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Design of an Intelligent Control System for Conveyor-Belt Grain Dryers: An Application of Soft Computing Techniques in Grain Drying Systems - Tapa blanda

 
9783846584941: Design of an Intelligent Control System for Conveyor-Belt Grain Dryers: An Application of Soft Computing Techniques in Grain Drying Systems

Sinopsis

The major objective of this research is to improve the performance of conveyor-belt grain dryers by designing an intelligent control system utilizing the capabilities of the adaptive neuro-fuzzy inference system (ANFIS) to model and control the drying process. To achieve this objective, a laboratory-scale conveyor-belt grain dryer was specifically fabricated for this study. As the main controller in this work, a simplified ANFIS structure is proposed to act as a proportional-integral-derivative (PID)-like feedback controller to control nonlinear systems. This controller has several advantages over its conventional ANFIS counterpart, particularly the reduction in processing time. Moreover, three evolutionary algorithms (EAs), in particular a real-coded genetic algorithm (GA), a particle swarm optimization (PSO), and a global-best harmony search (GHS), were separately used to train the proposed controller and to determine its scaling factors. The simplified ANFIS controller was then applied to control the developed ANFIS-based dryer model. From all the simulation tests, the simplified ANFIS controller has proved its remarkable ability in controlling the grain drying process.

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Reseña del editor

The major objective of this research is to improve the performance of conveyor-belt grain dryers by designing an intelligent control system utilizing the capabilities of the adaptive neuro-fuzzy inference system (ANFIS) to model and control the drying process. To achieve this objective, a laboratory-scale conveyor-belt grain dryer was specifically fabricated for this study. As the main controller in this work, a simplified ANFIS structure is proposed to act as a proportional-integral-derivative (PID)-like feedback controller to control nonlinear systems. This controller has several advantages over its conventional ANFIS counterpart, particularly the reduction in processing time. Moreover, three evolutionary algorithms (EAs), in particular a real-coded genetic algorithm (GA), a particle swarm optimization (PSO), and a global-best harmony search (GHS), were separately used to train the proposed controller and to determine its scaling factors. The simplified ANFIS controller was then applied to control the developed ANFIS-based dryer model. From all the simulation tests, the simplified ANFIS controller has proved its remarkable ability in controlling the grain drying process.

Biografía del autor

Omar F. Lutfy was born in Baghdad, Iraq in 1977. He received the B.Sc. degree in Computers Engineering from the Control and Systems Engineering Department, University of Technology, Baghdad-Iraq in 2000. In 2002, he obtained his M.Sc. degree in Mechatronics Engineering. In 2011, he received the Ph.D degree from Universiti Putra Malaysia (UPM).

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Omar F. Lutfy|Samsul Bahari B. M. Noor|Mohammad H. Marhaban
Publicado por LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3846584940 ISBN 13: 9783846584941
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: F. Lutfy OmarOmar F. Lutfy was born in Baghdad, Iraq in 1977. He received the B.Sc. degree in Computers Engineering from the Control and Systems Engineering Department, University of Technology, Baghdad-Iraq in 2000. In 2002, he obta. Nº de ref. del artículo: 5501343

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Omar F. Lutfy
ISBN 10: 3846584940 ISBN 13: 9783846584941
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The major objective of this research is to improve the performance of conveyor-belt grain dryers by designing an intelligent control system utilizing the capabilities of the adaptive neuro-fuzzy inference system (ANFIS) to model and control the drying process. To achieve this objective, a laboratory-scale conveyor-belt grain dryer was specifically fabricated for this study. As the main controller in this work, a simplified ANFIS structure is proposed to act as a proportional-integral-derivative (PID)-like feedback controller to control nonlinear systems. This controller has several advantages over its conventional ANFIS counterpart, particularly the reduction in processing time. Moreover, three evolutionary algorithms (EAs), in particular a real-coded genetic algorithm (GA), a particle swarm optimization (PSO), and a global-best harmony search (GHS), were separately used to train the proposed controller and to determine its scaling factors. The simplified ANFIS controller was then applied to control the developed ANFIS-based dryer model. From all the simulation tests, the simplified ANFIS controller has proved its remarkable ability in controlling the grain drying process. 244 pp. Englisch. Nº de ref. del artículo: 9783846584941

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Omar F. Lutfy
Publicado por LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3846584940 ISBN 13: 9783846584941
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The major objective of this research is to improve the performance of conveyor-belt grain dryers by designing an intelligent control system utilizing the capabilities of the adaptive neuro-fuzzy inference system (ANFIS) to model and control the drying process. To achieve this objective, a laboratory-scale conveyor-belt grain dryer was specifically fabricated for this study. As the main controller in this work, a simplified ANFIS structure is proposed to act as a proportional-integral-derivative (PID)-like feedback controller to control nonlinear systems. This controller has several advantages over its conventional ANFIS counterpart, particularly the reduction in processing time. Moreover, three evolutionary algorithms (EAs), in particular a real-coded genetic algorithm (GA), a particle swarm optimization (PSO), and a global-best harmony search (GHS), were separately used to train the proposed controller and to determine its scaling factors. The simplified ANFIS controller was then applied to control the developed ANFIS-based dryer model. From all the simulation tests, the simplified ANFIS controller has proved its remarkable ability in controlling the grain drying process. Nº de ref. del artículo: 9783846584941

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Omar F. Lutfy
ISBN 10: 3846584940 ISBN 13: 9783846584941
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Taschenbuch. Condición: Neu. Neuware -The major objective of this research is to improve the performance of conveyor-belt grain dryers by designing an intelligent control system utilizing the capabilities of the adaptive neuro-fuzzy inference system (ANFIS) to model and control the drying process. To achieve this objective, a laboratory-scale conveyor-belt grain dryer was specifically fabricated for this study. As the main controller in this work, a simplified ANFIS structure is proposed to act as a proportional-integral-derivative (PID)-like feedback controller to control nonlinear systems. This controller has several advantages over its conventional ANFIS counterpart, particularly the reduction in processing time. Moreover, three evolutionary algorithms (EAs), in particular a real-coded genetic algorithm (GA), a particle swarm optimization (PSO), and a global-best harmony search (GHS), were separately used to train the proposed controller and to determine its scaling factors. The simplified ANFIS controller was then applied to control the developed ANFIS-based dryer model. From all the simulation tests, the simplified ANFIS controller has proved its remarkable ability in controlling the grain drying process.Books on Demand GmbH, Überseering 33, 22297 Hamburg 244 pp. Englisch. Nº de ref. del artículo: 9783846584941

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Omar F. Lutfy Samsul Bahari B. M. Noor Mohammad H. Marhaban
Publicado por Editorial Academica Espanola, 2012
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F. Lutfy Omar B. M. Noor Samsul Bahari H. Marhaban Mohammad
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F. Lutfy, Omar, B. M. Noor, Samsul Bahari, H. Marhaban, Moha
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