A new adaptive DOT(dissolved oxygen tension) control algorithm considering the probe dynamics has been developed. The adaptive algorithm is used to compensate for the change of bio-reactor process dynamics. Probe dynamics is considered because the widely used oxygen probe has time delay a that makes it difficult to control the dissolved oxygen tension.
A bilinear model having two parameters and two input variables (air floe rate and rpm) is used for dissolved oxygen tension dynamics in a bio-reactor. Parameters are estimated using data weighting recursive least squares method with constant trace and its modified version. The dead beat control algorithm with first order filter is used as the control method. The control performance is improved using extended Kalman filter. Especially control performance is improved and parameter fluctuation is reduced by applying covariance matrix modification so as to reduce covariance matrix singularity. The new control algorithm performed better than other control algorithms tested PID and adaptive control without probe dynamics. When the adaptive control was adopted to two different micro-organisms, $\underline{E}. $\underline{coli}$ K-12 and $\underline{Xanthomonas campestris}$ (NRRL-B149), that have different growth rates and products, control performance was successful.