@inproceedings{63f80e33d5f24f2c951860302d6560b4,
title = "RBF-neural network adaptive PID control for 3-axis stabilized tracking system",
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",
author = "Liu, \{Zhi Gang\} and Wang, \{Jun Zheng\}",
year = "2006",
doi = "10.1109/HIS.2006.264950",
language = "English",
isbn = "0769526624",
series = "Proceedings - Sixth International Conference on Hybrid Intelligent Systems and Fourth Conference on Neuro-Computing and Evolving Intelligence, HIS-NCEI 2006",
booktitle = "Proceedings - Sixth International Conference on Hybrid Intelligent Systems and Fourth Conference on Neuro-Computing and Evolving Intelligence, HIS-NCEI 2006",
note = "6th International Conference on Hybrid Intelligent Systems and 4th Conference on Neuro-Computing and Evolving Intelligence, HIS-NCEI 2006 ; Conference date: 13-12-2006 Through 15-12-2006",
}