Hybrid PSO-HIL approach for controller tuning in servo pneumatic systems

Ashraf Saleem*, Bashar Taha

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper presents an approach that combinesParticle Swarm Optimization (PSO) and Hardware-in-the-loop (HIL) techniques for servo-control optimization and realization. The proposed approach is employed for controlling servo pneumatic system that exhibit high nonlinear dynamic behavior. In the proposed approach, the system is firstly identified through HIL, then the identified transfer function is used for controller tuning using PSO. After having the controller tuned in the simulation environment, it was applied to the real system through HIL. Simulation as well as experimental results show that the proposed method gives significantly better dynamic performances than using traditional tuning techniques. Furthermore, the proposed method facilitates the realization of effective control system for servo pneumatic systems.

Original languageEnglish
Title of host publication2014 15th International Workshop on Research and Education in Mechatronics, REM 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479930296
DOIs
Publication statusPublished - Oct 10 2014
Externally publishedYes
Event2014 15th International Workshop on Research and Education in Mechatronics, REM 2014 - El-Gouna, Egypt
Duration: Sept 9 2014Sept 11 2014

Publication series

Name2014 15th International Workshop on Research and Education in Mechatronics, REM 2014

Other

Other2014 15th International Workshop on Research and Education in Mechatronics, REM 2014
Country/TerritoryEgypt
CityEl-Gouna
Period9/9/149/11/14

Keywords

  • Hardware-in-the-loop concept
  • Particle swarm optimization (PSO)
  • Servo-pneumatic system
  • Tuning PID parameters

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Mechanical Engineering
  • Education
  • Artificial Intelligence

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