On the optimal control of the steel annealing processes as a two-stage hybrid systems via PSO algorithms

M. Senthil Arumugam*, G. Ramana Murthy, C. K. Loo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)

Abstract

The computation of optimal control variables for a two-stage steel annealing process which comprises of one or more furnaces is proposed in this paper. The heating and soaking furnaces of the steel annealing line form the two-stage hybrid systems. Three algorithms including particle swarm optimisation (PSO) with globally and locally tuned parameters (GLBest PSO), a parameter free PSO algorithm (pf-PSO) and a PSO-like algorithm via extrapolated PSO (ePSO) are considered to solve this optimal control problem for the two-stage steel annealing processes (SAP). The optimal solutions including optimal line speed, optimal cost and job completion time obtained through these three methods are compared with one another and those obtained via conventional PSO (cPSO) with time varying inertia weight (TVIW) and time varying acceleration coefficient (TVAC). From the results obtained through the five algorithms considered, the efficacy and validity of each algorithm are analysed.

Original languageEnglish
Pages (from-to)198-209
Number of pages12
JournalInternational Journal of Bio-Inspired Computation
Volume1
Issue number3
DOIs
Publication statusPublished - 2009

Keywords

  • Hybrid systems
  • Optimal control
  • Particle swarm optimisation
  • PSO
  • SAPs
  • Steel annealing processes

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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