Fast tracking of transient power system signals using fuzzy LMS algorithm

The paper presents an adaptive least mean squares (LMS) algorithm for the fast estimation of voltage and current signals in power networks. The new estimator is based on the use of linear combiners. The learning parameter of the proposed algorithm is constrained by two variable parameters which causes an automatic suitable adjustment of the step size using a fuzzy gain scheduling method to provide fast convergence and noise rejection for the tracking of fundamental and harmonic components from distorted signals. Several numerical tests have been conducted for the adaptive estimation of fundamental and harmonic components from simulated waveforms from power networks supplying converter loads and switched capacitors.