Predictive Functional Control
Principles and Industrial Applications
(Sprache: Englisch)
The last forty years have seen thousands of successful industrial applications of Predictive Functional Control controllers. This text offers a fundamental understanding of the principles of PFCs as well as numerous examples of industrial applications.
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The last forty years have seen thousands of successful industrial applications of Predictive Functional Control controllers. This text offers a fundamental understanding of the principles of PFCs as well as numerous examples of industrial applications.
Klappentext zu „Predictive Functional Control “
first industrial application of MPC was in 1973. A key motivation was to provide better performance than could be obtained with the widely-used PID controller whilst making it easy to replace the PID controller unit or module with his new algorithm. It was the advent of digital control technology and the use of software control algorithms that made this replacement easier and more acceptable to process engineers. A decade of industrial practice with PFC was reported in the archival literature by Jacques Richalet et al. in 1978 in an important seminal Automatica paper. Around this time, Cutler and Ramaker published the dynamic matrix control algorithm that also used knowledge of future reference signals to determine a sequence of control signal adjustment. Thus, the theoretical and practical development of predictive control methods was underway and subsequent developments included those of generalized predictive control, and the whole armoury of MPC methods. Jacques Richalet's approach to PFC was to seek an algorithm that was: - easy to understand; - easy to install; - easy to tune and optimise. He sought a new modular control algorithm that could be readily used by the control-technician engineer or the control-instrument engineer. It goes without saying that this objective also forms a good market strategy.
Inhaltsverzeichnis zu „Predictive Functional Control “
Why Predictive Control?.- Internal Model.- Reference Trajectory.- Control Computation.- Tuning.- Constraints.- Industrial Implementation.- Parametric Control.- Unstable Poles and Zeros.- Industrial Examples.- Conclusions.
Autoren-Porträt von Jacques Richalet, Donal O'Donovan
Jaques Richalet was born in Versailles, France, in 1936. He studied aeronautical engineering at ENSAE in Paris and graduated in 1960. He then went to Berkeley, USA, where he obtained his MSc degree under the guidance of Prof. Zadeh. Back in Paris he worked in the field of applied mathematics and received his PhD in 1965.
His interest in model-based predictive control started as early as 1968. In the same year he founded the process engineering consulting company ADERSA with a major breakthrough being the first commissioned application of model based predictive control to a binary distillation column in 1973.
Since then he has been active in the areas of process identification, modelling and diagnosis methods such as predictive maintenance. Applications range from petrochemical and food industry to faster systems as encountered in the automotive and defense sector.
He was a manager of ADERSA till 2001 and is still working as a consultant for modelling and predictive control. He now lives in Versailles in France.
In his academic career he published more than fifty articles as well as three books on identification and predictive control. He has been president of the National Committee of Automatic Control and chairman of EEC Interest Group "CIDIC". For his achievements he was awarded the status as Chevalier de l'Ordre National du Merite and many researchers would probably agree to his being called "the grandfather of predictive control". He received the Nordic Process Control Award in 2007. He is now retired.
Bibliographische Angaben
- Autoren: Jacques Richalet , Donal O'Donovan
- 2013, Repr. 2009, XXII, 224 Seiten, Maße: 15,2 x 23,8 cm, Kartoniert (TB), Englisch
- Verlag: Springer, Berlin
- ISBN-10: 1849968454
- ISBN-13: 9781849968454
Sprache:
Englisch
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