VOLTAGE TRACKING IN BOOST CONVERTER BASED ON ADAPTIVE NEURO – FUZZY INFERENCE SYSTEM
Author’s Name : Balamurugan P | Hemasilviavinothini S
Volume 01 Issue 02 Year 2014 ISSN No: 2349-2503 Page no: 19-23
In recent year various control strategies have been applied to power converters. DC-DC converter such as Buck type, Boost type, Buck-Boost type have been widely used in traditional industrial application, e.g., uninterruptible power supply (U.P.S), power system, dc motor drive, telecommunication equipment, etc. In the conventional method, Fuzzy control scheme is designed for the voltage tracking of a DC-DC Boost converter. The main drawback of only used Fuzzy logic control switching frequency will not constant on during load condition. AFNNC could be introduced. However, the computation cost is much higher than conventional system. In the proposed method presents an Adaptive Neuro – Fuzzy Inference System (ANFIS) control scheme is designed for the voltage tracking control, Harmonic reduction & current control. Then, the Total Sliding Mode Control (TSMC) strategies are introduced to developed for enhancing system robustness during the transient period .The output of the AFNNC scheme can be easily supply to the duty cycle of the power switch in the boost converter without strict constrains on control parameters selection in conventional control strategies.
Boost converter, fuzzy neural network (FNN),Lyapunov stability theorem, total sliding-mode control (TSMC), voltage tracking control
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