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Control system optimization of spillage brake based on RBF neural network
Author(s) -
An Xiaogang,
Zhu Weiwei,
An Na
Publication year - 2020
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.5588
Subject(s) - sluice , artificial neural network , pid controller , flood control , engineering , reliability (semiconductor) , closing (real estate) , automotive engineering , brake , control engineering , control system , power (physics) , computer science , flood myth , temperature control , electrical engineering , artificial intelligence , philosophy , physics , theology , archaeology , quantum mechanics , law , political science , history
Summary Aiming at the actual production needs of the Dadingzi mountain hydro‐junction, this paper studies the optimal control of the flood discharge system. From the angle of ensuring the opening and closing of the flood discharge gate, the control system of the sluice is designed reasonably, the intelligent control strategy is put forward, and the optimized RBF neural network based PID parameters are used to control the operating mode of the opening and closing machine in the flood sluice operation process, so as to further improve the reliability of the flood discharge gate. The proposed control approach of sluice gates provides a new control mode for the navigation and electric power junction.