Decentralised control optimisation for a glass furnace by SGAs

In this paper, the potential of standard genetic algorithms (SGAs) are presented to optimise the discrete PID parameters for multivariable glass furnace. Control oriented models of each multivariable glass furnace; glass temperature and excess oxygen are used to optimise the discrete controller with personalised cost function and adjusted boundaries by SGAs, individually. Well optimised discrete PID parameters by control oriented model are applied to realistic multivariable model by decentralised method.

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