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Modelling and Control of Dynamic Systems Using Gaussian Process Models

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This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research.

Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior knowledge then leading into full-blown control. The book is illustrated by extensive use of examples, line drawings, and graphical presentation of computer-simulation results and plant measurements. The research results presented are applied in real-life case studies drawn from successful applications including:

a gas–liquid separator control;
urban-traffic signal modelling and reconstruction; and
prediction of atmospheric ozone concentration.

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Detail Information

Series Title

Advances in Industrial Control

Call Number

-

Publisher

: ., 2016

Collation

XVI, 267

Language

English

ISBN/ISSN

978-3-319-21020-9

Classification

NONE

Content Type

-

Media Type

-

Carrier Type

-

Edition

1

Subject(s)

Computer Science
Physics
Industrial Chemistry
Control and Systems Theory
Statistics in Engineering
Chemistry and Earth Sciences

Specific Detail Info

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Statement of Responsibility

Juš Kocijan

Other Information

Cataloger

AJUN

Source

-

Validator

-

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