Identification and cascade control of servo-pneumatic system using Particle Swarm Optimization

Ashraf Saleem, Bashar Taha, Tarek Tutunji, Ahmad Al-Qaisia

Research output: Contribution to journalArticle

28 Citations (Scopus)

Abstract

This paper presents a cascade control methodology for pneumatic systems using Particle Swarm Optimization (PSO). First, experimental data is collected and used to identify the servo-pneumatic system where an Auto-Regressive Moving-Average (ARMA) model is formulated using PSO algorithm. Then, cascaded Proportional-Integral-Derivative (PID) controller with PSO tuning is proposed and implemented on real system using Hardware-In-the-Loop (HIL). The identified model is validated experimentally and the performance of the cascaded-PID controller is tested under various conditions of speed variation. Experimental results show that cascaded-PID with PSO tuning performs better than single-PID, especially in disturbance rejection (a practical challenge in industrial pneumatic systems). Results also show that cascaded-PID with PSO-tuning performs better than cascaded-PID with self-tuning in the transient and steady-state responses.

Original languageEnglish
Pages (from-to)164-179
Number of pages16
JournalSimulation Modelling Practice and Theory
Volume52
DOIs
Publication statusPublished - 2015

Keywords

  • Cascaded control
  • Optimization
  • Particle
  • PID control
  • Servo-pneumatic system
  • Swarm
  • System identification

ASJC Scopus subject areas

  • Software
  • Modelling and Simulation
  • Hardware and Architecture

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