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

Not published at VTT

Institute of Cryobiology and Food Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

10 Citations (Scopus)

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.

Original language	English
Title of host publication	2008 4th International IEEE Conference Intelligent Systems, IS 2008
Publisher	IEEE Institute of Electrical and Electronic Engineers
Pages	2013-2018
Volume	2
ISBN (Electronic)	978-1-4244-1740-7
ISBN (Print)	978-1-4244-1739-1
DOIs	https://doi.org/10.1109/IS.2008.4670467
Publication status	Published - 1 Dec 2008
MoE publication type	A4 Article in a conference publication
Event	2008 4th International IEEE Conference Intelligent Systems, IS 2008 - Varna, Bulgaria Duration: 6 Sept 2008 → 8 Sept 2008

Conference

Conference	2008 4th International IEEE Conference Intelligent Systems, IS 2008
Country/Territory	Bulgaria
City	Varna
Period	6/09/08 → 8/09/08

Keywords

Fuzzy-neural modeling
Lyophilization
Model predictive control

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10.1109/IS.2008.4670467

Cite this

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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.\}",

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

publisher = "IEEE Institute of Electrical and Electronic Engineers",

address = "United States",

note = "2008 4th International IEEE Conference Intelligent Systems, IS 2008 ; Conference date: 06-09-2008 Through 08-09-2008",

}

Todorov, YV & Tsvetkov, TD 2008, Volterra model predictive control of a lyophilization plant. in 2008 4th International IEEE Conference Intelligent Systems, IS 2008. vol. 2, 4670467, IEEE Institute of Electrical and Electronic Engineers, pp. 2013-2018, 2008 4th International IEEE Conference Intelligent Systems, IS 2008, Varna, Bulgaria, 6/09/08. https://doi.org/10.1109/IS.2008.4670467

Volterra model predictive control of a lyophilization plant. / Todorov, Yancho V.; Tsvetkov, Tsvetan D.
2008 4th International IEEE Conference Intelligent Systems, IS 2008. Vol. 2 IEEE Institute of Electrical and Electronic Engineers, 2008. p. 2013-2018 4670467.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Volterra model predictive control of a lyophilization plant

AU - Todorov, Yancho V.

AU - Tsvetkov, Tsvetan D.

PY - 2008/12/1

Y1 - 2008/12/1

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 - 978-1-4244-1739-1

VL - 2

SP - 2013

EP - 2018

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

PB - IEEE Institute of Electrical and Electronic Engineers

T2 - 2008 4th International IEEE Conference Intelligent Systems, IS 2008

Y2 - 6 September 2008 through 8 September 2008

ER -

Volterra model predictive control of a lyophilization plant

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Keywords

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