TY  - BOOK
AU  - Teo,K.L.
AU  - Wu,Z.S.
TI  - Computational methods for optimizing distributed systems
T2  - Mathematics in science and engineering
SN  - 9780126854800
AV  - QA402 .T46 1984eb
U1  - 515.3/53 22
PY  - 1984///
CY  - Orlando
PB  - Academic Press
KW  - Differential equations, Parabolic
KW  - Numerical solutions
KW  - Boundary value problems
KW  - Distributed parameter systems
KW  - Équations différentielles paraboliques
KW  - Solutions numériques
KW  - Problèmes aux limites
KW  - Systèmes à paramètres répartis
KW  - MATHEMATICS
KW  - Differential Equations
KW  - Partial
KW  - bisacsh
KW  - fast
KW  - Electronic books
N1  - Includes bibliographical references (pages 301-312) and index; Front Cover; Computational Methods for Optimizing Distributed Systems; Copyright Page; Contents; Preface; Chapter I. Mathematical Background; 1. Introduction; 2. Some Basic Concepts in Functional Analysis; 3. Some Basic Concepts in Measure Theory; 4. Some Function Spaces; 5. Relaxed Controls; 6. Multivalued Functions; 7. Bibliographical Remarks; Chapter II. Boundary Value Problems of Parabolic Type; 1. Introduction; 2. Boundary-Value Problems-Basic Definitions and Assumptions; 3. Three Elementary Lemmas; 4. A Priori Estimates; 5. Existence and Uniqueness of Solutions; 6. A Continuity Property; 7. Certain Properties of Solutions of Equation (2.1)8. Boundary-Value Problems in General Form; 9. A Maximum Principle; Chapter III. Optimal Control of First Boundary Problems: Strong Variation Techniques; 1. Introduction; 2. System Description; 3. The Optimal Control Problems; 4. The Hamiltonian Functions; 5. The Successive Controls; 6. The Algorithm; 7. Necessary and Sufficient Conditions for Optimality; 8. Numerical Consideration; 9. Examples; 10. Discussion; Chapter IV. Optimal Policy of First Boundary Problems: Gradient Techniques; 1. Introduction; 2. System Description; 3. The Optimization Problem4. An Increment Formula; 5. The Gradient of the Cost Functional; 6. A Conditional Gradient Algorithm; 7. Numerical Consideration and an Examples; 8. Optimal Control Problems with Terminal Inequality Constraints; 9. The Finite Element Method; 10. Discussion; Chapter V. Relaxed Controls and the Convergence of Optimal Control Algorithms; 1. Introduction; 2. The Strong Variational Algorithm; 3. The Conditional Gradient Algorithm; 4. The Feasible Directions Algorithm; 5. Discussion; Chapter VI. Optimal Control Problems Involving Second Boundary-Value Problems; 1. Introduction2. The General Problem Statement; 3. Preparatory Results; 4. A Basic Inequality; 5. An Optimal Control Problem with a Linear Cost Functional; 6. An Optimal Control Problem with a Linear System; 7. The Finite Element Method; 8. Discussion; Appendix I: Stochastic Optimal Control Problems; Appendix II: Certain Results on Partial Differential Equations Needed in Chapters III, IV, and V; Appendix III: An Algorithm of Quadratic Programming; Appendix IV: A Quasi-Newton Method for Nonlinear Function Minimization with Linear Constraints; Appendix V: An Algorithm for Optimal Control Problems of Linear Lumped Parameter SystemsAppendix VI: Meyer-Polak Proximity Algorithm; References; List of Notation; Index
N2  - Computational methods for optimizing distributed systems
UR  - https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=297160
ER  -