Open AccessApplication of Bacterial Foraging Algorithm and Genetic Algorithm for Selective Voltage Harmonic Elimination in PWM Inverter
Author(s) -
D. Maheswaran,
N. Rajasekar,
K. Priya,
L. Ashok Kumar
Publication year - 2015
Publication title -
journal of electrical engineering and technology/journal of electrical engineering and technology
Language(s) - English
Resource type - Journals
eISSN - 2093-7423
pISSN - 1975-0102
DOI - 10.5370/jeet.2015.10.3.944
Subject(s) - pulse width modulation , control theory (sociology) , inverter , voltage , harmonic , convergence (economics) , algorithm , mathematics , genetic algorithm , computer science , engineering , mathematical optimization , physics , artificial intelligence , control (management) , quantum mechanics , economic growth , electrical engineering , economics
Pulse Width Modulation (PWM) techniques are increasingly employed for PWM inverter fed induction motor drive. Among various popular PWM methods used, Selective Harmonic Elimination PWM (SHEPWM) has been widely accepted for its better harmonic elimination capability. In addition, using SHEPWM, it is also possible to maintain better voltage regulation. Hence, in this paper, an attempt has been made to apply Bacterial Foraging Algorithm (BFA) for solving selective harmonic elimination problem. The problem of voltage harmonic elimination together with output voltage regulation is drafted as an optimization task and the solution is sought through proposed method. For performance comparison of BFA, the results obtained are compared with other techniques such as derivative based Newton-Raphson method, and Genetic Algorithm. From the comparison, it can be observed that BFA based approach yields better results. Further, it provides superior convergence, reduced computational burden, and guaranteed global optima. The simulation results are validated through experimental findings.