NDLI: Predictive control of drum water level based on ant colony optimization algorithm

Content Provider	IEEE Xplore Digital Library
Author	Sun Lingfang Li Jichang Zhao Xue
Copyright Year	2010
Description	Author affiliation: School of Automation Engineering, Northeast Dianli University, Jilin, 132012, China (Sun Lingfang; Li Jichang; Zhao Xue)
Abstract	Drum water level is one of the main control parameters for turbo-generator unit. It is significant for drum water level researching as its many influence factors and false water level easily to bring about. The predictive control based on ant colony optimization (ACO) is used for the control of drum water level in this paper. The SVM with RBF kernel is used for training regression vector in order to accomplish water level dynamic systems modeling. ACO used for continuous function optimization is established. And the optimization of non-convex objective function is solved by the algorithm. Then the best control series can be obtained. From simulation results it shows that the algorithms have good control performance such as the rise time is 6*TS, overshoot is as small as 3.0192%, much small steady-state error and so on.
Starting Page	3111
Ending Page	3115
File Size	418048
Page Count	5
File Format	PDF
ISBN	9781424462636
e-ISBN	9787894631046
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-29
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Chinese Association of Aut
Subject Keyword	Support vector machines Predictive Control Ant Colony Optimization Ant colony optimization Drum Water Level Artificial neural networks Predictive models Prediction algorithms SVM Optimization Predictive control
Content Type	Text
Resource Type	Article

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