A Performance Investigation of Proposed High-Voltage Boost (HVB) DC-DC Converter Fed BLDC Pumping System Using ANFIS Controller
Kshatriya Vamshi Krishna Varma1, A. Ramkumar2

1Kshatriya Vamshi Krishna Varma, Research Scholar, Department of EEE, Kalasalingam University, Krishnakoil (Tamil Nadu), India.
2Dr. A. Ramkumar, Associate Professor, Department of EEE, Kalasalingam Academy of Research & Education, Krishnakoil (Tamil Nadu), India.
Manuscript received on 02 March 2019 | Revised Manuscript received on 14 March 2019 | Manuscript Published on 17 March 2019 | PP: 230-238 | Volume-7 Issue-ICETESM18, March 2019 | Retrieval Number: ICETESM49|19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The economic growth of any country depends on quality and reliable electric power availability to agriculture sector. A simple, efficient and viable power-conditioning structure is introduced for irrigation system with assisted knowledge of advanced intelligent schemes. Among, the classical high-step up converters; a breed of non-isolated high-step-up DC-DC power converter is proposed by utilizing voltage-multiplying modules. The proposed topology can be used as multi-output converter and draw continuous current from single input source in an interleaved approach. The VSI fed brushless DC motor drive is powered by single source High-Voltage Boost (HVB) converter by utilizing solar PV system. The expertise ANFIS prediction scheme is recommended for production of optimum switching states to improve the dynamic response and ameliorate the torque ripples. The versatility of proposed scheme has been developed under variable and/or constant speed conditions by real-time conditions by using computer simulation tool, results are illustrated.
Keywords: Adaptive Neuro-Fuzzy Inference System Controller; BLDC Motor Drive; HVB Converter; Pumping System; Solar PV System.
Scope of the Article: High Performance Computing