Arumugam, M.S. and Murthy, G.R. and Loo, C.K. (2009) On the optimal control of the steel annealing processes as a two-stage hybrid systems via PSO algorithms. International Journal of Bio-Inspired Computation, 1 (3). pp. 198-209. ISSN 1758-0366,
Full text not available from this repository.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.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Additional Information: | Arumugam, M. Senthil Murthy, G. Ramana Loo, C. K. |
| Uncontrolled Keywords: | Computer science; artificial intelligence; optimal control, steel annealing, particle swarm optimisation, PSO, hybrid systems, heating furnaces, soaking furnaces, line speed, cost, job completion time, bio-inspired computation |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Faculty of Computer Science & Information Technology > Department of Artificial Intelligence |
| Depositing User: | Miss Nur Jannatul Adnin Ahmad Shafawi |
| Date Deposited: | 19 Mar 2013 00:16 |
| Last Modified: | 19 Mar 2013 00:16 |
| URI: | http://eprints.um.edu.my/id/eprint/5157 |
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