Modelling and Control of Dynamic Systems Using Gaussian Process Models

AvJuš Kocijan

Inbunden, Engelska, 2015

Del i serien Advances in Industrial Control

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Beskrivning

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 separatorcontrol;urban-traffic signalmodelling and reconstruction; andprediction of atmosphericozone concentration.A MATLAB® toolbox, for identification and simulation ofdynamic GP models is provided for download.

Produktinformation

Utgivningsdatum:2015-12-07
Mått:155 x 235 x 20 mm
Vikt:646 g
Format:Inbunden
Språk:Engelska
Serie:Advances in Industrial Control
Antal sidor:267
Upplaga:15001
Förlag:Springer International Publishing AG
ISBN:9783319210209

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Mer om författaren

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.

Innehållsförteckning

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