| 书目名称 | Modelling and Control of Dynamic Systems Using Gaussian Process Models |
| 编辑 | Juš Kocijan |
| 视频video | |
| 概述 | 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 |
| 丛书名称 | Advances in Industrial Control |
| 图书封面 |  |
| 描述 | .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 measureme |
| 出版日期 | Book 2016 |
| 关键词 | Atmospheric Ozone; Fault Detection; Fault Diagnosis; Gas–Liquid Separator; Gaussian Process Model; Hydrau |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-21021-6 |
| isbn_softcover | 978-3-319-79327-6 |
| isbn_ebook | 978-3-319-21021-6Series ISSN 1430-9491 Series E-ISSN 2193-1577 |
| issn_series | 1430-9491 |
| copyright | Springer International Publishing Switzerland 2016 |
发表于 2025-3-21 20:02:58
