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In this paper, two efficient and reliable neural approaches to control an inverter are developed. The objective is to improve the compensation performance of a conventional active power filter (APF) with a homogeneous neural structure allowing an efficient hardware implementation. The first control approach is based on a neural PI regulator. This technique uses an Adaline to determine the PI parameters...
This paper compares different variants of the least mean squares (LMS) algorithm. The objective consists in finding the best compromise between on-line learning and computational costs. Indeed, an algorithm with low computational complexity for updating Adalines weights is required for a real-time implementation of a modular neural Active Power Filter (APF). This filtering scheme is inserted in an...
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