| Titre : | Advanced control of industrial processes | | Type de document : | document électronique | | Auteurs : | Tatjewski, Piotr, Auteur | | Editeur : | Berlin : Springer | | Année de publication : | 2007 | | Collection : | Advances in Industrial Control* | | ISBN/ISSN/EAN : | 978-1-84628-635-3 | | Langues : | Anglais (eng) | | Mots-clés : | Industrial engineering Control Engineering Calculus of Variations and Optimal Control | | Index. décimale : | 65 Gestion et organisation de l'industrie, du commerce et de la communication | | Résumé : | 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.
The major topics and key features are:
• Development and discussion of a multilayer control structure with interrelated direct control, set-point control and optimisation layers, as a framework for the subject of the book.
• Systematic presentation and stability analysis of fuzzy feedback control algorithms in Takagi-Sugeno structures for state-space and input-output models, in discrete and continuous time, presented as natural generalisations of well-known practical linear control laws (like the PID law) to the nonlinear case.
• Thorough derivation of most practical MPC algorithms with linear process models (dynamic matrix control, generalised predictive control, and with state-space models), both as fast explicit control laws (also embedded into appropriate structures to cope with process input constraints), and as more involved numerical constrained MPC algorithms.
• 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, together with iterative algorithms capable of coping with uncertainty in process models and disturbance estimates.
• Complete theoretical stability analysis of fuzzy Takagi-Sugeno control systems, discussion of stability and feasibility issues of MPC algorithms as well as of tuning aspects, discussion of applicability and convergence of on-line set-point improvement algorithms.
• Thorough illustration of the methodologies and algorithms by worked examples in the text.
• Control and set-point optimisation algorithms together with results of simulations based on industrial process models, stemming primarily from the petrochemical and chemical industries.
Starting from important and well-known techniques (supplemented with the original work of the author), the book includes recent research results mainly concerned with nonlinear advanced feedback control and set-point optimisation. It is addressed to readers interested in the important basic mechanisms of advanced control, including engineers and practitioners, as well as to research staff and postgraduate students. |
Advanced control of industrial processes [document électronique] / Tatjewski, Piotr, Auteur . - Springer, 2007. - ( Advances in Industrial Control*) . ISBN : 978-1-84628-635-3 Langues : Anglais ( eng) | Mots-clés : | Industrial engineering Control Engineering Calculus of Variations and Optimal Control | | Index. décimale : | 65 Gestion et organisation de l'industrie, du commerce et de la communication | | Résumé : | 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.
The major topics and key features are:
• Development and discussion of a multilayer control structure with interrelated direct control, set-point control and optimisation layers, as a framework for the subject of the book.
• Systematic presentation and stability analysis of fuzzy feedback control algorithms in Takagi-Sugeno structures for state-space and input-output models, in discrete and continuous time, presented as natural generalisations of well-known practical linear control laws (like the PID law) to the nonlinear case.
• Thorough derivation of most practical MPC algorithms with linear process models (dynamic matrix control, generalised predictive control, and with state-space models), both as fast explicit control laws (also embedded into appropriate structures to cope with process input constraints), and as more involved numerical constrained MPC algorithms.
• 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, together with iterative algorithms capable of coping with uncertainty in process models and disturbance estimates.
• Complete theoretical stability analysis of fuzzy Takagi-Sugeno control systems, discussion of stability and feasibility issues of MPC algorithms as well as of tuning aspects, discussion of applicability and convergence of on-line set-point improvement algorithms.
• Thorough illustration of the methodologies and algorithms by worked examples in the text.
• Control and set-point optimisation algorithms together with results of simulations based on industrial process models, stemming primarily from the petrochemical and chemical industries.
Starting from important and well-known techniques (supplemented with the original work of the author), the book includes recent research results mainly concerned with nonlinear advanced feedback control and set-point optimisation. It is addressed to readers interested in the important basic mechanisms of advanced control, including engineers and practitioners, as well as to research staff and postgraduate students. |
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