This item is printed on demand - it takes 3-4 days longer - Neuware -Moisture content (mc) within the cotton fibre is an important aspect for all stages of the ginning process. However due to the process dynamics, mc is currently being controlled by regulating the water and air temperatures from the Humidifiers. Human intervention and lack of consistence on set-points determination has resulted in inconsistent mc during humidification. This procedure requires a control system which will be able to adjust the process set-points automatically by eliminating the need for human intervention. In this paper a robust Model Reference Adaptive Control (MRAC) system for a Samuel Jackson Humidifier is presented. This system improves upon the existing system by creating a closed loop controller with parameters that can be updated to change the response from reference model. The control parameters are then updated based on this error thus the parameters converge to ideal values that cause the plant response to match the response of the reference model. 116 pp. Englisch.

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T�tulo: Model Reference Adaptive Fuzzy Control Systems for Automated Ginning
Editor: LAP LAMBERT Academic Publishing Nov 2014
Fecha de publicaci�n: 2014
Idioma: Ingl�s
ISBN 10: 3659556467
ISBN 13: 9783659556463
Encuadernaci�n: Taschenbuch
Estado: Neu

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Sinopsis

Moisture content (mc) within the cotton fibre is an important aspect for all stages of the ginning process. However due to the process dynamics, mc is currently being controlled by regulating the water and air temperatures from the Humidifiers. Human intervention and lack of consistence on set-points determination has resulted in inconsistent mc during humidification. This procedure requires a control system which will be able to adjust the process set-points automatically by eliminating the need for human intervention. In this paper a robust Model Reference Adaptive Control (MRAC) system for a Samuel Jackson Humidifier is presented. This system improves upon the existing system by creating a closed loop controller with parameters that can be updated to change the response from reference model. The control parameters are then updated based on this error thus the parameters converge to ideal values that cause the plant response to match the response of the reference model.

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BuchWeltWeit Ludwig Meier e.K.
Germany

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