<p>This work presents recent mathematical methods in the area of optimal control with a particular emphasis on the computational aspects and applications. Optimal control theory concerns the determination of control strategies for complex dynamical systems, in order to optimize some measure of their
Numerical methods for optimal control problems
β Scribed by Falcone M (ed.)
- Publisher
- Springer
- Year
- 2018
- Tongue
- English
- Leaves
- 275
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Table of Contents
Preface......Page 6
Contents......Page 8
About the Editors......Page 10
1 Introduction......Page 12
2.1 Problem Formulation......Page 15
2.2 Regularized Problem......Page 17
3 Dynamic Programming and Hamilton-Jacobi-Bellman Equation......Page 19
3.1 HJB Equation......Page 21
4 Numerical Approximation......Page 23
5.1 Example 1......Page 27
5.2 Example 2......Page 30
6 Conclusions......Page 31
References......Page 32
1 Introduction......Page 34
2 Problem Formulation and Solution Approach......Page 35
3 Upper Level: Route Planning......Page 37
4 Lower Level: Minimum Time Driving......Page 39
5 Levels Coupling......Page 42
6 Numerical Results......Page 43
6.1 General Evaluation of the Bi-level Algorithm......Page 44
6.2 Influence of the Parameters ΞΈ and Ξ»......Page 46
7 Conclusions......Page 47
References......Page 48
1 Introduction......Page 50
2 Optimal Control Problems with Time Delays and Optimality Conditions......Page 51
3 Discretization......Page 56
4 Convergence......Page 58
5 Numerical Simulations......Page 61
References......Page 73
1 Introduction......Page 74
2.1 The State Equation......Page 75
2.2 The State-Constrained Optimization Problem......Page 78
2.3 First-Order Optimality Conditions......Page 80
3 The Primal-Dual Active Set Strategy (PDASS)......Page 82
4 Proper Orthogonal Decomposition......Page 85
5 A-Posteriori Error Analysis......Page 86
6 Numerical Tests......Page 88
6.1 Test 1: Economic Optimal Control......Page 89
6.2 Test 2: Cost of Tracking Type......Page 92
7 Conclusions......Page 94
References......Page 96
Order Reduction Approaches for the Algebraic Riccati Equation and the LQR Problem......Page 99
1 Introduction......Page 100
2 The Linear-Quadratic Regulator Problem and Model Order Reduction......Page 102
3.1 Proper Orthogonal Decomposition......Page 104
3.2 Balanced Truncation......Page 105
4 Adaptive Reduction of the Algebraic Riccati Equation......Page 106
4.1 Galerkin and Petrov-Galerkin Riccati......Page 107
5 Numerical Experiments......Page 110
5.1 Test 1: 2D Linear Heat Equation......Page 111
5.2 Test 2: 2D Linear Convection-Diffusion Equation......Page 113
5.3 Test 3: A Discussion on Large Scale Balanced Truncation......Page 115
References......Page 117
1 Introduction......Page 120
2 Existence of Solution with Box and Sparse Constraints......Page 122
3.1 Finite Differences Discretization......Page 124
3.2.1 Box-Constrained Optimization Problems......Page 125
3.3 Fast and Reliable Solution of Sequences of FDEs......Page 127
3.3.1 Preconditioners for the Sequence of Jacobian in Semismooth Newton Method......Page 130
4 Numerical Examples......Page 135
4.1 Box-Constrained Problem......Page 136
4.2 Sparse Constrained Problem......Page 138
References......Page 143
Control, Shape, and Topological Derivatives via Minimax Differentiability of Lagrangians......Page 145
1 Introduction......Page 146
2 Examples of Derivatives with Respect to a Control, Shape, or Topological Variable......Page 147
2.2 Shape Derivative via the Velocity Method as a Differential......Page 148
2.3 Topological Derivative via Dilatations as a Semidifferential......Page 149
2.3.1 Tangent Space to the Group of Characteristic Functions......Page 150
2.3.2 The d-Dimensional Minkowski Content and d-Rectifiable Sets......Page 152
2.3.3 Back to the Example......Page 154
3.1 Abstract Framework......Page 155
3.2 Original Condition of Sturm and Its First Extension......Page 157
3.3 A New Condition with the Standard Adjoint at t=0......Page 159
3.4.1 Directional Derivative with Respect to the Control......Page 160
3.4.2 Shape Derivative......Page 162
3.4.3 Topological Derivative......Page 165
4 Minimax Theorems in the Mutivalued Case......Page 168
References......Page 172
1 Introduction......Page 173
2 Minimum Energy Estimation in Discrete Time......Page 175
3 Taylor Polynomial Approach......Page 178
4 The Relation Between the MEE and the EKF......Page 182
5 Example: Lorenz Attractor......Page 185
6 Conclusion......Page 188
References......Page 190
Probabilistic Max-Plus Schemes for Solving Hamilton-Jacobi-Bellman Equations......Page 191
1 Introduction......Page 192
2 The Probabilistic Time Discretization of Fahim, Touzi and Warin......Page 195
3 Monotone Probabilistic Approximation of First and Second Order Derivatives and Their Estimates......Page 196
4 Monotone Probabilistic Schemes for HJB Equations......Page 201
5 The Probabilistic Max-Plus Method......Page 209
References......Page 217
1 Introduction......Page 218
2 Optimal Control Problem......Page 220
3 Max-Plus Fundamental Solution Semigroups......Page 221
4 Adaptive Max-Plus Eigenvector Method......Page 229
5 Examples......Page 237
Appendix......Page 242
References......Page 246
1 Introduction......Page 248
2 Dequantization......Page 250
3.1 Stationarity Definitions......Page 251
3.2 The Non-inertial Frame......Page 252
3.3 Extensions to the Complex Domain......Page 253
4 An Expansion......Page 255
4.1 An Alternate Assumption......Page 258
5 Periodic S 0 Solutions......Page 260
6.1 The Underlying Stochastic Dynamics......Page 264
6.2 ItΓ΄'s Rule......Page 266
6.3 Moments and Iteration......Page 269
7 The 1 Term......Page 272
References......Page 274
π SIMILAR VOLUMES
Dissertation Script
<p>While optimality conditions for optimal control problems with state constraints have been extensively investigated in the literature the results pertaining to numerical methods are relatively scarce. This book fills the gap by providing a family of new methods. Among others, a novel convergence a
<p>While optimality conditions for optimal control problems with state constraints have been extensively investigated in the literature the results pertaining to numerical methods are relatively scarce. This book fills the gap by providing a family of new methods. Among others, a novel convergence a
The book presents a comprehensive development of effective numerical methods for stochastic control problems in continuous time. The process models are diffusions, jump-diffusions or reflected diffusions of the type that occur in the majority of current applications. All the usual problem formulatio