ArticleAbstract-We address the problem of frequency-selective channel estimation and symbol detection using superimposed training. The superimposed training consists of the sum of a known sequence and a data-dependent sequence that is unknown to the receiver. The data-dependent sequence cancels the effects of the unknown data on channel estimation. The performance of the proposed approach is shown to significantly outperform existing methods based on superimposed training (ST).

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Over the last few years there has been growing interest in performing channel estimation via superimposed training (ST), where a training sequence is added to the information-bearing data, as opposed to being time-division multiplexed with it. Recent enhancements of ST are data-dependent ST (DDST), where an additional data-dependent training sequence is also added to the information-bearing signal, and semiblind approaches based on ST. In this paper, along with the channel estimation, we consider new algorithms for training sequence synchronization for both ST and DDST and block (or frame) synchronization (BS) for DDST (BS is not needed for ST). The synchronization algorithms are based on the structural properties of the vector containing the cyclic means of the channel output. In addition, we also consider removal of the unknown dc offset that can occur due to using first-order statistics with a non-ideal radio-frequency receiver. The subsequent bit error rate (BER) simulations (after equalization) show a performance not far removed from the ideal case of exact synchronization. While this is the first synchronization algorithm for DDST, our new approach for ST gives identical results to an existing ST synchronization method but with a reduced computational burden. In addition, we also present analysis of BER simulations for time-varying channels, different modulation schemes, and traditional time-division multiplexed training. Finally, the advantage of DDST over (conventional, non semi-blind) ST will reduce as the constellation size increases, and we also show that even without a BS algorithm, DDST is still superior to conventional ST. However, iterative semiblind schemes based upon ST outperform DDST but at the expense of greater complexity.

The three-phase four-wire shunt active power filter (SAPF) was developed to suppress the harmonic currents generated by nonlinear loads, and for the compensation of unbalanced nonlinear load currents, reactive power, and the harmonic neutral current. In this work, we consider instantaneous reactive power theory (PQ theory) for reference current identification based on the following two algorithms: the classic low-pass filter (LPF) and the second-order generalized integrator (SOGI) filter. Furthermore, since an important process in SAPF control is the regulation of the DC bus voltage at the capacitor, a new controller based on the Lyapunov function is also proposed. A complete simulation of the resultant active filtering system confirms its validity, which uses the SOGI filter to extract the reference currents from the distorted line currents, compared with the traditional PQ theory based on LPF. In addition, the simulation performed also demonstrates the superiority of the proposed approach, for DC bus voltage control based on the Lyapunov function, compared with the traditional proportional-integral (PI) controller. Both novel approaches contribute towards an improvement in the overall performance of the system, which consists of a small rise and settling time, a very low or nonexistent overshoot, and the minimization of the total harmonic distortion (THD). KEYWORDS active power filter (APF), DC bus voltage control, low-pass filter (LPF), Lyapunov function, PQ theory, SOGI filter Int J Circ Theor Appl. 2020;48:887-905.wileyonlinelibrary.com/journal/cta

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Available online xxxKeywords: Permanent magnet synchronous generator Aggregated wind farm model Equivalent wind method Approximate mechanical torque method Equivalent wind turbine rotor method a b s t r a c t This paper evaluates the responses of three aggregated models of a wind farm consisting of variable speed permanent magnet synchronous generator wind turbines when wind fluctuations or grid disturbances occur. These responses are compared with those of the detailed wind farm model, in order to verify the effectiveness of the studied aggregation methods for this type of wind farms. The equivalent wind farm models have been developed by adapting different aggregation criteria that already exist in technical literature and had been applied to other technologies. In this work, these methods have been modified to suit them to the permanent magnet synchronous generator technology. The results show that the three aggregated models provide very similar results to the detailed model, both in the evolution of active power when fluctuations in wind speed occur, and in the active power and DC-link voltage during the two simulated voltage dips. Notably, the aggregated model with an approximate mechanical torque offers excellent results.