Compounded Calibration Based on FNN and Attitude Estimation Method Using Intelligent Filtering for Low Cost MEMS Sensor Application
Micro electro mechanical system (MEMS) inertial sensors have advantages, including small size and low power consumption. The performances of Micro Inertial measurement unit (IMU), which is composed of MEMS inertial sensors, degrade, and error, will become larger in high dynamic environment. In order...
Main Authors: | Lei Wang, Ying Guan, Xuedong Hu |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2019-01-01
|
Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2019/4514873 |
Similar Items
-
Accelerated Adaptive Backstepping Control of the Chaotic MEMS Gyroscope by Using the Type-2 Sequential FNN
by: Le Zhao, et al.
Published: (2021-03-01) -
Attitude Determination Method by Fusing Single Antenna GPS and Low Cost MEMS Sensors Using Intelligent Kalman Filter Algorithm
by: Lei Wang, et al.
Published: (2017-01-01) -
Adaptive UAV Attitude Estimation Employing Unscented Kalman Filter, FOAM and Low-Cost MEMS Sensors
by: Carlos Santos, et al.
Published: (2012-07-01) -
An Observer-Based Adaptive Iterative Learning Control Using Filtered-FNN Design for Robotic Systems
by: Ying-Chung Wang, et al.
Published: (2014-02-01) -
Modeling the Thermal Performance of an Intelligent MEMS Pressure Sensor with Self-Calibration Capabilities
by: De Clerck, Albrey Paul
Published: (2020)