Read e-book online Advanced Practical Process Control PDF

By Prof. Dr. ir. Brian Roffel, Dr. ir. Ben H. Betlem (auth.)

ISBN-10: 3540404805

ISBN-13: 9783540404804

ISBN-10: 3642182585

ISBN-13: 9783642182587

This textual content and reference bargains an application-oriented method of procedure keep an eye on. It systematically explains technique id, regulate and optimization, the 3 key steps had to remedy a multivariable regulate challenge. thought is mentioned so far as it truly is had to comprehend and resolve the outlined challenge, whereas a number of examples written in MATLAB illustrate the problem-solving process.

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In general , this type ofmodel consists of a set of (dynamic) conservation balances, such as mass balance, component balance, momentum balance and energy balance. These equations are supplemented with algebraic equat ions describing mass transfer, kinetics, etc. The effort required to build these types of models is high. Black box models or empirical models do not reflect the physical structure of the process, they are data based and reflect the input/output relationship of the process. 2 Type s of Models 47 when a physical understanding of the process is absent or incomplete.

88) . However it is not necessary to determine its value since it is cancelled at the summation point A, shown in Fig. 8. There are many ways in which the Smith Predictor block diagram can be equivalently represented. Another simpler representation is shown in Fig. 9. However, implementing the control strategy as shown in Fig. 8 allows the user to 'fine tune' the process model parameters on-line by comparing the predicted process output Yk against the actual process output value y. Once this comparison is favorable, the control engineer is assured of a good process model and thus good feedback control.

These models are often simple dynamic or static models with a large time horizon. • Operation Optimization. To optimize a process operation, a process model is required. Often these models can be derived by simplification from the design models . In this case, the degrees of freedom are the control variables or process conditions instead of the design variables. • Prediction and control. g. the molecular weight of a polymer. In addition, the control actions that are calculated in regulating a plant are often based on a model of the process.

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Advanced Practical Process Control by Prof. Dr. ir. Brian Roffel, Dr. ir. Ben H. Betlem (auth.)


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