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Dynamic programming in chemical engineering and process control

Author: Sanford M Roberts
Publisher: New York : Academic Press, 1964.
Series: Mathematics in science and engineering, v. 12.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Roberts, Sanford M.
Dynamic programming in chemical engineering and process control.
New York, Academic Press, 1964
(DLC) 63016974
(OCoLC)1690835
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Sanford M Roberts
ISBN: 9780080955193 0080955193
OCLC Number: 688476058
Reproduction Notes: Electronic reproduction. [S.l.] : HathiTrust Digital Library, 2010. MiAaHDL
Description: 1 online resource (xiii, 457 pages) : illustrations.
Details: Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.
Contents: Front Cover; Dynamic Programming in Chemical Engineering and Process Control; Copyright Page; Contents; Preface; Chapter 1. Introduction; 1. Introduction; 2. Definition of Dynamic Programming; 3. Examples of Multi-Stage Processes; 4. Definitions; 5. Method of Attack; 6. Advantages of Dynamic Programming; 7. Disadvantage of Dynamic Programming; Reference; Chapter 2. Replacement Problems; 1. Introduction; 2. Equipment Replacement; 3. Numerical Example; 4. Infinitely Long Process Equipment Replacement; 5. Catalyst Replacement Problems; 6. Model I-Simplest Case; 7. Model II-N-Stage Process. 8. Computational Aspects for Model II9. Numerical Example, Model II; References; Problems; Chapter 3. Allocation Problems; 1. Introduction; 2. Parallel Reactors, Catalyst Activity Constant; 3. Parallel Reactors with Feed Forward; 4. Series Reactor System; 5. Single Reactor, Catalyst Activity Variable; 6. Alternate Formulation; 7. Feed Rate Distribution over Multiple Reactors and over Time, Variable Catalyst Activity; 8. Cross-Current Extraction; 9. Alternate Formulation of Cross-Current Extraction; 10. Multi-Unit Chemical Plant; 11. Minimization of Liquid Pipeline Pumping Costs. 12. Generalization of Minimization of Liquid Pipeline Pumping Costs13. Efficiency of Units in Tandem; References; Problems; Chapter 4. Dynamic Programming and the Calculus of Variations; 1. Introduction; 2. Calculus of Variations Problems; 3. Ordinary Maxima and Minima and the Calculus of Variations; 4. Difficulties in the Calculus of Variations; 5. Equality Constraints; 6. Inequality Constraints; 7. Devices for Handling Inequality Constraints; 8. Two-Point Boundary Value Problems; 9. Linearity; 10. Nonanalytic Functions; 11. Example: Inequality Constrained Problem. 12. Dynamic Programming Point of View13. Derivation of Dynamic Programming Equations; 14. Max?T0 F(x, y) dt; 15. Max?80 F(x, y) dt; 16. Max?80 F(x, y, t) dt; 17. Classical Method for Max?80 F(x, y) dt; 18. Euler-Lagrange Equation Derivation by Dynamic Programming; 19. Numerical Evaluation of FT = Max [F(c, v) + G(c, v) fc]; 20. Alternate Approach. Finite Analog to Max?8T F(x, y) dt; 21. Finite Analog to Min?T0 F(y, y', t) dt; 22. Control of Chemical Reactor; 23. Example: Smoothing Problems as Variational Problems; 24. Example: Brachistochrone; 25. Batch Reaction Control, Time Minimization. 26. Comparison of Methods of Solution of the Brachistochrone Problem27. Dynamic Programming and Calculus of Variations-Summing Up; References; Problems; Chapter 5. Computational Aspects of Dynamic Programming; 1. Introduction; 2. Computational Aspects. Raison d'Etre; Untitled; 3. Numerical Example. Combinatorial Method versus Dynamic Programming; 4. General Computation Process; 5. Expanding Grid Problem; 6. Two-Dimensional Problems; 7. Multi-Dimensional Problems; 8. Step-by-Step Grid Generation; 9. Example of Step-by-Step Grid Generation. Control of Batch Reaction.
Series Title: Mathematics in science and engineering, v. 12.
Responsibility: Sanford M. Roberts.

Abstract:

In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation;methods for low-rank.

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