@inproceedings{f09f3e0ffdd94221bacb4185ebf72378,
title = "Fault detection and diagnosis for servo systems with backlash",
abstract = "This paper is concerned with the fault detection and diagnosis problem for the single motor servo systems. The continuous-time nonlinear servo system with disturbance, actuator fault and backlash is modeled. An observer based on radial basis function neural network is constructed to approximate the unknown backlash nonlinear, and a threshold is computed to detect the occurrence of fault. Then, another radial basis function neural network is provided to identify the fault information after a fault occurs. Finally, simulation results show the effectiveness and applicability of the proposed method.",
keywords = "Backlash, Fault detection and diagnosis, Neural network, Servo systems",
author = "Fumin Guo and Xuemei Ren",
note = "Publisher Copyright: {\textcopyright} 2018, Springer Nature Singapore Pte Ltd.; Chinese Intelligent Systems Conference, CISC 2017 ; Conference date: 14-10-2017 Through 15-10-2017",
year = "2018",
doi = "10.1007/978-981-10-6496-8\_43",
language = "English",
isbn = "9789811064951",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "461--469",
editor = "Junping Du and Weicun Zhang and Yingmin Jia",
booktitle = "Proceedings of 2017 Chinese Intelligent Systems Conference",
address = "Germany",
}