Advanced Control of Industrial Processes

Structures and Algorithms
1. Auflage. 2006
ISBN: 978-1-84628-634-6
Verlag: Springer

Buch, Englisch, 332 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 1490 g

Reihe: Advances in Industrial Control

"Advanced Control of Industrial Processes" presents the concepts and algorithms of advanced industrial process control and on-line optimisation within the framework of a multilayer structure. Relatively simple unconstrained nonlinear fuzzy control algorithms and linear predictive control laws are covered, as are more involved constrained and nonlinear model predictive control (MPC) algorithms and on-line set-point optimisation techniques.

Major topics and key features include: Derivation of practical MPC algorithms with linear process models; Development of computationally effective MPC structures for nonlinear process models, utilising on-line model linearisations and fuzzy reasoning; General presentation of the subject of on-line set-point improvement and optimisation; Complete theoretical stability analysis of fuzzy Takagi-Sugeno control systems; Illustration of the methodologies and algorithms by worked examples in the text and by results of simulations based on industrial process models.

Zielgruppe

Research

Autoren/Hrsg.

Tatjewski, Piotr

Fachgebiete

• Mathematik | Informatik Mathematik Operations Research Spieltheorie
• Mathematik | Informatik Mathematik Mathematische Analysis Variationsrechnung
• Technische Wissenschaften Technik Allgemein Mess- und Automatisierungstechnik
• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Verfahrenstechnik, Chemieingenieurwesen
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik Fertigungstechnik

Inhaltsverzeichnis

Multilayer Control Structure.- Model-based Fuzzy Control.- Model-based Predictive Control.- Set-point Optimization.

Über Autor(innen)

Professor Piotr Tatjewski graduated in control engineering from Warsaw University of Technology, Poland in 1972. He obtained his Ph.D. in 1976, and his D.Sc. in 1988, both in control engineering. The first period of his academic career was spent in the group of professor Wladyslaw Findeisen, working on control and optimisation of complex processes, on projects for process industry and concerning water distribution networks. In 1986 he was given a SERC fellowship for research on on-line set-point optimisation and spent 6 months as a research fellow of the Control Engineering Center of The City University London. Since 1990 he has been head of the Process Control Group at the Institute of Control and Computation Engineering, Warsaw University of Technology, leading many research and application projects (including that on advanced control for the Polish Petroleum Company). Professor Tatjewski spent the academic year 1992/1993 at the University of Birmingham in a project supported by the EU TEMPUS program. In 1993 he took up a professorship at Warsaw University of Technology and in 1996 the directorship of the Institute of Control and Computation Engineering there. In 2004 he was elected a member of the Committee of Automation and Robotics of the Polish Academy of Sciences. He works for the Ministry of Education and Science as an expert on standards in university education.

An experienced researcher and teacher, Professor Tatjewski has published 4 books (two in English) and over 20 journal papers as author or co-author and participated in numerous international conferences. He has taught many courses, including Feedback Control, Digital Feedback Control, Hierarchical Control and Optimisation, and Advanced Control. Between 1994 and 1997 he was the coordinator and contractor of the large EU project Information Technology for Control and Decision Support – Curriculum Development within the TEMPUS program, co-ordinating work in 4 major Polish technicaluniversities and 11 universities from EU countries (Germany, France, UK, Italy, Spain and Denmark). His main research interests are multilayer-multilevel process control and optimisation, fuzzy modelling and control, model predictive control of linear and nonlinear processes, soft computing methods, control and optimisation of large-scale processes.