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Titlebook: Methods of Model Based Process Control; Ridvan Berber Book 19951st edition Kluwer Academic Publishers 1995 design.fuzzy.model.modeling.num

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书目名称Methods of Model Based Process Control
编辑Ridvan Berber
视频video
丛书名称NATO Science Series E:
图书封面Titlebook: Methods of Model Based Process Control;  Ridvan Berber Book 19951st edition Kluwer Academic Publishers 1995 design.fuzzy.model.modeling.num
描述Model based control has emerged as an important way to improveplant efficiency in the process industries, while meeting processingand operating policy constraints. The reader of .Methods of ModelBased. .Process Control. will find state of the art reports onmodel based control technology presented by the world‘s leadingscientists and experts from industry. All the important issues that amodel based control system has to address are covered in depth,ranging from dynamic simulation and control-relevant identification toinformation integration. Specific emerging topics are also covered,such as robust control and nonlinear model predictive control. Inaddition to critical reviews of recent advances, the reader will findnew ideas, industrial applications and views of future needs andchallenges. ..Audience.: A reference for graduate-level courses and acomprehensive guide for researchers and industrial control engineersin their explorationof the latest trends in the area. .
出版日期Book 19951st edition
关键词design; fuzzy; model; modeling; numerical methods; optimization; polymer; simulation
版次1
doihttps://doi.org/10.1007/978-94-011-0135-6
isbn_softcover978-94-010-4061-7
isbn_ebook978-94-011-0135-6Series ISSN 0168-132X
issn_series 0168-132X
copyrightKluwer Academic Publishers 1995
The information of publication is updating

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Mp Tuning and Synthesis[.] to obtain models for optimal control system performance for three uncertain processes: 1) a second order process with uncertainty in time constant and damping ratio, 2) an overdamped second order plus dead time process and, 3) a non collocated spring mass system.
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Nonlinear Moving Horizon State Estimationequivalent to the optimal filter. Constraints are added to the moving horizon estimator to improve robustness to modeling errors. Finally, nonlinear batch and moving horizon estimators are discussed and shown to be nominally stable. Previous implementations of these techniques in the process control literature are reviewed.
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Attainable Performance in LQG Control available measurements. Introduction of two additional measurements is believed to partly resolve the observed limitation in the estimator. Also, a rotary kiln is investigated, and it is shown that the available measurements may limit the attainable performance.
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