Harmonics and Decaying DC Estimation Using Volterra LMS/F Algorithm

Correct estimation of harmonics and sequence components is essential to monitor the overall performance of three phase power systems. Least mean square (LMS) based adaptive models have simpler structures to estimate the required parameters for a given power quality (PQ) event. However, these models are not very much effective in case of time-varying and short duration disturbances. Least mean fourth (LMF) is comparatively a better approach than LMS to deal with different PQ problems, but high computational complexity limits the filter performance in case of practical applications. LMS/fourth (LMS/F) filter is a compromise between LMS and LMF to improve the error convergence properties. The proposed model explained in this paper is based on the concept of LMS/F with Volterra expansions of input samples. The proposed Volterrra LMS/F filter is tested in case of distorted power signals to estimate harmonics, decaying dc, and sequence components in presence of white Gaussian noise. The detail comparison results are presented using MATLAB simulations to verify the performance of the adaptive model.