Abstract
To acquire a satisfied accelerometer dynamic compensation effect, the accelerometer model should be with high precision using the traditional method of zero-pole assignment (ZPS). But in the accelerometer output, the noises, the drift error and the disturbances of the system which make the low precision of the built accelerometer model, can not be avoidable. In this paper, an accelerometer dynamic compensation method based on CMAC neural network is proposed. In this method, a dynamic compensation model can be set up according to the measurement data of dynamic response of the accelerometer without knowing its dynamic model. The dynamic compensation model parameters are trained by CMAC neural network. To a kind of micro-silicon piezoresistance accelerometer, the simulation results show that the proposed new dynamic compensation method has the advantages of fast training process, high precision and easy realization of the dynamic compensation device.
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