Cantitate/Preț
Produs
Total produse
Vezi coșul
Modelling and Control of Dynamic Systems Using Gaussian Process Models de Juš Kocijan

Modelling and Control of Dynamic Systems Using Gaussian Process Models: Advances in Industrial Control

Autor Juš Kocijan
en Limba Engleză Hardback – 7 dec 2015
This monograph opens up new horizons for engineers and researchers inacademia and in industry dealing with or interested in new developments in thefield of system identification and control. It emphasizes guidelines forworking solutions and practical advice for their implementation rather than thetheoretical background of Gaussian process (GP) models. The book demonstratesthe potential of this recent development in probabilistic machine-learningmethods and gives the reader an intuitive understanding of the topic. Thecurrent state of the art is treated along with possible future directions forresearch.
Systems control design relies on mathematical models and these may bedeveloped from measurement data. This process of system identification, whenbased on GP models, can play an integral part of control design in data-basedcontrol and its description as such is an essential aspect of the text. Thebackground of GP regression is introduced first with system identification andincorporation of prior knowledge then leading into full-blown control. The bookis illustrated by extensive use of examples, line drawings, and graphicalpresentation of computer-simulation results and plant measurements. Theresearch results presented are applied in real-life case studies drawn fromsuccessful applications including:
  • a gas–liquid separator control;
  • urban-traffic signal modelling and reconstruction; and
  • prediction of atmospheric ozone concentration.
A MATLAB® toolbox, for identification and simulation ofdynamic GP models is provided for download.

Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 68171 lei  38-44 zile
  Springer International Publishing – 27 mar 2019 68171 lei  38-44 zile
Hardback (1) 70004 lei  38-44 zile
  Springer International Publishing – 7 dec 2015 70004 lei  38-44 zile

Din seria Advances in Industrial Control

Preț: 70004 lei

Preț vechi: 92110 lei
-24% Nou

Puncte Express: 1050
Preț estimativ în valută:
13399€ • 13965$ • 11154£

Carte tipărită la comandă

Livrare economică 03-09 ianuarie 25

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă
Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783319210209
ISBN-10: 3319210203
Pagini: 267
Ilustrații: XVI, 267 p. 117 illus., 17 illus. in color. With online files/update.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.69 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Seria Advances in Industrial Control

Locul publicării:Cham, Switzerland

Public țintă

Research

Cuprins

System Identification with GP Models.- Incorporation of Prior Knowledge.- Control with GP Models.- Trends, Challenges and Research Opportunities.- Case Studies.

Notă biografică

Juš Kocijan is a senior research fellow at the Department of Systems and Control, Jozef Stefan Institute, the leading Slovenian research institute in the field of natural sciences and engineering, and a Professor of Electrical Engineering at the University of Nova Gorica, Slovenia. His past experience in the field of control engineering includes teaching and research at the University of Ljubljana and visiting research and teaching posts at several European universities and research institutes. He has been active in applied research in automatic control through numerous domestic and international research grants and projects, in a considerable number of which he acted as project leader. His research interests include the modelling of dynamic systems with Gaussian process models, control based on Gaussian process models, multiple-model approaches to modelling and control, applied nonlinear control, Individual Channel Analysis and Design. His other experience includes: serving as one of the editors of the Engineering Applications of Artificial Intelligence journal and on the editorial boards of other research journals, serving as a member of IFAC Technical committee on Computational Intelligence in Control, actively participating as a member of numerous scientific-meeting international programme and organising committees. Prof. Kocijan is a member of various national and international professional societies in the field of automatic control, modelling and simulation.

Textul de pe ultima copertă

This monograph opens upnew horizons for engineers and researchers in academia and in industry dealingwith or interested in new developments in the field of system identificationand control. It emphasizes guidelines for working solutions and practicaladvice for their implementation rather than the theoretical background ofGaussian process (GP) models. The book demonstrates the potential of thisrecent development in probabilistic machine-learning methods and gives thereader an intuitive understanding of the topic. The current state of the art istreated along with possible future directions for research.
Systems control designrelies on mathematical models and these may be developed from measurement data.This process of system identification, when based on GP models, can play anintegral part of control design in data-based control and its description assuch is an essential aspect of the text. The background of GP regression isintroduced first with system identification and incorporation of priorknowledge then leading into full-blown control. The book is illustrated byextensive use of examples, line drawings, and graphical presentation ofcomputer-simulation results and plant measurements. The research resultspresented are applied in real-life case studies drawn from successfulapplications including:
  • a gas–liquid separator control;
  • urban-traffic signal modelling and reconstruction; and
  • prediction of atmospheric ozone concentration.
A MATLAB® toolbox,for identification and simulation of dynamic GP models is provided fordownload.
Advances in IndustrialControl aims to report andencourage the transfer of technology in control engineering. The rapiddevelopment of control technology has an impact on all areas of the controldiscipline. The series offers an opportunity for researchers to present anextended exposition of new work in all aspects of industrial control.

Caracteristici

Explains how theoretical work in Gaussian process models can be applied in the control of real industrial systems Provides the engineer with practical guidance is not unduly encumbered by complicated theory Shows the academic researcher the potential for real-world application of a recent branch of control theory Includes supplementary material: sn.pub/extras