RBF-neural network adaptive PID control for 3-axis stabilized tracking system

Zhi Gang Liu*, Jun Zheng Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings - Sixth International Conference on Hybrid Intelligent Systems and Fourth Conference on Neuro-Computing and Evolving Intelligence, HIS-NCEI 2006
DOIs
Publication statusPublished - 2006
Event6th International Conference on Hybrid Intelligent Systems and 4th Conference on Neuro-Computing and Evolving Intelligence, HIS-NCEI 2006 - Auckland, New Zealand
Duration: 13 Dec 200615 Dec 2006

Publication series

NameProceedings - Sixth International Conference on Hybrid Intelligent Systems and Fourth Conference on Neuro-Computing and Evolving Intelligence, HIS-NCEI 2006

Conference

Conference6th International Conference on Hybrid Intelligent Systems and 4th Conference on Neuro-Computing and Evolving Intelligence, HIS-NCEI 2006
Country/TerritoryNew Zealand
CityAuckland
Period13/12/0615/12/06

Keywords

  • 3-axis stabilized tracking system
  • Adaptive control
  • RBF neural network

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