This paper proposes a self-excited induction generator model with saturation effect for power generating mode in a remote site. The model is led through the space vector mathematical formalism and allows one to analyze the steady and dynamic states. It is developed for a squirrel cage induction machine. This model provides magnetizing inductance variation able to influence the build-up and the stabilization of voltage generation when the load changes. The final result is a realistic approach model which takes into con- sideration the dependency of the magnetizing inductance versus magnetizing current. This novel model is validated through experimental measurements to demonstrate its validity and practicability.

To reduce the random error of microelectromechanical system (MEMS) gyroscope, a hybrid method combining improved empirical mode decomposition (EMD) and least squares algorithm (LS) is proposed. Firstly, based on the multiple screening mechanism, intrinsic mode functions (IMFs) from the first decomposition are divided into noise IMFs, strong noise mixed IMFs, weak noise mixed IMFs and signal IMFs. Secondly, according to their characteristics, they are processed again. IMFs from the second decomposition are divided into noise IMFs and signal IMFs. Finally, useful signal is gathered to obtain the final denoising signal. Compared with some other denoising methods proposed in recent years, the experimental results show that the proposed method has obvious advantages in suppressing random error, greatly improving the signal quality and improving the accuracy of inertial navigation.