Open AccessFault Detection of Areo-engine Actuator Based on Adaptive Radial Basic Function Observer
Author(s) -
Dingzhe Li,
Jingbo Peng,
Shuaiguo Li,
Weixuan Wang,
Ruosong Xu
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1550/4/042055
Subject(s) - control theory (sociology) , actuator , observer (physics) , computer science , fault detection and isolation , fault (geology) , nonlinear system , convergence (economics) , lyapunov function , control engineering , engineering , artificial intelligence , control (management) , physics , quantum mechanics , seismology , economic growth , economics , geology
Aiming at the fault detection problem of aero-engine actuators, a fault diagnosis method for aero-engine actuators based on adaptive RBF network observer is proposed. Firstly, the system model is established for the faulty actuator, and then the observer-based actuator fault diagnosis principle is established. Secondly, for the problem that the traditional observer is not sensitive to the gradual fault, the nonlinear approximation characteristics of the RBF network are used. The adaptive fault observer design method based on RBF network is applied. At the same time, the sufficient conditions for the convergence of the observer error system are given by using the Lyapunov stability analysis method. Finally, the simulation experiments of different types of actuators for a turbofan engine are carried out. The results show that the adaptive RBF observer designed in this paper is more effective in detecting faults and has certain fault estimation ability.