Self-tuning PID parameters using NN-GA for brush DC motor control system

Conference proceedings article

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Publication Details

Author list: Pongfai J., Assawinchaichote W.

Publisher: Hindawi

Publication year: 2017

Start page: 111

End page: 114

Number of pages: 4

ISBN: 9781538604496

ISSN: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85039899816&doi=10.1109%2fECTICon.2017.8096185&partnerID=40&md5=49f97443179a7f4d797bcccb6e318dfb

Languages: English-Great Britain (EN-GB)

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Abstract

This paper presents the self-tuning PID parameters by applying Artificial intelligence(AI) algorithm for tuning the Brush DC motor. This proposed approach combines with two algorithms, so called the NN-GA, which are the Neural Network (NN) and the Genetic algorithm(GA). To show the effectiveness of the designed approach, the simulation results are then given. In addition, the simulation results are analyzed by examining the transient responses and comparing the performance of self-tuning with the pure GA and the pure NN. The evaluated criterions of analysis and comparison performance are the maximum overshoot, the steady state error, the rise time and the settling time. From the simulation results, the NN-GA has significantly given the better results than the pure GA and the pure NN. ฉ 2017 IEEE.

Keywords

Brush DC motor, self-tuning, transient response analysis