The Robust Maximum Principle Theory and Applications [Hardcover]

Covering some of the key areas of optimal control theory (OCT), a rapidly expanding field, the authors use new methods to set out a version of OCTs more refined?maximum principle. The results obtained?have applications?in production planning, reinsurance-dividend management, multi-model sliding mode control, and multi-model differential games.

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.

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 OCTs 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, covering its principle topics of the maximum principle and dynamic programming and considering the important sub-problems of linear quadratic optimal control and time optimization. Moving on to examine the tent method in detail, the book then presents its core material, which is a more rl;