<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper proposes the Fictitious Reference Iterative Tuning-Particle Swarm Optimization (PSO-FRIT) method to design PID controllers for control systems. The proposed method is an offline PID parameter tuning method and it is not necessary to derive any mathematical models of objected control systems. The proposed method is demonstrated by comparing with the FRIT method in numerical examples.</p>
</abstract>

This paper proposes the Fictitious Reference Iterative Tuning-Particle Swarm Optimization (PSO-FRIT) method to design PID controllers for control systems. The proposed method is an offline PID parameter tuning method and it is not necessary to derive any mathematical models of objected control systems. The proposed method is demonstrated by comparing with the FRIT method in numerical examples.

A design of PID controllers using FRIT-PSO

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"A design of PID controllers using FRIT-PSO"}

This paper proposes the Fictitious Reference Iterative Tuning-Particle Swarm Optimization (PSO-FRIT) method to design PID controllers for control systems. The...

A design of PID controllers using FRIT-PSO

Published Online: Feb 15, 2020

Page range: 1 - 6

DOI: https://doi.org/10.21307/ijssis-2019-053

Keywords
PID control, particle swarm optimization, fictitious reference iterative tuning, systems and control

© 2019 Takehito Azuma et al., published by Sciendo.

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

A design of PID controllers using FRIT-PSO

Published Online: Feb 15, 2020

Page range: 1 - 6

DOI: https://doi.org/10.21307/ijssis-2019-053

KeywordsPID control, particle swarm optimization, fictitious reference iterative tuning, systems and control

© 2019 Takehito Azuma et al., published by Sciendo.

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Keywords
PID control, particle swarm optimization, fictitious reference iterative tuning, systems and control