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Titlebook: Nonlinear Model Predictive Control; Frank Allg?wer,Alex Zheng Conference proceedings 2000 Springer Basel AG 2000 Differentialgleichungen.S

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書目名稱Nonlinear Model Predictive Control
編輯Frank Allg?wer,Alex Zheng
視頻videohttp://file.papertrans.cn/668/667560/667560.mp4
叢書名稱Progress in Systems and Control Theory
圖書封面Titlebook: Nonlinear Model Predictive Control;  Frank Allg?wer,Alex Zheng Conference proceedings 2000 Springer Basel AG 2000 Differentialgleichungen.S
描述.During the past decade model predictive control (MPC), also referred to as receding horizon control or moving horizon control, has become the preferred control strategy for quite a number of industrial processes. There have been many significant advances in this area over the past years, one of the most important ones being its extension to nonlinear systems. This book gives an up-to-date assessment of the current state of the art in the new field of nonlinear model predictive control (NMPC). The main topic areas that appear to be of central importance for NMPC are covered, namely receding horizon control theory, modeling for NMPC, computational aspects of on-line optimization and application issues. The book consists of selected papers presented at the International Symposium on Nonlinear Model Predictive Control – Assessment and Future Directions, which took place from June 3 to 5, 1998, in Ascona, Switzerland..The book is geared towards researchers and practitioners in the area of control engineering and control theory. It is also suited for postgraduate students as the book contains several overview articles that give a tutorial introduction into the various aspects of nonline
出版日期Conference proceedings 2000
關鍵詞Differentialgleichungen; Systemtheorie; control engineering; model; modeling; optimization; systems theory
版次1
doihttps://doi.org/10.1007/978-3-0348-8407-5
isbn_softcover978-3-0348-9554-5
isbn_ebook978-3-0348-8407-5
copyrightSpringer Basel AG 2000
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Modeling and Identification for NonlinearModel Predictive Control: Requirements,Current Status and Frious empirical modeling methods are examined in light of these requirements. A promising new paradigm of nonlinear subspace identification is put forth. We conclude the paper with a discussion of future research needs.
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Structural Concepts for Optimization Based Control of Transient Processesicular, a direct and several decomposition approaches are presented. Applicability of the different approaches is treated with respect to the time scales of the process, the disturbances and the available process models. A number of illustrative examples from the optimization of semi-batch reactors are given.
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Continuous-time Predictive Control of Constrained Nonlinear Systemsn terms of an admissible set for the prediction system state to derive an asymptotically optimal control law. Closed-loop stability and convergence are guaranteed without the need for end-point constraints.
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