Weighted minimum-variance self-tuning regulation of stochastic time-varying systems: application to a heat transfer process
نویسندگان
چکیده
This paper deals with the weighted minimum-variance self-tuning regulation of stochastic time-varying systems, which can be described by linear input-output mathematical models. We consider the input-output ARMAX mathematical models with unknown time-varying parameters. The recursive extended least squares RELS algorithm, which can be applied to the stochastic time-varying systems, is presented. Self-tuning regulators are developed on the basis upon the weighted minimum-variance control strategy. The developed theoretical results are applied to a heat transfer process. The obtained practical results show the good performances of the developed weighted minimum-variance self-tuning regulators.
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