DocumentCode :
3043695
Title :
Centrifugal compressor surge control using nonlinear model predictive control based on LS-SVM
Author :
Wang, Chuanxin ; Shao, Cheng ; Han, Yu
Author_Institution :
Inst. of Adv. Control Technol., Dalian Univ. of Technol., Dalian, China
fYear :
2010
fDate :
8-10 June 2010
Firstpage :
466
Lastpage :
471
Abstract :
This paper reports a surge control strategy for centrifugal compressor using nonlinear model predictive control based on Lease-Squared Support Vector Machine(LS-SVM) in order to increase efficiency of centrifugal compressor. The MISO nonlinear predictive models of compressor´s discharge pressure and mass flow are developed by LS-SVM. In order to avoid surge, the conditions of anti-surge are chosen as the limiting conditions of the control objective and also the reference trajectory. The influence of actuator´s response time is reduced by predict the compressor´s input and output in advance. The operating point´s fluctuate is avoided by the control objective which let the difference of the adjacent control input be the minimum. Simulation and experiment results show that the proposed control strategy can decrease the distance between surge line and control line at the same time avoid surge effectively, so compressor´s efficiency is increased significantly.
Keywords :
actuators; compressors; least squares approximations; nonlinear control systems; predictive control; support vector machines; surge protection; LS-SVM; MISO nonlinear predictive model; actuator response time; adjacent control input; centrifugal compressor surge control; compressor discharge pressure; lease squared support vector machine; mass flow; nonlinear model predictive control; Discharges; Predictive control; Predictive models; Surges; Time domain analysis; Time factors; Trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems and Control in Aeronautics and Astronautics (ISSCAA), 2010 3rd International Symposium on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-6043-4
Electronic_ISBN :
978-1-4244-7505-6
Type :
conf
DOI :
10.1109/ISSCAA.2010.5633206
Filename :
5633206
Link To Document :
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