Evolutionary Algorithms

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Evolutionary algorithms have proven to be an enormously powerful and successful problem-solving strategy for optimisation problems. This book presents a novel application for implementing Evaluation Algorithm to tune Model Base Predictive Control (MBPC), MBPC systems require accurate models if high performance is to be attained. Most chemical processes are nonlinear in nature, which makes developing precise models challenging. Indeed, there are no procedures available for tuning MBPC that offer robust performance in the presence of model uncertainty. Using of Evolution Algorithms offer the opportunity of incorporating multiple objective functions to tune and optimise MBPC in term of H-two, H-infinity and LQC design. This resulted in increased stability robustness and the satisfaction of the performance objectives.

Autorentext

Dr Haitham Mohamed Osman Abdelghafar Osman is a Chemical engineer, with Master and PhD degrees in Process Control from University of Newcastle Upon Tyne, UK.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783844318548
    • Sprache Englisch
    • Genre Maschinenbau
    • Anzahl Seiten 160
    • Größe H220mm x B150mm x T11mm
    • Jahr 2011
    • EAN 9783844318548
    • Format Kartonierter Einband
    • ISBN 3844318542
    • Veröffentlichung 07.04.2011
    • Titel Evolutionary Algorithms
    • Autor Haitham Osman
    • Untertitel Tuning Model Base Predictive Control
    • Gewicht 256g
    • Herausgeber LAP LAMBERT Academic Publishing

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