Title :
An approach of Eddy current sensor calibration in state estimation for maglev system
Author :
Zhang, He-sheng ; Cao, Xun-kai ; Guo, Bin ; Wang, Qiang ; Fu, Yue-hui
Author_Institution :
Beijing Jiaotong Univ., Beijing
Abstract :
Eddy current sensors are used in state estimation of the maglev system. However, the input output characteristic of the eddy current sensor is nonlinear and cannot be fit for the precision and time limit of the control system. So the radial basis function (RBF) neural network is used to construct the inverse model of the eddy current sensor. The simplified adaptive algorithm for hidden layer structure and center value can quickly and accurately compute the structure and parameter of RBF network. And the eddy current sensor is calibrated. In the practical measurement, the method can satisfy the requirement of the control system. The calibration error is less than 0.7% and the linear range is extended.
Keywords :
calibration; eddy currents; magnetic levitation; magnetic sensors; power engineering computing; radial basis function networks; state estimation; RBF neural network; adaptive algorithm; control system; eddy current sensor calibration; hidden layer structure; maglev system; radial basis function; state estimation; Calibration; Control systems; Eddy currents; Inverse problems; Magnetic levitation; Neural networks; Nonlinear control systems; Sensor phenomena and characterization; Sensor systems; State estimation;
Conference_Titel :
Electrical Machines and Systems, 2007. ICEMS. International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-89-86510-07-2
Electronic_ISBN :
978-89-86510-07-2
