Cover image for Max-plus methods for nonlinear control and estimation
Title:
Max-plus methods for nonlinear control and estimation
Personal Author:
Series:
Systems and control : foundation and applications
Publication Information:
Boston, MA : Birkh�auser, 2006
ISBN:
9780817635343

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30000010129649 QA402.35 M32 2006 Open Access Book Book
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Summary

Summary

The control and estimation of continuous-time/continuous-space nonlinear systems continues to be a challenging problem, and this is one of the c- tral foci of this book. A common approach is to use dynamic programming; this typically leads to solution of the control or estimation problem via the solution of a corresponding Hamilton-Jacobi (HJ) partial di?erential eq- tion (PDE). This approach has the advantage of producing the "optimal" control. (The term "optimal" has a somewhat more complex meaning in the class of H problems. However, we will freely use the term for such controllers ? throughout, and this meaning will be made more precise when it is not ob- ous. )Thus,insolvingthecontrol/estimationproblem,wewillbesolvingsome nonlinear HJ PDEs. One might note that a second focus of the book is the solution of a class of HJ PDEs whose viscosity solutions have interpretations as value functions of associated control problems. Note that we will brie?y discuss the notion of viscosity solution of a nonlinear HJ PDE, and indicate that this solution has the property that it is the correct weak solution of the PDE. By correct weak solution in this context, we mean that it is the solution that is the value function of the associated control (or estimation) problem. The viscosity solution is also the correct weak solution in many PDE classes not considered here, and references to further literature on this subject will be given.


Table of Contents

Prefacep. vii
1 Introductionp. 1
1.1 Some Control and Estimation Problemsp. 3
1.2 Concepts of Max-Plus Methodsp. 6
2 Max-Plus Analysisp. 11
2.1 Spaces of Semiconvex Functionsp. 13
2.2 Basesp. 15
2.3 Two-Parameter Familiesp. 21
2.4 Dual Spaces and Reflexivityp. 22
3 Dynamic Programming and Viscosity Solutionsp. 31
3.1 Dynamic Programming Principlep. 32
3.2 Viscosity Solutionsp. 42
4 Max-Plus Eigenvector Method for the Infinite Time-Horizon Problemp. 57
4.1 Existence and Uniquenessp. 58
4.2 Max-Plus Linearity of the Semigroupp. 60
4.3 Semiconvexity and a Max-Plus Basisp. 66
4.4 The Eigenvector Equationp. 70
4.5 The Power Methodp. 72
4.6 Computing B: Initial Notesp. 83
4.7 Outline of Algorithmp. 84
4.8 A Control Problem Without Nominal Stability and a Gamep. 84
4.8.1 A Game Problemp. 93
4.9 An Examplep. 95
5 Max-Plus Eigenvector Method Error Analysisp. 97
5.1 Allowable Errors in Computation of Bp. 98
5.2 Convergence and Truncation Errorsp. 107
5.2.1 Convergencep. 108
5.2.2 Truncation Error Estimatep. 110
5.3 Errors in the Approximation of Bp. 119
5.3.1 A Method for Computing Bp. 122
5.4 Error Summaryp. 124
5.5 Example of Convergence Ratep. 126
6 A Semigroup Construction Methodp. 129
6.1 Constituent Problemsp. 130
6.2 Operating on the Transformed Operatorsp. 133
6.3 The HJB PDE Limit Problemsp. 134
6.4 A Simple Examplep. 138
7 Curse-of-Dimensionality-Free Methodp. 143
7.1 DP for the Constituent and Originating Problemsp. 146
7.2 Max-Plus Spaces and Dual Operatorsp. 150
7.3 Discrete Time Approximationp. 158
7.4 The Algorithmp. 164
7.5 Practical Issuesp. 170
7.5.1 Pruningp. 170
7.5.2 Initializationp. 171
7.6 Examplesp. 171
7.7 More General Quadratic Constituentsp. 175
7.8 Future Directionsp. 180
8 Finite Time-Horizon Application: Nonlinear Filteringp. 183
8.1 Semiconvexityp. 187
8.2 Max-Plus Propagationp. 192
9 Mixed L[subscript infinity]/L[subscript 2] Criteriap. 197
9.1 Mixed L[subscript infinity]/L[subscript 2] Problem Formulationp. 197
9.2 Dynamic Programmingp. 200
9.2.1 Dynamic Programming Principlesp. 200
9.2.2 Dynamic Programming Equationsp. 204
9.3 Max-Plus Representations and Semiconvexityp. 205
9.4 Max-Plus Numerical Methodsp. 209
9.4.1 Nonuniqueness for the Max-Plus Affine Equationp. 211
9.4.2 The Affine Power Methodp. 212
A Miscellaneous Proofsp. 217
A.0.1 Sketch of Proof of Theorem 2.8p. 217
A.0.2 Proof of Theorem 3.13p. 218
A.0.3 Proof of Lemma 3.15p. 220
A.0.4 Sketch of Proof of Theorem 7.27p. 222
A.0.5 Sketch of Proof of Lemma 7.31p. 224
A.0.6 Existence of Robust/H[subscript infinity] Estimator and a Disturbance Boundp. 228
Referencesp. 233
Indexp. 239