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February 23, 2024IETE Journal of Research4 citations

Development of Sliding Mode Control-Adaptive Neuro-Fuzzy Inference Strategy Algorithm for Three-Phase 15-Level MLI

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TVT. Deepika VinothiniRKR. KarthigaivelJBJ. Barsana Banu

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Abstract

A comparative analysis was conducted in current research on the control strategies utilized in three-phase 15-level Cascaded H-Bridge Multilevel inverter (CHBMLI)-fed different RL loads with a three-phase induction motor, generally applied in industries. The analysis of 15-level CHBMLI, with Sliding Mode Control (SMC), the sliding mode control with an artificial neural network (SMC-ANN), and sliding mode control with an Adaptive Neuro-Fuzzy Inference Strategy (SMC-ANFIS) controller are explained. The study compared the performance achieved by controllers at four different speeds of a 3ϕ inductor motor and parallel-connected RL load dynamic change under closed-loop operations. The comparative study results demonstrate that there should be a reduction in the methodology suggested in terms of both the quantity of power devices and Total Harmonic Distortion (THD). The researcher conducted the experimentation procedures to authenticate the proposed 15-level MLI topology's performance. The SMC-ANFIS control technique produces less voltage and lower current total harmonic distortion of 5.53% and 2.74% compared to the SMC-ANN control technique in both simulation and real-time implementations.

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Vinothini et al. (2024) studied this question.

synapsesocial.com/papers/68e77f49b6db6435876f29a1https://doi.org/10.1080/03772063.2024.2315203
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