A First Course in Predictive Control / J.A. Rossiter

Von:

Rossiter, J. A [VerfasserIn]

Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: Control SeriesVerlag: Boca Raton ; London ; New York : CRC Press, Taylor & Francis Group, 2018Auflage: Second editionBeschreibung: 1 Online-RessourceISBN:

9781351597166
9781351597159

Schlagwörter:

Andere physische Formen: 9781138099340. | 9781351597142 | 9781315104126. | Erscheint auch als: A first course in predictive control. Druck-Ausgabe Second edition. Boca Raton : CRC Press, Taylor & Francis Group, 2018. xxiii, 402 SeitenDDC-Klassifikation:

629.8

LOC-Klassifikation:

TJ217.6

Online-Ressourcen:

Zugang im Netz des KIT

Zusammenfassung: 1.6.6 Degrees of freedom in the predictions or prediction class . .1.6.7 Tuning; 1.6.8 Constraint handling; 1.6.9 Multivariable and interactive systems; 1.6.10 Systematic use of future demands; 1.7 MPC philosophy in summary; 1.8 MATLAB files from this chapter; 1.9 Reminder of book organisation; Chapter 2 Prediction in model predictive control; 2.1 Introduction; 2.2 Guidance for the lecturer/reader; 2.2.1 Typical learning outcomes for an examination assessment .; 2.2.2 Typical learning outcomes for an assignment/coursework . .; 2.3 General format of prediction modellingZusammenfassung: 2.3.1 Notation for vectors of past and future values2.3.2 Format of general prediction equation; 2.3.3 Double subscript notation for predictions; 2.4 Prediction with state space models; 2.4.1 Prediction by iterating the system model; 2.4.2 Predictions in matrix notation; 2.4.3 Unbiased prediction with state space models; 2.4.4 The importance of unbiased prediction and deviation variables; 2.4.5 State space predictions with deviation variables; 2.4.6 Predictions with state space models and input increments .; 2.5 Prediction with transfer function models -- matrix methodsZusammenfassung: 2.5.1 Ensuring unbiased prediction with transfer function models2.5.2 Prediction for a CARIMA model with T(z) = 1: the SISO case; 2.5.3 Prediction with a CARIMA model and T = 1: the MIMO case; 2.5.4 Prediction equations with T(z) = 1: the SISO case; 2.5.4.1 Summary of the key steps in computing prediction equations with a T-filter; 2.5.4.2 Forming the prediction equations with a T-filter beginning from predictions (2.59); 2.6 Using recursion to find prediction matrices for CARIMA models .; 2.7 Prediction with independent models; 2.7.1 Structure of an independent model and predictionsZusammenfassung: "The book presents a significant expansion in depth and breadth of the previous edition. It includes substantially more numerical illustrations and copious supporting MATLAB code that the reader can use to replicate illustrations or build his or her own. The code is deliberately written to be as simple as possible and easy to edit. The book is an excellent starting point for any researcher to gain a solid grounding in MPC concepts and algorithms before moving into application or more advanced research topics. Sample problems for readers are embedded throughout the chapters, and in-text questions are designed for readers to demonstrate an understanding of concepts through numerical simulation."--Provided by publisherPPN: PPN: 102633103XPackage identifier: Produktsigel: ZDB-4-NLEBK

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