This paper attempts to improve the dynamic performance of a shunt-type active power filter. The predictive and adaptive properties of artificial neural networks (ANNs) are used for fast estimation of the compensating current. The dynamics of the dc-link voltage is utilized in a predictive controller to generate the first estimate followed by convergence of the algorithm by an adaptive ANN (adaline) based network. Weights in adaline are tuned to minimize the total harmonic distortion of the source current. Extensive simulations and experimentations confirm the validity of the proposed scheme for all kinds of load (balanced and unbalanced) for a three-phase three-wire system.Index Terms-Adaline, current control, nonlinear load, shunt active power filter (APF), total harmonic distortion (THD), voltage source inverter.

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Often, High Brightness LEDs (HB-LED) are connected in series to create strings. According to their data sheets, the HB-LEDs have a variation in their forward voltage drop. This forward voltage variation may create a non-uniform illumination if the strings are connected in parallel. This paper proposes a probabilistic approach for modeling the forward voltage drop across the HB-LEDs and determining the value of the resistance needed in each string to control the current. The results of this paper show that when the probabilistic models are used, the value of the added balancing resistance is reduced compared to when using standard worst case models.

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