Adaptive Fuzzy Kalman Filter Applied for Identification of Rotor/Active Magnetic Bearing Dynamics

2013 ◽  
Author(s):  
Yu-Hsun Liu ◽  
Nan-Chyuan Tsai ◽  
Hsin-Lin Chiu
Keyword(s):  
Kalman Filter ◽  
Magnetic Bearing ◽  
Active Magnetic Bearing ◽  
Adaptive Fuzzy ◽  
Bearing Dynamics

Intelligent Kalman Filtering for Fault Detection on an Active Magnetic Bearing System

2008 ◽  
Author(s):  
Nana K. Noel ◽  
Kari Tammi ◽  
Gregory D. Buckner ◽  
Nathan S. Gibson
Keyword(s):  
Neural Network ◽  
Kalman Filter ◽  
Fault Detection ◽  
Magnetic Bearing ◽  
Active Magnetic Bearing ◽  
Estimation Accuracy ◽  
False Alarms ◽  
Single Input Single Output ◽  
Single Output ◽  
Modeling Uncertainties

One of the challenges of condition monitoring and fault detection is to develop techniques that are sufficiently sensitive to faults without triggering false alarms. In this paper we develop and experimentally demonstrate an intelligent approach for detecting faults in a single-input, single-output active magnetic bearing. This technique uses an augmented linear model of the plant dynamics together with a Kalman filter to estimate fault states. A neural network is introduced to enhance the estimation accuracy and eliminate false alarms. This approach is validated experimentally for two types of fabricated faults: changes in suspended mass and coil resistance. The Kalman filter alone is shown to be incapable of identifying all fault cases due to modeling uncertainties. When an artificial neural network is trained to compensate for these uncertainties, however, all fault conditions are identified uniquely.

Vibration Control of Active Magnetic Bearing using Kalman Filter

2018 ◽  
Vol 2018.67 (0) ◽  
pp. 112
Author(s):  
Kazushige Yoshino ◽  
Gan Chen ◽  
Isao Takami
Keyword(s):  
Kalman Filter ◽  
Vibration Control ◽  
Magnetic Bearing ◽  
Active Magnetic Bearing

Reducing Energy Consumption in Active Magnetic Bearings by a Nonlinear Variable Bias Controller

2012 ◽  
Author(s):  
Satoshi Ueno ◽  
M. Necip Sahinkaya
Keyword(s):  
Energy Savings ◽  
Magnetic Bearing ◽  
Bias Current ◽  
Active Magnetic Bearing ◽  
Current Controller ◽  
Wide Range ◽  
Bearing Force ◽  
Variable Bias ◽  
Bearing Dynamics ◽  
Magnetic Center

This paper presents a nonlinear variable bias controller for an active magnetic bearing (AMB). The nonlinear bearing force is analyzed theoretically and the control current for various bias current settings is derived from the nonlinear bearing equation. Then the power consumption is minimized to obtain the optimum bias current expression analytically. Results show that the optimum bias current can be calculated from the demand bearing force and the instantaneous rotor displacement. Moreover, the influences of magnetic bearing parameter errors are investigated and correction methods are introduced. Results of experimental rotational tests show that the rotor dynamics are not altered under variable bias currents if the proposed correction for parameter errors is implemented. The magnetic center of misalignment is also detected and compensated for. The proposed variable bias current controller provides not only significant energy savings, but also it is simple to implement and applicable to wide range of magnetic bearing systems without deterioration of the bearing dynamics.

scholarly journals Application of the Dynamic Iterative Learning Control to the Heteroplanar Active Magnetic Bearing

2020 ◽  
Vol 53 (2) ◽  
pp. 1511-1516
Author(s):  
Lukasz Hladowski ◽  
Arkadiusz Mystkowski ◽  
Krzysztof Galkowski ◽  
Eric Rogers ◽  
Bing Chu
Keyword(s):  
Iterative Learning Control ◽  
Learning Control ◽  
Magnetic Bearing ◽  
Iterative Learning ◽  
Active Magnetic Bearing

Analysis of supercritical pitchfork bifurcation in active magnetic bearing-rotor system with current saturation

2021 ◽  
Vol 104 (1) ◽  
pp. 103-123
Author(s):  
Xiaoshen Zhang ◽  
Zhe Sun ◽  
Lei Zhao ◽  
Xunshi Yan ◽  
Jingjing Zhao ◽  
...  
Keyword(s):  
Pitchfork Bifurcation ◽  
Magnetic Bearing ◽  
Rotor System ◽  
Active Magnetic Bearing ◽  
Current Saturation

Data-Driven Self-sensing Technique for Active Magnetic Bearing

2021 ◽  
Author(s):  
Seong Jong Yoo ◽  
Sinyoung Kim ◽  
Kwang-Hwi Cho ◽  
Hyeong-Joon Ahn
Keyword(s):  
Magnetic Bearing ◽  
Active Magnetic Bearing ◽  
Data Driven
Sign in / Sign up

Export Citation Format

Share Document