Javad Rezaie

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Interior permanent magnet synchronous motors (IPMSMs) are receiving increased attention for high performance drive applications because of their high power density, high efficiency and flux weakening capability. However, their high efficiency characteristic is influenced by applied control strategies. Thus much effort has been directed towards the(More)
In this paper, first an enhanced neuro-fuzzy method for modeling nonlinear system is presented In this method we use EM algorithm for identification of local models, which gain us model mismatch covariance. The achieved model can be stated in state space model as a linear time-varying system. As the noise and model mismatch covariance is known, Kalman(More)
The filtering problem, or dynamic data assimilation problem, is studied for linear and nonlinear systems with continuous state space and over discrete time steps. The paper presents filtering approaches based on the conjugate closed skew normal probability density. This distribution allows additional flexibility over the usual Gaussian approximations. With(More)
In this paper, first an enhanced NeuroFuzzy method for modeling nonlinear system is presented. In this method we use EM algorithm for identification of local models, which gain us model mismatch covariance. The achieved model can be stated in state space model as a linear time-varying system. As the noise and model mismatch covariace is known, Kalman filter(More)
State estimation in high dimensional systems remains a challenging part of real time analysis. The ensemble Kalman filter addresses this challenge by using Gaussian approximations constructed from a number of samples. This method has been a large success in many applications. Unfortunately, for some cases, Gaussian approximations are no longer valid and the(More)
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