Volterra model predictive control of a lyophilization plant

Yancho V. Todorov; Tsvetan D. Tsvetkov

doi:10.1109/IS.2008.4670467

Volterra model predictive control of a lyophilization plant

Yancho V. Todorov
, Tsvetan D. Tsvetkov

Ei julkaistu Aalto-yliopiston affiliaatiolla

Institute of Cryobiology and Food Technologies Sofia

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference article in proceedings › Scientific › vertaisarvioitu

10 Sitaatiot (Scopus)

Abstrakti

Lyophilization plants are widely used by pharmaceutical industries to produce stable dried medications and important preparations. Since, a Lyophilization cycle involves a high energy demands it is needed to be used an improved control strategy in order to minimize the operating costs. This paper describes a method for designing a nonlinear model predictive controller to be used in a Lyophilization plant. The controller is based on a truncated fuzzy-neural Volterra predictive model and a simplified gradient optimization algorithm. The proposed approach is studied to control the product temperature in a Lyophilization plant. The efficiency of the proposed approach is tested and proved by simulation experiments.

Alkuperäiskieli	Englanti
Otsikko	2008 4th International IEEE Conference Intelligent Systems, IS 2008
Kustantaja	IEEE
Sivut	2013-2018
Sivumäärä	6
Vuosikerta	2
ISBN (painettu)	9781424417391
DOI - pysyväislinkit	https://doi.org/10.1109/IS.2008.4670467
Tila	Julkaistu - 2008
OKM-julkaisutyyppi	A4 Artikkeli konferenssijulkaisussa
Tapahtuma	IEEE International Conference on Intelligent Systems - Varna, Bulgaria Kesto: 6 syysk. 2008 → 8 syysk. 2008 Konferenssinumero: 4

Conference

Conference	IEEE International Conference on Intelligent Systems
Lyhennettä	IS
Maa/Alue	Bulgaria
Kaupunki	Varna
Ajanjakso	06/09/2008 → 08/09/2008

Pääsy asiakirjaan

10.1109/IS.2008.4670467

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@inproceedings{f8e0fca9d22741a7a875828759915455,

title = "Volterra model predictive control of a lyophilization plant",

abstract = "Lyophilization plants are widely used by pharmaceutical industries to produce stable dried medications and important preparations. Since, a Lyophilization cycle involves a high energy demands it is needed to be used an improved control strategy in order to minimize the operating costs. This paper describes a method for designing a nonlinear model predictive controller to be used in a Lyophilization plant. The controller is based on a truncated fuzzy-neural Volterra predictive model and a simplified gradient optimization algorithm. The proposed approach is studied to control the product temperature in a Lyophilization plant. The efficiency of the proposed approach is tested and proved by simulation experiments.",

keywords = "Fuzzy-neural modeling, Lyophilization, Model predictive control",

author = "Todorov, \{Yancho V.\} and Tsvetkov, \{Tsvetan D.\}",

year = "2008",

doi = "10.1109/IS.2008.4670467",

language = "English",

isbn = "9781424417391",

volume = "2",

pages = "2013--2018",

booktitle = "2008 4th International IEEE Conference Intelligent Systems, IS 2008",

publisher = "IEEE",

address = "United States",

note = "IEEE International Conference on Intelligent Systems, IS ; Conference date: 06-09-2008 Through 08-09-2008",

}

TY - GEN

T1 - Volterra model predictive control of a lyophilization plant

AU - Todorov, Yancho V.

AU - Tsvetkov, Tsvetan D.

N1 - Conference code: 4

PY - 2008

Y1 - 2008

N2 - Lyophilization plants are widely used by pharmaceutical industries to produce stable dried medications and important preparations. Since, a Lyophilization cycle involves a high energy demands it is needed to be used an improved control strategy in order to minimize the operating costs. This paper describes a method for designing a nonlinear model predictive controller to be used in a Lyophilization plant. The controller is based on a truncated fuzzy-neural Volterra predictive model and a simplified gradient optimization algorithm. The proposed approach is studied to control the product temperature in a Lyophilization plant. The efficiency of the proposed approach is tested and proved by simulation experiments.

AB - Lyophilization plants are widely used by pharmaceutical industries to produce stable dried medications and important preparations. Since, a Lyophilization cycle involves a high energy demands it is needed to be used an improved control strategy in order to minimize the operating costs. This paper describes a method for designing a nonlinear model predictive controller to be used in a Lyophilization plant. The controller is based on a truncated fuzzy-neural Volterra predictive model and a simplified gradient optimization algorithm. The proposed approach is studied to control the product temperature in a Lyophilization plant. The efficiency of the proposed approach is tested and proved by simulation experiments.

KW - Fuzzy-neural modeling

KW - Lyophilization

KW - Model predictive control

UR - https://www.scopus.com/pages/publications/78650444584

U2 - 10.1109/IS.2008.4670467

DO - 10.1109/IS.2008.4670467

M3 - Conference article in proceedings

AN - SCOPUS:78650444584

SN - 9781424417391

VL - 2

SP - 2013

EP - 2018

BT - 2008 4th International IEEE Conference Intelligent Systems, IS 2008

PB - IEEE

T2 - IEEE International Conference on Intelligent Systems

Y2 - 6 September 2008 through 8 September 2008

ER -

Volterra model predictive control of a lyophilization plant

Abstrakti

Conference

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