Double Closed-Loop Controller Design of Brushless DC Torque Motor Based on RBF Neural Network

Abstract:

Article Preview

For the problem of that the traditional brushless DC torque motor controller position servo system is difficult to track accurately the complex and varied location information, an improved double closed-loop controller is designed in this paper. A self-adaptive PID algorithm based on RBF neural network is employed to design position loop controller and a feed-forward control algorithm is used in the speed loop controller. The improved double closed-loop controller validated the feasibility of the new method for the design of brushless DC torque motor position servo system

Info:

Periodical:

Advanced Materials Research (Volumes 503-504)

Edited by:

Wen-Pei Sung, Jimmy Chih-Ming Kao and Ran Chen

Pages:

1351-1356

Citation:

D. H. Li et al., "Double Closed-Loop Controller Design of Brushless DC Torque Motor Based on RBF Neural Network", Advanced Materials Research, Vols. 503-504, pp. 1351-1356, 2012

Online since:

April 2012

Export:

Price:

$38.00

[1] Zhi Huang, Hong Guo, Dayu Wang, Jinquan Yu. The simulation of double closed-loop brushless DC torque motor controller. Beijing University of Aeronautics and Astronautics. Vol. 37 (2011), pp.72-75.

[2] Yanhe Gao. Optimization and application of RBF neural network based hybrid hierarchy genetic algorithm. Sichuan University. (2004) , pp.7-14.

[3] Shaoming Li, Wei Zhao. Simulation of PID controller based RBF neural network about S-function. Journal of anhui vocational college of metallurgy and technology. Vol. 18 (2008), pp.19-21.

[4] Changliang Xia. Brushless DC motor control system. Beijing: Science Press. 2009, pp.25-53.

[5] Xiaoqing Zhou. Design and implement of electric actuator control system of high-speed unmanned aerial vehicle. Zhejiang University . Vol. 8(2010), pp.11-38.