Mathematical Algorithm of Fuzzy Logic Controller for Multilevel Inverter Creating Vertical Divided Voltage

Abstract

A 9-level inverter with a boost converter has been controlled with a fuzzy logic controller and a PID controller for regulating output voltage applications on resistive (R) and inductive (L), capacitance (C). The mathematical model of this system is created according to the fuzzy logic controlling new high multilevel inverter with a boost converter. The DC-DC boost converter and the multi-level inverter are designed and explained, when creating a mathematical model after a linear pulse width modulation (LPWM), it is preferred to operate the boost multi-level inverter. The fuzzy logic control and the PID control are used to manage the LPWM that allows the switches to operate. The fuzzy logic algorithm is presented by giving necessary mathematical equations that have second-degree differential equations for the fuzzy logic controller. After that, the fuzzy logic controller is set up in the 9-level inverter. The proposed model runs on different membership positions of the triangles at the fuzzy logic controller after testing the PID controller. After the output voltage of the converter, the output voltage of the inverter and the output current of the inverter are observed at the MATLAB SIMULINK, the obtained results are analysed and compared. The results show the demanded performance of the inverter and approve the contribution of the fuzzy logic control on multi-level inverter circuits.

Novel Predictive Control for the IPMSM Fed by the 3L-SNPC Inverter for EVAs: Modified Lyapunov Function, Computational Efficiency, and Delay Compensation

“…To address the aforementioned issue and to fulfill the high-performance IPMSM application requirements (e.g., EVAs), numerous multilevel power converter structures are recognized: neutral-point clamped (NPC), flying capacitor (FC), cascade H-bridge (CHB), and modular multilevel (MM) [27][28][29]. Several researchers have investigated the multilevel power converter, thanks to its benefits: low voltage applied to each component, less dv/dt and low THD of the output voltage and current waveforms, and low switching loss using the redundancy of the switching states [30,31].…”

Application of Adaptive Neuro Fuzzy Logic Method of Noised Electrical Signals for Correcti

“…The artificial neural network (ANN) is used at the design of the weighting factors for a multilevel converter while artificial neural network provides a reliable technique for protection of multi-terminal high voltage direct current system systems [10,11]. Also, lighting estimation has been made with ANN in building and environment [12,13] while Adaptive Neuro-Fuzzy "ANFIS" has been used for Maximum Power Point Tracking Control for photovoltaic system in some studies [14,15,16,17] although modulation signal regulation has been provided by fuzzy logic control in a multilevel inverter [14], it is necessary to use a higher-level application such as ANFIS to correct a signal that contains too much noise. To demonstrate the correction effect of ANFIS in this study, after the electrical signals which are a pure reference signal and a noised signal can be expressed with a mathematical equation, adaptive fuzzy logic is to be applied to correct on a distorted electrical sinusoidal.…”