On the optimal control of the steel annealing processes as a two-stage hybrid systems via PSO algorithms
Document Type
Article
Publication Date
1-1-2009
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.
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
Divisions
ai
Publication Title
International Journal of Bio-Inspired Computation
Volume
1
Issue
3
Additional Information
Arumugam, M. Senthil Murthy, G. Ramana Loo, C. K.