Title :
Artificial neural network regulator implementation for 50kW half controlled thyristor rectifier
Author :
Bartl, Matous ; Rubas, Pavel
Author_Institution :
Dept. of Appl. Electron. & Telecommun., Univ. of West Bohemia, Plzeň, Czech Republic
Abstract :
Paper describes solution of regulator for 50kW one phase half controlled thyristor rectifier. Device stabilizes 620V DC link for 3-phase 400V/50Hz invertor for locomotive air compressor driven by induction motor. Wide range and unstable one phase input voltage are typical for application such like this. Conventional PI/PS regulator is not suitable due to long response time. Proposed solution uses feedforward multilayer perceptron artificial neural network for control phase angle estimation. Implementation based on selected method as well as method itself is described. Obtained results and comparison with conventional method are given.
Keywords :
compressors; induction motors; invertors; multilayer perceptrons; rectifying circuits; thyristor circuits; DC link; artificial neural network regulator; control phase angle estimation; feedforward multilayer perceptron; frequency 50 Hz; half controlled thyristor rectifier; induction motor; invertor; locomotive air compressor; phase input voltage; power 50 kW; voltage 400 V; voltage 620 V; Artificial neural networks; Converters; Firing; Rectifiers; Regulators; Thyristors; 3-phase invertor; Artificial neural network; Controlled rectifier; electric locomotive; power convertor;
Conference_Titel :
Electric Power Engineering (EPE), 2015 16th International Scientific Conference on
Conference_Location :
Kouty nad Desnou
DOI :
10.1109/EPE.2015.7161139
