Fuzzy logic based DC-Link Voltage Self-Balance Method for Multilevel Converter with less Number of Voltage Sensors

b.anji babu; arikatla nagalakshmi

Fuzzy logic based DC-Link Voltage Self-Balance Method for Multilevel Converter with less Number of Voltage Sensors

Authors: b.anji babu, arikatla nagalakshmi

Unique Paper ID: 147520
Volume: 5
Issue: 8
PageNo: 253-260

Keywords: Capacitor voltage balance cascade active power filter (CS-APF) diode-clamped modular multilevel converter (DCM2 C) minimum number of voltage sensors fuzzy logic controller.

Abstract:
In many inverters, Voltage balance of dc- link capacitors is very important for applications of a cascade multilevel converter or a modular multilevel converter. In this paper, a novel diode-clamped modular multilevel converter (DCM2 C) topology is proposed and a power feedback control method is developed with fuzzy logic controller. With the developed control strategy, the proposed diode-clamped circuit becomes controllable closed loop which enables the capacitor voltages to be clamped by low power rating clamping diodes. The proposed topology and control strategy has quicker response with transient state error reduction and requires much fewer voltage sensors than the normally used traditional method of multilevel inverters as diode clamped inverters; therefore, the system performance improvement and cost reduction are expected. Based on the proposed DCM2 C, a novel N +1-level cascade multilevel topology is proposed for a cascade active power filter (CS-APF). The Proposed fuzzy logic controller is implemented to get study state response at dc voltage capacitors, therefore to get balanced load outputs. The simulation results from the CS-APF have demonstrated and verified the effectiveness of the proposed novel topology and control method.

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Cite This Article

ISSN: 2349-6002
Volume: 5
Issue: 8
PageNo: 253-260

Fuzzy logic based DC-Link Voltage Self-Balance Method for Multilevel Converter with less Number of Voltage Sensors

Available:https://ijirt.org/Article?manuscript=147520

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Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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