Unscented Kalman Filtering for Self‐Sensing Magnetic Levitation against Magnetic Saturation
Unscented Kalman Filtering for Self‐Sensing Magnetic Levitation against Magnetic Saturation
This paper investigates the magnetic saturation problem of self‐sensing electromagnetic levitation system and presents a novel self‐sensing scheme. The proposed approach employs a demodulation technique. By superimposing a high‐frequency voltage, the resulting electromagnet coil currents have ripples that can be used for gap sensing. This paper shows that the gap length is not uniquely estimated when using only the relation between the ripple, the control currents, and the gap. The constraint conditions are to be determined to solve the problem. The proposed approach utilizes the dynamical motion model of the electromagnetic levitation system to uniquely identify the gap. Introducing the system behavior dynamics, the gap can be exactly estimated. To incorporate the system model with the gap sensing algorithm, a nonlinear filtering methodology is employed. The proposed estimator is demonstrated by the experiments. The results show that it is possible to address magnetic saturation with the proposed gap sensing scheme. The estimator has a good accuracy in a wider gap range compared to the conventional methods.
Document information
Unscented Kalman Filtering for Self‐Sensing Magnetic Levitation against Magnetic Saturation
Electrical engineering in Japan ; 196 , 4
2016
Article (Journal)
English
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