Modelling and Control of Dynamic Systems Using Gaussian Process Models
暫譯: 使用高斯過程模型進行動態系統建模與控制

Kocijan, Jus

Modelling and Control of Dynamic Systems Using Gaussian Process Models

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商品描述

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.

A MATLAB(R) toolbox, for identification and simulation of dynamic GP models is provided for download.

商品描述(中文翻譯)

這本專著為從事或對系統辨識與控制領域新發展感興趣的工程師和學術研究者開啟了新的視野。它強調的是針對可行解的指導方針和實施的實用建議，而非高斯過程（Gaussian process, GP）模型的理論背景。這本書展示了這一近期在機率機器學習方法中的發展潛力，並使讀者對該主題有直觀的理解。當前的技術狀態以及未來研究的可能方向都在書中有所探討。

系統控制設計依賴於數學模型，而這些模型可以從測量數據中發展而來。基於高斯過程模型的系統辨識過程，能在數據驅動的控制設計中扮演重要角色，這一描述是文本中的一個重要方面。書中首先介紹高斯過程回歸的背景，然後進入系統辨識和先驗知識的整合，最終導向完整的控制設計。書中廣泛使用範例、線條圖和計算機模擬結果及工廠測量的圖形展示來進行說明。所呈現的研究結果應用於從成功應用中提取的現實案例研究，包括：

- 氣液分離器控制；
- 城市交通信號建模與重建；
- 大氣臭氧濃度預測。

提供了一個 MATLAB(R) 工具箱，用於動態高斯過程模型的辨識和模擬，供下載使用。

作者簡介

Jus 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.

作者簡介(中文翻譯)

Jus Kocijan 是斯洛維尼亞約瑟夫·斯特凡研究所（Jozef Stefan Institute）系統與控制系的高級研究員，該研究所是自然科學和工程領域的領先研究機構，同時也是斯洛維尼亞新戈里察大學（University of Nova Gorica）的電機工程教授。他在控制工程領域的過去經驗包括在盧布爾雅那大學（University of Ljubljana）的教學和研究，以及在幾所歐洲大學和研究所的訪問研究和教學職位。他通過多項國內和國際研究補助金和項目積極參與自動控制的應用研究，其中相當多的項目他擔任項目負責人。他的研究興趣包括使用高斯過程模型對動態系統進行建模、基於高斯過程模型的控制、多模型建模和控制方法、應用非線性控制、個別通道分析與設計等。他的其他經驗包括：擔任《人工智慧工程應用》（Engineering Applications of Artificial Intelligence）期刊的編輯之一，以及其他研究期刊的編輯委員會成員，擔任國際自動控制聯合會（IFAC）計算智能控制技術委員會的成員，並積極參與多個科學會議的國際程序和組織委員會。Kocijan 教授是自動控制、建模和模擬領域各種國內和國際專業學會的成員。

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