Stochastic Averaging and Stochastic Extremum Seeking

Nonfiction, Science & Nature, Technology, Automation, Mathematics, Calculus
Cover of the book Stochastic Averaging and Stochastic Extremum Seeking by Shu-Jun Liu, Miroslav Krstic, Springer London
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Shu-Jun Liu, Miroslav Krstic ISBN: 9781447140870
Publisher: Springer London Publication: June 16, 2012
Imprint: Springer Language: English
Author: Shu-Jun Liu, Miroslav Krstic
ISBN: 9781447140870
Publisher: Springer London
Publication: June 16, 2012
Imprint: Springer
Language: English

Stochastic Averaging and Extremum Seeking treats methods inspired by attempts to understand the seemingly non-mathematical question of bacterial chemotaxis and their application in other environments. The text presents significant generalizations on existing stochastic averaging theory developed from scratch and necessitated by the need to avoid violation of previous theoretical assumptions by algorithms which are otherwise effective in treating these systems. Coverage is given to four main topics.
Stochastic averaging theorems are developed for the analysis of continuous-time nonlinear systems with random forcing, removing prior restrictions on nonlinearity growth and on the finiteness of the time interval. The new stochastic averaging theorems are usable not only as approximation tools but also for providing stability guarantees.
Stochastic extremum-seeking algorithms are introduced for optimization of systems without available models. Both gradient- and Newton-based algorithms are presented, offering the user the choice between the simplicity of implementation (gradient) and the ability to achieve a known, arbitrary convergence rate (Newton).
The design of algorithms for non-cooperative/adversarial games is described. The analysis of their convergence to Nash equilibria is provided. The algorithms are illustrated on models of economic competition and on problems of the deployment of teams of robotic vehicles.
Bacterial locomotion, such as chemotaxis in E. coli, is explored with the aim of identifying two simple feedback laws for climbing nutrient gradients. Stochastic extremum seeking is shown to be a biologically-plausible interpretation for chemotaxis. For the same chemotaxis-inspired stochastic feedback laws, the book also provides a detailed analysis of convergence for models of nonholonomic robotic vehicles operating in GPS-denied environments.
The book contains block diagrams and several simulation examples, including examples arising from bacterial locomotion, multi-agent robotic systems, and economic market models.
Stochastic Averaging and Extremum Seeking will be informative for control engineers from backgrounds in electrical, mechanical, chemical and aerospace engineering and to applied mathematicians. Economics researchers, biologists, biophysicists and roboticists will find the applications examples instructive.

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

Stochastic Averaging and Extremum Seeking treats methods inspired by attempts to understand the seemingly non-mathematical question of bacterial chemotaxis and their application in other environments. The text presents significant generalizations on existing stochastic averaging theory developed from scratch and necessitated by the need to avoid violation of previous theoretical assumptions by algorithms which are otherwise effective in treating these systems. Coverage is given to four main topics.
Stochastic averaging theorems are developed for the analysis of continuous-time nonlinear systems with random forcing, removing prior restrictions on nonlinearity growth and on the finiteness of the time interval. The new stochastic averaging theorems are usable not only as approximation tools but also for providing stability guarantees.
Stochastic extremum-seeking algorithms are introduced for optimization of systems without available models. Both gradient- and Newton-based algorithms are presented, offering the user the choice between the simplicity of implementation (gradient) and the ability to achieve a known, arbitrary convergence rate (Newton).
The design of algorithms for non-cooperative/adversarial games is described. The analysis of their convergence to Nash equilibria is provided. The algorithms are illustrated on models of economic competition and on problems of the deployment of teams of robotic vehicles.
Bacterial locomotion, such as chemotaxis in E. coli, is explored with the aim of identifying two simple feedback laws for climbing nutrient gradients. Stochastic extremum seeking is shown to be a biologically-plausible interpretation for chemotaxis. For the same chemotaxis-inspired stochastic feedback laws, the book also provides a detailed analysis of convergence for models of nonholonomic robotic vehicles operating in GPS-denied environments.
The book contains block diagrams and several simulation examples, including examples arising from bacterial locomotion, multi-agent robotic systems, and economic market models.
Stochastic Averaging and Extremum Seeking will be informative for control engineers from backgrounds in electrical, mechanical, chemical and aerospace engineering and to applied mathematicians. Economics researchers, biologists, biophysicists and roboticists will find the applications examples instructive.

More books from Springer London

Cover of the book Evidence-Based Cardiology Consult by Shu-Jun Liu, Miroslav Krstic
Cover of the book Neurodegenerative Diseases by Shu-Jun Liu, Miroslav Krstic
Cover of the book Emergency Echocardiography by Shu-Jun Liu, Miroslav Krstic
Cover of the book Systems Practice: How to Act in a Climate Change World by Shu-Jun Liu, Miroslav Krstic
Cover of the book Virtual and Augmented Reality Applications in Manufacturing by Shu-Jun Liu, Miroslav Krstic
Cover of the book Materials for Nuclear Plants by Shu-Jun Liu, Miroslav Krstic
Cover of the book Bronchial Carcinoma by Shu-Jun Liu, Miroslav Krstic
Cover of the book Secure Information Management Using Linguistic Threshold Approach by Shu-Jun Liu, Miroslav Krstic
Cover of the book The Heart and Stroke by Shu-Jun Liu, Miroslav Krstic
Cover of the book Innovation with Information Technologies in Healthcare by Shu-Jun Liu, Miroslav Krstic
Cover of the book Systems Engineering for Business Process Change: New Directions by Shu-Jun Liu, Miroslav Krstic
Cover of the book Multiple Sclerosis by Shu-Jun Liu, Miroslav Krstic
Cover of the book HCI and User-Experience Design by Shu-Jun Liu, Miroslav Krstic
Cover of the book Real-Time 3D Interventional Echocardiography by Shu-Jun Liu, Miroslav Krstic
Cover of the book Hacking Europe by Shu-Jun Liu, Miroslav Krstic
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