GLSDC Based Parameter Estimation Algorithm for a PMSM Model

In this study, a GLSDC (Gaussian Least Squares Differential Correction) based parameter estimation algorithm is used to identify PMSM (Permanent Magnet Synchronous Motor) model. method, nonlinear model assumed be the correct representation of underlying state dynamics and output signals are measured in noisy environment. Using input signals, parameters that constitute coefficients signal terms estimated using transition matrix which computed by numerical means detailed. Since requires initial value, term also addition unknown whose bounds known, mostly case industrial applications. The batch iteratively estimate set before after convergence, recover filtered trajectories. A couple different scenarios tested simulations results addressed. Different methods discussed compute better values, shorten convergence time.