%0 Electronic Article
%A Shi Kejian
%A Li Bin
%A Wang Feiming
%A Zhang Bin
%A Luo Wei
%A Deng Jiale
%K reliability
%K 550 kV GIS disconnector
%K radial basis function-based proportional-integral-derivative control method
%K servo following error
%K RBF neural network
%K RBF-PID control method
%K dynamic mathematical model
%K tracking control characteristics
%K voltage 550.0 kV
%K double-loop PID
%K velocity 0.1 m/s
%K gradient descent method
%K computational experiment methods
%K motor actuator
%K 550 kV gas-insulated switchgear
%K controllability
%K AC transmission system
%K control system
%K intelligent level
%K UHV GIS disconnector
%K RFB-PID control method
%X To improve the reliability and intelligent level of the AC transmission system, the radial basis function-based proportional-integral-derivative (RBF-PID) control method for the motor actuator used in the 550 kV gas-insulated switchgear (GIS) disconnector is proposed. According to the dynamic mathematical model of the motor actuator, the main structure of the RBF neural network based on the gradient descent method for learning algorithm is constructed. An identification function is formed by taking values of the output error square, and then by gathering information on the real-time tuning parameters of PID. Based on that, the simulation of the control system is constructed. The comparative analyses of the tracking control characteristics and the servo following error of the disconnector's contact speed between double-loop PID and RBF-PID are done through the computational and experiment methods, respectively. The results show that 550 kV GIS disconnector with the motor actuator by the RFB-PID control method has better controllability, and the servo following error is controlled within 0.1 m/s.
%T Research on the RBF-PID control method for the motor actuator used in a UHV GIS disconnector
%B The Journal of Engineering
%D October 2018
%I Institution of Engineering and Technology
%U https://digital-library.theiet.org/;jsessionid=1t9nc5tfk5lvl.x-iet-live-01content/journals/10.1049/joe.2018.8728
%G EN