Buch, Englisch, 137 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 248 g
Approaches Based on the Extended State Space Model and Extended Non-minimal State Space Model
Buch, Englisch, 137 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 248 g
ISBN: 978-981-13-4326-1
Verlag: Springer Nature Singapore
This monograph introduces the authors’ work on model predictive control system design using extended state space and extended non-minimal state space approaches. It systematically describes model predictive control design for chemical processes, including the basic control algorithms, the extension to predictive functional control, constrained control, closed-loop system analysis, model predictive control optimization-based PID control, genetic algorithm optimization-based model predictive control, and industrial applications. Providing important insights, useful methods and practical algorithms that can be used in chemical process control and optimization, it offers a valuable resource for researchers, scientists and engineers in the field of process system engineering and control engineering.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Energietechnik | Elektrotechnik Energieeffizienz
- Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Regelungstechnik
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Mathematik | Informatik Mathematik Mathematik Interdisziplinär Systemtheorie
Weitere Infos & Material
Introduction.- Model Predictive Control Based on Extended State Space Model.- Predictive Functional Control Based on Extended State Space Model.- Model Predictive Control Based on Extended Non-Minimal State Space Model.- Predictive Functional Control Based on Extended Non-minimal State Space Model.- Model Predictive Control Under Constraints.- PID Control Using Extended Non-minimal State Space Model Optimization.- Closed-loop System Performance Analysis.- Model Predictive Control Performance Optimized by Genetic Algorithm.- Industrial Application.- Further Ideas on MPC and PFC Using Relaxed Constrained Optimization.