I had read/studied most of this book when I was a graduate student in chemical engineering at Syracuse University (in 1987-88). I also took two courses on the subject from Professor Troutman. I strongly recommend this book to any "newcomer" to the subject. The author is a mathematician, and a larg
Variational Calculus and Optimal Control: Optimization with Elementary Convexity (Undergraduate Texts in Mathematics)
β Scribed by John L. Troutman
- Publisher
- Springer
- Year
- 1995
- Tongue
- English
- Leaves
- 479
- Edition
- 2
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Although the calculus of variations has ancient origins in questions of ArΒ istotle and Zenodoros, its mathematical principles first emerged in the postΒ calculus investigations of Newton, the Bernoullis, Euler, and Lagrange. Its results now supply fundamental tools of exploration to both mathematicians and those in the applied sciences. (Indeed, the macroscopic statements obΒ tained through variational principles may provide the only valid mathematiΒ cal formulations of many physical laws. ) Because of its classical origins, variational calculus retains the spirit of natural philosophy common to most mathematical investigations prior to this century. The original applications, including the Bernoulli problem of finding the brachistochrone, require optiΒ mizing (maximizing or minimizing) the mass, force, time, or energy of some physical system under various constraints. The solutions to these problems satisfy related differential equations discovered by Euler and Lagrange, and the variational principles of mechanics (especially that of Hamilton from the last century) show the importance of also considering solutions that just provide stationary behavior for some measure of performance of the system. However, many recent applications do involve optimization, in particular, those concerned with problems in optimal control. Optimal control is the rapidly expanding field developed during the last half-century to analyze optimal behavior of a constrained process that evolves in time according to prescribed laws. Its applications now embrace a variety of new disciplines, including economics and production planning.
β¦ Table of Contents
Cover
Series: Undergraduate Texts in Mathematics
Variational Calculus and Optimal Control: Optimization with Elementary Convexity, Second edition
Copyright - ISBN: 0387945113
Preface
Acknowledgments
Contents
CHAPTER 0. Review of Optimization in IR^d
Problems
PART ONE. BASIC THEORY
CHAPTER 1. Standard Optimization Problems
1.1. Geodesic Problems
(a) Geodesies in IR^d
(b) Geodesies on a Sphere
(c) Other Geodesic Problems
1.2. Time-of-Transit Problems
(a) The Brachistochrone
(b) Steering and Control Problems
1.3. Isoperimetric Problems
1.4. Surface Area Problems
(a) Minimal Surface of Revolution
(b) Minimal Area Problem
(c) Plateau's Problem
1.5. Summary: Plan of the Text
Notation: Uses and Abuses
Problems
CHAPTER 2. Linear Spaces and Gateaux Variations
2.1. Real Linear Spaces
2.2. Functions from Linear Spaces
2.3. Fundamentals of Optimization
Constraints
Application: Rotating Fluid Column
2.4. The GΓ’teaux Variations
Problems
CHAPTER 3. Minimization of Convex Functions
3.1. Convex Functions
3.2. Convex Integral Functions
Free End-Point Problems
3.3. [Strongly] Convex Functions
3.4. Applications
(a) Geodesies on a Cylinder
(b) A Brachistochrone
(c) A Profile of Minimum Drag
(d) An Economics Problem
(e) Minimal Area Problem
3.5. Minimization with Convex Constraints
The Hanging Cable
Optimal Performance
3.6. Summary: Minimizing Procedures
Problems
CHAPTER 4. The Lemmas of Lagrange and Du Bois-Reymond
Problems
CHAPTER 5. Local Extrema in Normed Linear Spaces
5.1. Norms for Linear Spaces
5.2. Normed Linear Spaces: Convergence and Compactness
5.3. Continuity
5.4. (Local) Extremal Points
5.5. Necessary Conditions: Admissible Directions
5.6. Affine Approximation: The Frechet Derivative
Tangency
5.7. Extrema with Constraints: Lagrangian Multipliers
Problems
CHAPTER 6. The Euler-Lagrange Equations
6.1. The First Equation: Stationary Functions
