Parameter estimation of nonstationary power signals using an improved Gauss- Newton adaptive filter

In this paper a recursive adaptive filter based on a Gauss-Newton method has been proposed for the estimation of amplitude, phase, and frequency for time- signals in power networks. The presented algorithm is based on the minimization of a weighted forgetting factor based error cost function by the use of recursive Gauss-Newton method. Further a Hessian matrix approximation is used to produce a fast recursive algorithm, that is immune to random noise, waveform distortion and increases the speed of convergence and accuracy. The algorithm models the typical time-varying signal and the accompanied distortions due to harmonics and random noise in a manner that will be suitable for real-time parameter estimation of nonstationary signals in noise. Extensive digital simulations have been carried out to prove the validity of the proposed filter.