ISSUES IN ON-LINE OPTIMIZATION - Mansour, Moufid;Ellis, Joe E.
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THIS BOOK ADDRESSES THE THEORETICAL AND PRACTICAL IMPLEMENTATION OF REAL-TIME OPTIMIZATION TECHNIQUES ON PROCESSES. IT IS SUPPOSED TO GIVE AN INSIGHT OF THE ISSUES FACED WITH WHEN OPTIMIZING A REAL PROCESSES WHILE IT IS WORKING. THE MAIN AIM IS TO FIND THE OPTIMUM OPERATING POINT OF A SYSTEM EVEN IF WE HAVE A LITTLE INFORMATION ABOUT IT, OR THAT THE MEASUREMENTS ARE FLAWED. THIS IS ACHIEVED BY STUDYING SPECIAL TECHNIQUES FOR REMOVING THE ERRORS PRESENT IN THE MEASUREMENTS, AND ADAPTIVE METHODS WITHIN THE OPTIMIZATION ROUTINE IN PARAMETER MODELS ARE UPDATED REGULARLY USING PARAMETER ESTIMATION.

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Produktbeschreibung
THIS BOOK ADDRESSES THE THEORETICAL AND PRACTICAL IMPLEMENTATION OF REAL-TIME OPTIMIZATION TECHNIQUES ON PROCESSES. IT IS SUPPOSED TO GIVE AN INSIGHT OF THE ISSUES FACED WITH WHEN OPTIMIZING A REAL PROCESSES WHILE IT IS WORKING. THE MAIN AIM IS TO FIND THE OPTIMUM OPERATING POINT OF A SYSTEM EVEN IF WE HAVE A LITTLE INFORMATION ABOUT IT, OR THAT THE MEASUREMENTS ARE FLAWED. THIS IS ACHIEVED BY STUDYING SPECIAL TECHNIQUES FOR REMOVING THE ERRORS PRESENT IN THE MEASUREMENTS, AND ADAPTIVE METHODS WITHIN THE OPTIMIZATION ROUTINE IN PARAMETER MODELS ARE UPDATED REGULARLY USING PARAMETER ESTIMATION.
Autorenporträt
Moufid Mansour obtained his PhD degree in 2004 from City University, London, UK. He is now a Senior Lecturer at the faculty of Electronics and Computer Science, USTHB, Algeria. His research interests include: Real-time Optimization, adaptive control, neural networks, data reconciliation and gross error detection and embedded systems.