Performance Enhancement of a Single-Stage CUK Based Three Phase Photovoltaic Inverter using Anfis Controller
S. Annapoorani1, R. Jayaparvathy2, B. N. Priyanka3

1S. Annapoorani, Assistant Professor, Department of Electrical and Electronics Engineering, Agni College of Technology, Chennai, Tamil Nadu, India.
2R. Jayaparvathy, Professor, Department of Electronics and Communication Engineering, SSN College of Engineering, Kalavakkam, Tamil Nadu, India.
3B. N. Priyanka, Research Scholar, Department of Electronics and Communication Engineering, SSN College of Engineering, Kalavakkam, Tamil Nadu, India.

Manuscript received on 20 August 2019. | Revised Manuscript received on 03 September 2019. | Manuscript published on 30 September 2019. | PP: 2682-2688 | Volume-8 Issue-11, September 2019. | Retrieval Number: K21390981119/2019©BEIESP | DOI: 10.35940/ijitee.K2139.0981119
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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: A modular structured and high efficient photovoltaic (PV) system is essential in today’s scenario. The single stage Cuk based inverter has continuous input and output current, and hence, makes it suitable for applying MPPT techniques when used for PV applications. The PI, PID, and fuzzy controllers could be applied for PV inverter. The PI controller decreases the error in steady state, and at the same time, it also decreases the stability of the system. The PID controller involves large time delay process. The random nature in fuzzy controller may not lead to optimum results. Hence, this paper proposes a controller based on Adaptive Neuro-Fuzzy Inference System (ANFIS) for a three phase PV inverter based on Cuk converter. The effectiveness of proposed system is verified using MATLAB/SIMULINK, and the results are presented. The performance of proposed ANFIS controller for Cuk based three phase inverter is compared with conventional PI controller. The proposed system has several merits like increased performance, accuracy, and efficiency.
Keywords: DC‐DC power converters, DC‐AC power converters, PI control, photovoltaic systems, artificial intelligence.
Scope of the Article: Artificial Intelligence and Machine Learning