllable parameters are shown on the left dependent processes are shown in italics. [Reprinted from Ref. 16 with the permission of the publisher, Taylor Francis, Ltd. R. W. Schwartz et al., Sol-gel processing of PZT thin films a review of the state-of-the-art and process optimization strategies, Int. Ferro., 7,259, (1995).]... Figure 2.1. Processing stages in chemical solution deposition of thin films. Controllable parameters are shown on the left dependent processes are shown in italics. [Reprinted from Ref. 16 with the permission of the publisher, Taylor Francis, Ltd. R. W. Schwartz et al., Sol-gel processing of PZT thin films a review of the state-of-the-art and process optimization strategies, Int. Ferro., 7,259, (1995).]...

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