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 | |
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