Design of complex FIR filters with arbitrary magnitude and group delay responses

To design approximately linear-phase complex coefficient finite impulse response （FIR） digital filters with arbitrary magnitude and group delay responses, a novel neural network approach is studied. The approach is based on a batch back-propagation neural network algorithm by directly minimizing the real magnitude error and phase error from the linear-phase to obtain the filter＇s coefficients. The approach can deal with both the real and complex coefficient FIR digital filters design problems. The main advantage of the proposed design method is the significant reduction in the group delay error. The effectiveness of the proposed method is illustrated with two optimal design examples.

A Control Strategy of Frequency Self-adaptation Without Phase-locked Loop for VSC-HVDC

A control strategy of frequency self-adaptation without phase-locked loop(PLL)underαβstationary reference frame(αβ-SRF)for a VSC-HVDC system is presented to improve the operational performance of the system under severe harmonic distortion conditions.The control strategy helps to eliminate the cross-coupling under dq synchronous reference frame(dq-SRF),and is achieved through two key technologies:1)positive phase sequence(PPS)and negative phase sequence(NPS)fundamental components are extracted from the AC grid voltage with an improved multiple complex coefficient filter(IMCF),and 2)grid instantaneous frequency is rapidly and precisely tracked using a frequency self-adaptation tracking algorithm(FATA)without PLL.The proposed strategy is applied to a point-to-point VSCHVDC system and validated by means of simulations.The results are compared to those with the traditional vector control strategy under dq-SRF.Simulation results illustrate that the proposed strategy results in better system performance than that with the traditional strategy in terms of harmonic suppression under normal and severe operating conditions of the AC system.