Optimization of batch reactor operation under parametric uncertainty — computational aspects
✍ Scribed by D. Ruppen; C. Benthack; D. Bonvin
- Publisher
- Elsevier Science
- Year
- 1995
- Tongue
- English
- Weight
- 561 KB
- Volume
- 5
- Category
- Article
- ISSN
- 0959-1524
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✦ Synopsis
The paper describes a method for optimizing batch reactors when the models at hand are characterized by parametric uncertainty. A discrete (or discretized) probability distribution of the uncertain parameters is assumed. This leads to a differential/algebraic optimization problem (DAOP) including several model descriptions, each corresponding to a grid point in parameter space. The DAOP is then transformed to an algebraic optimization problem (AOP) using a time parameterization based on the method of orthogonal collocation. This allows the user to (i) easily include additional algebraic path or endpoint constraints, and (ii) use a computationally-attractive simultaneous solution and optimization approach. Successive linear programming is used for solving the large and sparse AOP. The proposed solution strategy is illustrated on two optimization studies of a simulated batch reactor.