General Pontryagin-Type Stochastic Maximum Principle and Backward Stochastic Evolution Equations in Infinite Dimensions

Nonfiction, Science & Nature, Science, Other Sciences, System Theory, Mathematics, Calculus, Reference & Language, Reference
Cover of the book General Pontryagin-Type Stochastic Maximum Principle and Backward Stochastic Evolution Equations in Infinite Dimensions by Xu Zhang, Qi Lü, Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Xu Zhang, Qi Lü ISBN: 9783319066325
Publisher: Springer International Publishing Publication: June 2, 2014
Imprint: Springer Language: English
Author: Xu Zhang, Qi Lü
ISBN: 9783319066325
Publisher: Springer International Publishing
Publication: June 2, 2014
Imprint: Springer
Language: English

The classical Pontryagin maximum principle (addressed to deterministic finite dimensional control systems) is one of the three milestones in modern control theory. The corresponding theory is by now well-developed in the deterministic infinite dimensional setting and for the stochastic differential equations. However, very little is known about the same problem but for controlled stochastic (infinite dimensional) evolution equations when the diffusion term contains the control variables and the control domains are allowed to be non-convex. Indeed, it is one of the longstanding unsolved problems in stochastic control theory to establish the Pontryagin type maximum principle for this kind of general control systems: this book aims to give a solution to this problem. This book will be useful for both beginners and experts who are interested in optimal control theory for stochastic evolution equations.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

The classical Pontryagin maximum principle (addressed to deterministic finite dimensional control systems) is one of the three milestones in modern control theory. The corresponding theory is by now well-developed in the deterministic infinite dimensional setting and for the stochastic differential equations. However, very little is known about the same problem but for controlled stochastic (infinite dimensional) evolution equations when the diffusion term contains the control variables and the control domains are allowed to be non-convex. Indeed, it is one of the longstanding unsolved problems in stochastic control theory to establish the Pontryagin type maximum principle for this kind of general control systems: this book aims to give a solution to this problem. This book will be useful for both beginners and experts who are interested in optimal control theory for stochastic evolution equations.

More books from Springer International Publishing

Cover of the book Using Transparency Against Corruption in Public Procurement by Xu Zhang, Qi Lü
Cover of the book Algebraic Geometry for Coding Theory and Cryptography by Xu Zhang, Qi Lü
Cover of the book Bipolar Depression: Molecular Neurobiology, Clinical Diagnosis, and Pharmacotherapy by Xu Zhang, Qi Lü
Cover of the book Novel Functional Magnetic Materials by Xu Zhang, Qi Lü
Cover of the book Computational Collective Intelligence by Xu Zhang, Qi Lü
Cover of the book Congregations in Europe by Xu Zhang, Qi Lü
Cover of the book Politics and Bureaucracy in the Norwegian Welfare State by Xu Zhang, Qi Lü
Cover of the book Systemic Racism in the United States by Xu Zhang, Qi Lü
Cover of the book Mobility, Migration and Transport by Xu Zhang, Qi Lü
Cover of the book Synopsis of Pathophysiology in Nuclear Medicine by Xu Zhang, Qi Lü
Cover of the book Service Life Prediction of Exterior Plastics by Xu Zhang, Qi Lü
Cover of the book Balancing Individualism and Collectivism by Xu Zhang, Qi Lü
Cover of the book Moons of the Solar System by Xu Zhang, Qi Lü
Cover of the book Fair Queueing by Xu Zhang, Qi Lü
Cover of the book The Distribution of Income and Wealth by Xu Zhang, Qi Lü
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy