Iterative Dynamic Programming
Seiten
2000
Chapman & Hall/CRC (Verlag)
978-1-58488-148-3 (ISBN)
Chapman & Hall/CRC (Verlag)
978-1-58488-148-3 (ISBN)
Iterative dynamic programming (IDP) has been refined to handle inequality state constraints and noncontinuous functions. This book offers a comprehensive presentation of this powerful tool. It provides the necessary background, examines the effects of the parameters involved, and illustrates IDP's advantages.
Dynamic programming is a powerful method for solving optimization problems, but has a number of drawbacks that limit its use to solving problems of very low dimension. To overcome these limitations, author Rein Luus suggested using it in an iterative fashion. Although this method required vast computer resources, modifications to his original scheme have made the computational procedure feasible.
With iteration, dynamic programming becomes an effective optimization procedure for very high-dimensional optimal control problems and has demonstrated applicability to singular control problems. Recently, iterative dynamic programming (IDP) has been refined to handle inequality state constraints and noncontinuous functions.
Iterative Dynamic Programming offers a comprehensive presentation of this powerful tool. It brings together the results of work carried out by the author and others - previously available only in scattered journal articles - along with the insight that led to its development. The author provides the necessary background, examines the effects of the parameters involved, and clearly illustrates IDP's advantages.
Dynamic programming is a powerful method for solving optimization problems, but has a number of drawbacks that limit its use to solving problems of very low dimension. To overcome these limitations, author Rein Luus suggested using it in an iterative fashion. Although this method required vast computer resources, modifications to his original scheme have made the computational procedure feasible.
With iteration, dynamic programming becomes an effective optimization procedure for very high-dimensional optimal control problems and has demonstrated applicability to singular control problems. Recently, iterative dynamic programming (IDP) has been refined to handle inequality state constraints and noncontinuous functions.
Iterative Dynamic Programming offers a comprehensive presentation of this powerful tool. It brings together the results of work carried out by the author and others - previously available only in scattered journal articles - along with the insight that led to its development. The author provides the necessary background, examines the effects of the parameters involved, and clearly illustrates IDP's advantages.
Rein Luus
Chapter 1: Fundamental concepts; Chapter 2: Steady-state optimization; Chapter 3: Dynamic programming; Chapter 4: Iterative dynamic programming; Chapter 5: Allowable values for control; Chapter 6: Evaluation of parameters in IDP; Chapter 7: Piecewise linear control; Chapter 8: Time-delay systems; Chapter 9: Variable stage lengths; Chapter 10: Singular control problems; Chapter 11: State constraints; Chapter 12: Time optimal control; Chapter 13: Nonseparable problems; Chapter 14: Sensitivity considerations; Chapter 15: Toward practical optimal control
| Erscheint lt. Verlag | 27.1.2000 |
|---|---|
| Reihe/Serie | Monographs and Surveys in Pure and Applied Mathematics |
| Zusatzinfo | 57 Tables, black and white |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 790 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Theorie / Studium |
| Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
| Technik ► Elektrotechnik / Energietechnik | |
| ISBN-10 | 1-58488-148-8 / 1584881488 |
| ISBN-13 | 978-1-58488-148-3 / 9781584881483 |
| Zustand | Neuware |
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