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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/7726
Title: Model Structure and Adjustable Parameter Selection for Operations Optimization
Authors: Forbes, Fraser J
Advisor: Marlin, T.E.
Department: Chemical Engineering
Keywords: Chemical Engineering;Chemical Engineering
Publication Date: Apr-1994
Abstract: <p>The value of model-based process optimization systems for competitive advantage in many industries, has been widely recognized. Such model-based optimization systems include Real-Time Optimization, On-Line Optimizing Control, off-line process scheduling, and any other economic process optimization scheme which uses a process model to predict optimal plant operation. The thesis investigates the design of these model-based optimization systems, particularly with respect to model structure and adjustable parameter selection.</p> <p>The main contribution of this work include design phase methods, based on fundamental principles of optimization and statistics theory, for determining whether a model-based optimization system can attain the plant optimum, as well as methods for discriminating between design alternatives. Three necessary conditions for zero-offset from the optimal plant operation are presented. These include Pont-Wise Model Adequacy, Augmented Model Adequacy and Point-Wise Stability. Recognizing that achieving zero-offset from the plant optimum may not always be possible, or may not be the only design objective, a Design Cost method is presented for selecting among design alternatives. This Design Cost method provides a natural "trade off" between offset elimination and variance of the predicted optimal manipulated variable values.</p> <p>Finally, the thesis is completed with a larger-scale case study involving the Williams-Otto Plant [1960]. In the case study selection of a process model and the adjustable parameter set for implementation in closed-loop Real-Time Optimization system is investigated.</p>
URI: http://hdl.handle.net/11375/7726
Identifier: opendissertations/2983
3996
1426911
Appears in Collections:Open Access Dissertations and Theses

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