6.2. Special Cases of the First Equation
(a) When f = f(z)
(b) When f = f(x, z)
(c) When f = f(y, z)
6.3. The Second Equation
6.4. Variable End Point Problems: Natural Boundary Conditions
Application: Jakob Bernoulli's Brachistochrone
Transversal Conditions
6.5. Integral Constraints: Lagrangian Multipliers
6.6. Integrals Involving Higher Derivatives
Buckling of a Column under Compressive Load
6.7. Vector Valued Stationary Functions
Application 1: The Isoperimetric Problem
Lagrangian Constraints
Application 2: Geodesies on a Surface
6.8. Invariance of Stationarity
6.9. Multidimensional Integrals
Application: Minimal Area Problem
Natural Boundary Conditions
Problems
PART TWO. ADVANCED TOPICS
CHAPTER 7. Piecewise C^1 Extremal Functions
7.1. Piecewise C^1 Functions
(a) Smoothing
(b) Norms for hat{C}^1
7.2. Integral Functions on hat{C}^1
7.3. Extremals in hat{C}^1[a, b]:The Weierstrass-Erdmann Corner Conditions
Application: A Sturm-Liouville Problem
7.4. Minimization Through Convexity
Internal Constraints
7.5. Piecewise C^1 Vector-Valued Extremals
Application: Minimal Surface of Revolution
Hilbert's Differentiability Criterion
7.6. Conditions Necessary for a Local Minimum
(a) The Weierstrass Condition
(b) The Legendre Condition
Bolza's Problem
Problems
CHAPTER 8. Variational Principles in Mechanics
8.1. The Action Integral
8.2. Hamilton's Principle: Generalized Coordinates
Bernoulli's Principle of Static Equilibrium
8.3. The Total Energy
Application: Spring-Mass-Pendulum System
8.4. The Canonical Equations
8.5. Integrals of Motion in Special Cases
Jacobi's Principle of Least Action
Symmetry and Invariance
8.6. Parametric Equations of Motion
8.7 The Hamilton-Jacobi Equation
8.8. Saddle Functions and Convexity; Complementary Inequalities
Example 1. The Cycloid Is the Brachistochrone
Example 2 .Dido's Problem
8.9. Continuous Media
(a) Taut String
The Nonuniform String
(b) Stretched Membrane
Static Equilibrium of (Nonplanar) Membrane
Problems
CHAPTER 9. Sufficient Conditions for a Minimum
9.1. The Weierstrass Method
9.2. [Strict] Convexity of f(underline{x}, underline{Y}, Z)
9.3. Fields
Exact Fields and the Hamilton-Jacobi Equation
9.4. Hilbert's Invariant Integral
Application: The Brachistochrone
Variable End-Point Problems
9.5. Minimization with Constraints
The Wirtinger Inequality
9.6. Central Fields
Smooth Minimal Surface of Revolution
9.7. Construction of Central Fields with Given Trajectory: The Jacobi Condition
9.8. Sufficient Conditions for a Local Minimum
(a) Pointwise Results
Application: Hamilton's Principle
(b) Trajectory Results
9.9. Necessity of the Jacobi Condition
9.10. Concluding Remarks
Problems
PART THREE. OPTIMAL CONTROL
CHAPTER 10. Control Problems and Sufficiency Considerations
10.1. Mathematical Formulation and Terminology
10.2. Sample Problems
(a) Some Easy Problems
(b) A Bolza Problem
(c) Optimal Time of Transit
(d) A Rocket Propulsion Problem
(e) A Resource Allocation Problem
(f) Excitation of an Oscillator
(g) Time-Optimal Solution by Steepest Descent
10.3. Sufficient Conditions Through Convexity
Linear State-Quadratic Performance Problem
10.4. Separate Convexity and the Minimum Principle
Problems
CHAPTER 11. Necessary Conditions for Optimality
11.1. Necessity of the Minimum Principle
(a) Effects of Control Variations
(b) Autonomous Fixed Interval Problems
(c) General Control Problems
11.2. Linear Time-Optimal Problems
Problem Statement
A Free Space Docking Problem
11.3. General Lagrangian Constraints
(a) Control Sets Described by Lagrangian Inequalities
(b) Variational Problems with Lagrangian Constraints
(c) Extensions
Problems
Appendix
A.0. Compact Sets in IR^d
A.1. The Intermediate and Mean Value Theorems
A.2. The Fundamental Theorem of Calculus
A.3. Partial Integrals: Leibniz' Formula
A.4. An Open Mapping Theorem
A.5. Families of Solutions to a System of Differential Equations
A.6. The Rayleigh Ratio
A.7*. Linear Functional and Tangent Cones in IR^d
Bibliography
Historical References
Answers to Selected Problems
Index
π SIMILAR VOLUMES
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