Title :
Neural Network-Based Sensor Online Fault Diagnosis and Reconfiguration for Flight Control Systems
Author :
Liu, Xiaoxiong ; Zhang, Weiguo ; Huang, Yijun ; Wu, Yan
Author_Institution :
Coll. of Autom., Northwestern Polytech. Univ., Xi´´an
Abstract :
A scheme for sensor online fault diagnosis and reconfiguration was proposed. It was based on the radial basis function network (RBF) which was designed by efficient algorithm of on-line training and parameter optimization. Using multiple model adaptive technique, a set of adaptive neural network observers were designed to restrain modeling uncertainties and the output couple in flight control system. The performance of the scheme was validated by the nonlinear simulation for a fighter within automatic terrain following flight control system. As a conclusion, online accommodation is achieved
Keywords :
aerospace control; fault diagnosis; learning (artificial intelligence); neurocontrollers; observers; optimisation; radial basis function networks; sensors; adaptive neural network observers; flight control systems; online training; parameter optimization; radial basis function network; sensor online fault diagnosis; sensor online fault reconfiguration; Adaptive control; Adaptive systems; Aerospace control; Algorithm design and analysis; Design optimization; Fault diagnosis; Neural networks; Programmable control; Radial basis function networks; Sensor systems; Fault diagnosis and reconfiguration; RBF neural network; flight control system;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1714141