书目名称 | Model Predictive Control |
副标题 | Classical, Robust an |
编辑 | Basil Kouvaritakis,Mark Cannon |
视频video | |
概述 | Equips the student to deal with broad classes of system uncertainties with the first textbook treatment of stochastic predictive control.Gives the student an up-to-date source on robust predictive con |
丛书名称 | Advanced Textbooks in Control and Signal Processing |
图书封面 |  |
描述 | .For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques...Model Predictive Control .describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplicative and stochastic model uncertainty. The book provides:...extensive use of illustrative examples;..sample problems; and..discussion of novel control applications such asr |
出版日期 | Textbook 2016 |
关键词 | Constained Systems; Controller Parameterization; Convex Optimization; Model Predictive Control Textbook |
版次 | 1 |
doi | https://doi.org/10.1007/978-3-319-24853-0 |
isbn_softcover | 978-3-319-79689-5 |
isbn_ebook | 978-3-319-24853-0Series ISSN 1439-2232 Series E-ISSN 2510-3814 |
issn_series | 1439-2232 |
copyright | Springer International Publishing AG, part of Springer Nature 2016 |