MATEC Web Conf.
Volume 264, 20192nd International Conference on Composite Material, Polymer Science and Engineering (CMPSE2018)
|Number of page(s)||5|
|Section||Product Manufacturing (Recycle, Material Process, Machining)|
|Published online||30 January 2019|
High-Performance Control Technology of Buck Inverter Used for Super-Precision Machining of Composite Materials
Department of Electrical Engineering, I-Shou University,
* Corresponding author: email@example.com
An effective technique, genetic-feedforward sliding mode-fractional PI controlled buck inverter used for super-precision machining of composite materials is proposed. The obstruction using sliding mode control (SMC) is due to the strong chattering that severely limits its practical applicability. The chattering yields high voltage distortion in buck inverter output, thus degrading stability and reliability of super-precision machining of composite materials. The modification structure to fractional PI has been established through the plant extending way so that the chattering is diminished and better flexibility in adjusting system response can be provided. The feedforward compensator improves the dynamics response further. The genetic algorithm (GA) can be adopted for determining optimal fractional proportional-integral (FPI) parametric values. With this control technique, the TI microprocessor-based buck inverter is implemented, and then experiments illustrate that the presented technique produces less steady-state inaccuracy, chattering attenuation, loading interference rejection and parametric variation removal.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.