Abstract
A previous paper has outlined a novel method for estimation of the parameters (including the time delay) of a general Single Input, Single Output (SISO) process model from an appropriate number of arbitrarily specified points on the process frequency response. The method involved combining an analytical approach with a least squares approach using a gradient algorithm, to provide accurate estimates of the parameters. In this paper, the approach is applied to the estimation of a model for a laboratory heating and ventilation system and the estimation of a model for the human pupil reflex to light.
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