Title :
Volterra model predictive control of a lyophilization plant
Author :
Todorov, Yancho V. ; Tsvetkov, Tsvetan D.
Author_Institution :
Inst. of Cryobiology & Food Technol., Sofia
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 :
control system synthesis; fuzzy control; gradient methods; neurocontrollers; nonlinear control systems; pharmaceutical industry; predictive control; temperature control; Lyophilization plant; Volterra model predictive control; gradient optimization algorithm; nonlinear model predictive controller design; pharmaceutical industries; product temperature control; stable dried medications; truncated fuzzy-neural Volterra predictive model; Artificial neural networks; Fuzzy logic; Intelligent systems; Kernel; Nonlinear systems; Optimal control; Pharmaceuticals; Predictive control; Predictive models; Temperature control; Fuzzy-Neural Modeling; Lyophilization; Model Predictive Control;
Conference_Titel :
Intelligent Systems, 2008. IS '08. 4th International IEEE Conference
Conference_Location :
Varna
Print_ISBN :
978-1-4244-1739-1
Electronic_ISBN :
978-1-4244-1740-7
DOI :
10.1109/IS.2008.4670467
