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  • Book
  • © 2012

The Robust Maximum Principle

Theory and Applications

Birkhäuser
  • Class-tested in mathematical institutions throughout the world
  • Includes a stand-alone review of classical optimal control theory
  • Presents a new version of the maximum principle for the construction of optimal control strategies for the class of uncertain systems given by a system of ordinary differential equations with unknown parameters from a given set that corresponds to different scenarios of possible dynamics
  • Real-world applications to areas such as production planning and reinsurance-dividend management
  • Applications of obtained results from dynamic programming derivations to multi-model sliding mode control and multi-model differential games
  • Includes supplementary material: sn.pub/extras

Part of the book series: Systems & Control: Foundations & Applications (SCFA)

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Table of contents (17 chapters)

  1. Front Matter

    Pages I-XXII
  2. Introduction

    • Vladimir G. Boltyanski, Alexander S. Poznyak
    Pages 1-6
  3. Topics of Classical Optimal Control

    1. Front Matter

      Pages 7-7
    2. The Maximum Principle

      • Vladimir G. Boltyanski, Alexander S. Poznyak
      Pages 9-43
    3. Dynamic Programming

      • Vladimir G. Boltyanski, Alexander S. Poznyak
      Pages 45-69
    4. Linear Quadratic Optimal Control

      • Vladimir G. Boltyanski, Alexander S. Poznyak
      Pages 71-118
    5. Time-Optimization Problem

      • Vladimir G. Boltyanski, Alexander S. Poznyak
      Pages 119-128
  4. Tent Method

    1. Front Matter

      Pages 129-129
    2. The Tent Method in Finite-Dimensional Spaces

      • Vladimir G. Boltyanski, Alexander S. Poznyak
      Pages 131-147
    3. Extremal Problems in Banach Spaces

      • Vladimir G. Boltyanski, Alexander S. Poznyak
      Pages 149-188
  5. Robust Maximum Principle for Deterministic Systems

    1. Front Matter

      Pages 189-189
    2. Finite Collection of Dynamic Systems

      • Vladimir G. Boltyanski, Alexander S. Poznyak
      Pages 191-211
    3. Multimodel Bolza and LQ Problem

      • Vladimir G. Boltyanski, Alexander S. Poznyak
      Pages 213-228
    4. Linear Multimodel Time Optimization

      • Vladimir G. Boltyanski, Alexander S. Poznyak
      Pages 229-251
    5. A Measurable Space as Uncertainty Set

      • Vladimir G. Boltyanski, Alexander S. Poznyak
      Pages 253-267
    6. Dynamic Programming for Robust Optimization

      • Vladimir G. Boltyanski, Alexander S. Poznyak
      Pages 269-283
    7. Min-Max Sliding-Mode Control

      • Vladimir G. Boltyanski, Alexander S. Poznyak
      Pages 285-306
    8. Multimodel Differential Games

      • Vladimir G. Boltyanski, Alexander S. Poznyak
      Pages 307-339
  6. Robust Maximum Principle for Stochastic Systems

    1. Front Matter

      Pages 341-341
    2. Multiplant Robust Control

      • Vladimir G. Boltyanski, Alexander S. Poznyak
      Pages 343-376

About this book

Both refining and extending previous publications by the authors, the material in this monograph has been class-tested in mathematical institutions throughout the world. Covering some of the key areas of optimal control theory (OCT)—a rapidly expanding field that has developed to analyze the optimal behavior of a constrained process over time—the authors use new methods to set out a version of OCT’s more refined ‘maximum principle’ designed to solve the problem of constructing optimal control strategies for uncertain systems where some parameters are unknown. Known as a ‘min-max’ problem, this type of difficulty occurs frequently when dealing with finite uncertain sets.

The text begins with a standalone section that reviews classical optimal control theory. Moving on to examine the tent method in detail, the book then presents its core material, which is a more robust maximum principle for both deterministic and stochastic systems. The results obtained have applications in production planning, reinsurance-dividend management, multi-model sliding mode control, and multi-model differential games.

Using powerful new tools in optimal control theory, this book explores material that will be of great interest to post-graduate students, researchers, and practitioners in applied mathematics and engineering, particularly in the area of systems and control.

Reviews

From the reviews:

“This book is a useful and positive contribution to the literature of optimal control theory. … The book covers a rather expansive collection of topics, individual topics are usually well motivated, and most chapters have concluding and, on occasion, historical remarks to provide useful perspective to the reader. … more suitable as a reference for researchers … .” (Kevin A. Grasse, Mathematical Reviews, September, 2013)

“This good structured and really clearly written book is worth reading both for readers interested in theory and applications of optimal control. For theory, since robustness embraces dependencies and sensitivities with respect to deterministic or stochastic uncertainties, and for applications, since robustness of a method is responsible for a good use of numerical results. … The special technique specific for stochastic calculus is fully used in the last section of the book and supports the recommendation that it is a pleasure to read this book.” (Alfred Göpfert, Zentralblatt MATH, Vol. 1239, 2012)

Authors and Affiliations

  • CIMAT, Guanajuato, Mexico

    Vladimir G. Boltyanski

  • , Automatic Control Department, CINVESTAV-IPN, AP-14-740, México, Mexico

    Alexander S. Poznyak

Bibliographic Information

Buy it now

Buying options

eBook USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book USD 139.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access