Abstract
In this paper a software sensor for estimating the respiration rate and the nonlinear oxygen transfer function {itK{inL}a} is presented. The respiration rate and the oxygen transfer function were estimated from measurements of the dissolved oxygen concentration (DO) and airflow rate by a Kalman filter. In particular, a filtering procedure was applied for the case when the DO sensor dynamic cannot be neglected. In the estimation scheme the time varying respiration rate was modelled by a filtered random walk model, and the nonlinear {itK{inL}a} function was modelled with an exponential model. A numerical study illustrated the advantage of the method. Also, real data were applied to the software sensor with promising results
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