@inproceedings{47b3e40bc58643c0999de8b1f6ff0016,
title = "The fuzzy controller design for MEMS gyro stable platform",
abstract = "Since a high sensor noise level will limit the gain of a PID controller, an adaptive Kalman filter (KF) has been designed to reduce the noise of MEMS gyro in a stable platform system, which has better performance than a FIR filters, Such as smaller phase lag and lower variance. By using the filtered gyro signal, a T-S fuzzy reasoning module has been constructed to adjust the PID coefficients adaptively. The simulation illustrates that the fuzzy-PID performs better than a classic PID when conquering the disturbance torque acting on platform frame.",
keywords = "Fuzzy control, Kalman filter, MEMS gyroscope, Stable platform",
author = "Jinlong Dong and Bo Mo",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2014.; 8th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2013 ; Conference date: 20-11-2013 Through 23-11-2013",
year = "2014",
doi = "10.1007/978-3-642-54927-4\_52",
language = "English",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "549--556",
editor = "Zhenkun Wen and Tianrui Li",
booktitle = "Practical Applications of Intelligent Systems - Proceedings of the 8th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2013",
address = "Germany",
}