Model-Based Control: (eBook, PDF)

Bridging Rigorous Theory and Advanced Technology
Redaktion: Hof, Paul M. J. van den; Heuberger, Peter S. C.; Scherer, Carsten

• Format: PDF

Produktbeschreibung

Model-Based Control: Bridging Rigorous Theory and Advanced Technology contains a collection of contributions written in honor of Professor Okko Bosgra's sixty-fifth birthday. The book follows his lifelong idea of establishing a unified research agenda that covers a wide cross-section of the model-based control field, ranging from modeling and identification to optimal and robust control. It presents a collection of advances in the aforementioned areas, contributed by a group of leading academics in systems and control. The book's chapters connect major theoretical developments with practical applications across numerous subject areas, while utilizing clear and well-defined case-studies that help the reader relate theory to practice. Particular attention is given to the application domains of motion control systems, as well as large-scale industrial process control systems.



Model-Based Control is required reading for academic researchers and engineers actively working with process systems or mechatronics who are interested in learning more about model-based control.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer US
• Seitenzahl: 239
• Erscheinungstermin: 5. August 2009
• Englisch
• ISBN-13: 9781441908957
• Artikelnr.: 37341272

Inhaltsangabe

Fundamentals.- Linear Systems in Discrete Time.- Robust Controller Synthesis is Convex for Systems without Control Channel Uncertainties.- Conservation Laws and Lumped System Dynamics.- Polynomial Optimization Problems are Eigenvalue Problems.- Bridging Theory and Applied Technology.- Designing Instrumentation for Control.- Uncertain Model Set Calculation from Frequency Domain Data.- Robust Estimation for Automatic Controller Tuning with Application to Active Noise Control.- Identification of Parameters in Large Scale Physical Model Structures, for the Purpose of Model-Based Operations.- Applications in Motion Control Systems and Industrial Process Control.- Recovering Data from Cracked Optical Discs using Hankel Iterative Learning Control.- Advances in Data-driven Optimization of Parametric and Non-parametric Feedforward Control Designs with Industrial Applications.- Incremental Identification of Hybrid Models of Dynamic Process Systems.- Front Controllability in Two-Phase Porous Media Flow.- PhD Supervision by Okko H. Bosgra.- Okko H. Bosgra, Bibliographic Record.