Computational methods for optimizing distributed systems /

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Computational methods for optimizing distributed systems.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Teo, K. L.
Otros Autores: Wu, Z. S.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Orlando : Academic Press, 1984.
Colección:Mathematics in science and engineering ; v. 173.
Temas:
Differential equations, Parabolic > Numerical solutions.
Boundary value problems > Numerical solutions.
Distributed parameter systems.
Équations différentielles paraboliques > Solutions numériques.
Problèmes aux limites > Solutions numériques.
Systèmes à paramètres répartis.
MATHEMATICS > Differential Equations > Partial.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 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

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