Work

System Identification of BLDC Motor and Optimization Speed Control Using Artificial Intelligent

Year: 2019

Type: preprint

Abstract: BLDC motors have the main contribution in the transportation industry applications, for example, is used as the driving electric bicycles. The purpose of this paper is to explain how to improve the performance of BLDC motors with optimization. The method used in this study first experimented with collecting input and output data on a BLDC motor with a specification of 350-watt power. Input and output data was simulated by the ARX method to identify the transfer function equation. After obtaining the transfer function equation, simulations and analyses are performed using several optimization methods, such as PID, Fuzzy, Hybrid Fuzzy PID, and the last is by combining fuzzy and PID optimized with PSO algorithm. The results showed that the combination of Fuzzy and PID optimization with the PSO Algorithm could improve performance effectively and efficiently.

Source: SSRN Electronic Journal

Authors: Izza Anshory, Imam Robandi, Wirawan Wirawan, Makoto Ohki

Institutions: Institut Teknologi Sepuluh Nopember, Tottori University

Language: English

Topic: Fuzzy Logic and Control Systems

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy

Open Access status: green

OpenAlex ID: W3134944255

Cites:

Cited by: 5

Related to: 10