DocumentCode :
3635035
Title :
Process model and implementation the multivariable model predictive control to ventilation system
Author :
Jozef Hrb?ek;Juraj Spalek;Vojtech ?im?k
Author_Institution :
Department of Control and Information Systems, Faculty of Electrical Engineering, University of ?ilina, Univerzitn? 8215/1, 010 26 ?ilina, Slovak Republic
fYear :
2010
Firstpage :
211
Lastpage :
214
Abstract :
Predictive control seems to be a promising approach that can help to improve properties of existing ventilation systems applied in road tunnels. Advantages of predictive control result mainly from its ability to solve both SISO and MIMO tasks, to have regard for dynamics of process changes in a broad extent, to compensate effect of measurable and non-measurable failures and to formulate the task as an optimization control task considering limiting conditions of control actions, changes of control actions and output variables. Data characterizing the existing ventilation system can be used to analyze and identify the system and create its models. Thereafter the predictive control of ventilation can be designed enabling to predict concentrations of pollutants and optimize system operation.
Keywords :
"Predictive models","Predictive control","Ventilation","Mathematical model","Roads","Stochastic resonance","Control system synthesis","Pollution measurement","White noise","Equations"
Publisher :
ieee
Conference_Titel :
Applied Machine Intelligence and Informatics (SAMI), 2010 IEEE 8th International Symposium on
Print_ISBN :
978-1-4244-6422-7
Type :
conf
DOI :
10.1109/SAMI.2010.5423738
Filename :
5423738
Link To Document :
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