An Improved ANFIS with Aid of ALO Technique for THD Minimization of Multilevel Inverters

作者：Francis Roy^*; Meganathan D

来源：Journal of Circuits, Systems, and Computers, 2018, 27(12): 1850193.

DOI：10.1142/S0218126618501931

• Multilevel Inverter (MLI)
• Total Harmonic Distortion (THD)
• Ant-Lion Optimizer (ALO)
• Adaptive Neuro-Fuzzy Inference System (ANFIS)

In this study, an artificial intelligent (AI) technique is proposed for minimizing the total harmonic distortion (THD) of the multi-level inverter (MLI). An AI technique is a mixture of an ALO and ANFIS, which controls the parameters of the inverter. The innovation of the proposed technique is improving the performance of the MLI, which is reducing the THD based on the output voltage waveform. Normally, the output voltage of the inverter is based on the switching angle of MLI. Then the proposed technique is utilized to optimize the switching angle and THD of the inverter. Here, the ALO is used to analyze the switching angle of the MLI with the aid of the fitness function. ANFIS is familiar with optimizing the switching angle from the ALO algorithm output. By the implementation of the proposed technique, decrease the value of THD in the MLI for gathering the performance of the system. Asymmetrical MLI is used in the proposed model and it wishes to separate DC supply to activate. For skilled activation, the optimal outcomes and the objective functions are well-definite and recognize their restriction similarly. The proposed technique was realized in MATLAB/Simulink platform and compared with the prevailing techniques such as particle swarm optimization (PSO)-ANFIS, genetic algorithm (GA)-Artificial Neural Networks (ANN) and ANN-ALO.

• 出版日期2018-11
• 单位MIT