11th Annual International Conference on Industrial Engineering and Operations Management

Modeling and Fuzzy Control of a PWM Converter Feeding DC Machine

0 Paper Citations
Track: Automation and Control

Nowadays, direct current (DC) machines are widely used in various applications thanks to its ease control and natural decoupling between its grandeur: flux and torque. In most industrial processes, it is essential to master certain physical parameters, so it is very often necessary to have recourse to a control. The work presented in this paper is based on the modeling and control of the PWM Converter-DC Machine drive chain. Firstly, we used a PI regulator for closed loop (CL) speed and current control. From the obtained results, it is noted that, the rotational speed and the current can be controlled separately. Indeed, knowing that the regulator parameters are essentially calculated as a function of the machine parameters, and that in practice the machine parameters vary over time, where this variation influences the control degradation, for this, a control strategy based on the fuzzy logic technique has been developed and applied. The basic idea is to transmit the richness of human reasoning from fuzzy logic to a computer under "if ....then" rules form. It does not process a well-defined mathematical relationship, but it uses inferences with several rules based on linguistic variables. In order to find a fast response and high dynamic performance, a comparative study between the classical PI and the fuzzy regulator as well as the study of the robustness related to the parametric variations were presented and analyzed. The modeling and control simulation of the whole system was carried out under MatLab/Simulink. The results show that the use of fuzzy logic for the control gives good results as well as good robustness.

Published in: 11th Annual International Conference on Industrial Engineering and Operations Management, Singapore, Singapore

Publisher: IEOM Society International
Date of Conference: March 7-11, 2021

ISBN: 978-1-7923-6124-1
ISSN/E-ISSN: 2169-8767