DocumentCode :
2970241
Title :
RBF-Neural Network Adaptive PID Control for 3-Axis Stabilized Tracking System
Author :
Zhi-Gang Liu
Author_Institution :
Beijing Institute of Technology, China
fYear :
2006
fDate :
Dec. 2006
Firstpage :
67
Lastpage :
67
Abstract :
The 3-axis stabilized tracking system is a vital part of the anti-aircraft system. To achieve the demand on swiftness, precision and stability, an adaptive PID control algorithm based on RBF-NN is introduced. In order to verify the feasibility of the method, several experiments were taken under the same conditions while using both the traditional PID and the adaptive RBF-NN PID. The steady state error is 0.003¿, and the maximum tracking error is 0.203¿ when the signal frequency is 0.1Hz and the amplitude is 20¿ .The results of experiments proved that the RBF-NN adaptive PID controller performs well in the actual 3-axis stabilized tracking control system.
Keywords :
3-axis stabilized tracking system; Adaptive control; RBF Neural Network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Hybrid Intelligent Systems, 2006. HIS '06. Sixth International Conference on
Conference_Location :
Rio de Janeiro, Brazil
Print_ISBN :
0-7695-2662-4
Type :
conf
DOI :
10.1109/HIS.2006.264950
Filename :
4041447
Link To Document :
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