Process Systems Engineering
Volume 2: Multi-Parametric Model-Based Control
Process Systems Engineering (Band Nr. 2)
1. Auflage Februar 2007
XVIII, 257 Seiten, Hardcover
165 Abbildungen (15 Farbabbildungen)
Handbuch/Nachschlagewerk
Kurzbeschreibung
This volume covers all aspects of multi-parametric model-based control, highlighting its applications in process systems engineering, focusing on both fundamental research, as well as developing mechanisms for the transfer of the new technologies to industrial applications.
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This volume covers theoretical advances and developments, computational challenges and tools as well as applications in the area of multi-parametric model based control.
Part I is concerned with the presentation of algorithms for parametric model based control focusing on:
- novel frameworks for the derivation of explicit optimal control policies for continuous time-linear dynamic systems
- new theoretical developments on hybrid model based control
- methods for obtaining the explicit robust model-based tracking control
- theoretical frameworks for parametric dynamic optimization and
- recent developments for continuous-time systems
Part II presents a series of application in the following areas:
- the incorporation of advanced model based controllers in a simultaneous process design and control framework for complex separation systems
- the development of advanced model based control techniques for regulating the blood glucose for patients with Type 1 diabetes
- the design of model predictive and parametric controllers for anesthesia.
- the development of optimal control policies in a pilot plant exothermic reactor
The volume is intended for academics and researchers that carry out model based control research, industrial practitioners involved in the control of new and existing processes and products, policy makers, as well as for educational purposes both in academia and industry.
Linear Model Predictive Control via Multi-Parametric Programming
Hybrid Parametric Model Based Control
Robust Parametric Model-Based Control
Parametric Dynamic Optimization
ConiParametric Model Based Control
PART II: APPLICATIONS
Integration of Design and Control
Model Based Control of Blood Glucose for Type 1 Diabetes
Control of Anaesthesia
Model based Control of a Pilot Plant Reactor
MPC on a Chip
Michael C. Georgiadis is Head of the Process System Engineering Laboratory at the PSE, Imperial College London and is the manager for academic business development of Process Systems Enterprise Ltd in Thessaloniki, Greece. He obtained his Chemical Engineering degree from Aristotle University of Thessaloniki, Greece and a MSc and PhD from Imperial College London. Dr. Georgiadis has authored/ co-authored over 55 papers and two books. He has a long experience in the management and participation of more than 20 collaborative research contracts and projects.
Vivek Dua is a Lecturer in the Department of Chemical Engineering at University College London. He holds a degree in Chemical Engineering from Panjab University, Chandigarh, India and MTech in chemical engineering from the Indian Institute of Technology, Kanpur. He joined Kinetics Technology India Ltd. as a Process Engineer before moving to Imperial College London, where he obtained his PhD in Chemical Engineering. He was an Assistant Professor in the Department of Chemical Engineering at Indian Institute of Technology, Delhi before joining University College London. He is a co-founder of Parametric Optimization Solutions (PAROS) Ltd.
Process Systems Enterprise (PSE), provider of the gPROMS advanced process simulation and modelling environment, is the 2007 winner of the Royal Academy of Engineering's MacRobert Award. The award, the UK's most prestigious for engineering, recognises the successful development of innovative ideas. The PSE team was presented with the MacRobert gold medal by HRH Prince Philip.