IoT Communication for Grid-Tie Matrix Converter with Power Factor Control Using the Adaptive Fuzzy Sliding (AFS) Method

Abstract

In this work, we propose and encourage the sending of an IoT-based domestic systems conditions small scale programmable framework for grid-tie matrix converter that can efficiently be executed with low-control equipment plan with quick execution capacity. The proposed framework for matrix grid-tie converter has been performed based on an adaptive fuzzy sliding technique and furthermore monitors the grid status through an IoT server. The adaptive fuzzy sliding method was connected to the framework, and a unity power factor was fulfilled alongside the wanted sinusoidal input and output results. The proposed AFS-based matrix converter has been validated through simulation using MATLAB software. The control clock signals are generated for the positive and negative clock pulses of the sequence. Here the sinusoidal reference signal is compared with the switching frequency of the triangular carrier frequency. The hardware results were also verified to validate the simulation. When diverged from other standard techniques, the proposed AFS technique has achieved 97.23% efficiency in full load conditions.

Voltage Control of Wind System Using Adaptive Fuzzy Sliding Method With Iot Monitoring

“…Based on the maximum compensated angle, a novel switching technique is presented. The dissemination of a low-control equipment plan with a rapid execution capacity-based IoT structure for grid-tie matrix converters in residential settings is suggested [17].…”