NDLI: Application of BP neural network intelligent PID controller based on GA in electrode regulator systems of electric arc furnace

Content Provider	IEEE Xplore Digital Library
Author	Wang Hong-jun Li Yan-wei Yue You-jun
Copyright Year	2011
Description	Author affiliation: Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems, Tianjin University of Technology, Tianjin, China (Wang Hong-jun) \|\| School of Electrical Engineering, Tianjin, University of Technology, Tianjin, China (Li Yan-wei; Yue You-jun)
Abstract	Aimed at the characteristics of strong nonlinearity, uncertainty, time-variance and, strong coupling etc for AC electric arc furnace (EAF), and the traditional PID can not achieve desired control effect. The paper proposes a PID control algorithm based on optimized BP neural network using genetic algorithm, which is applied in electrode regulator systems of electric arc furnace to design the optimized controller. The algorithm optimizes the initial weights of BP neural network by using genetic algorithm firstly, and then adjusts the PID parameters by using BP neural network. The simulation indicates that the algorithm is feasible, and unit with intelligent PID controller has better accuracy and dynamic characteristics.
Starting Page	198
Ending Page	202
File Size	999842
Page Count	5
File Format	PDF
ISBN	9781612844855
e-ISBN	9781612844862
DOI	10.1109/ICCSN.2011.6014422
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-27
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electrodes Algorithm design and analysis genetic algorithm electrode BP neural network Furnaces Heuristic algorithms PID control Optimization Tuning Genetic algorithms
Content Type	Text
Resource Type	Article

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