The controlling and monitoring of bioprocesses very often requires the estimation of certain biological concentrations that are difficult to measure, usually assuming some structure of the reaction rates which might be barely known. Although many algorithms have been designed to estimate these reaction rates, they are not robust against input disturbances and cannot be updated to treat them. This paper addresses the problem of estimating unmeasurable states, reaction rates, and input disturbance by applying a hybrid observer in a continuous bioreactor. The proposed algorithm uses an extended super-twisting algorithm coupled with an adaptive observer to exponentially estimate the reaction rates and input disturbance provided the persistent excitation condition is fulfilled. Later, an asymptotic observer estimates the unmeasurable states with the previous estimations. The hybrid observer is tested through simulations in a continuous sulfate-reducing bioprocess. Finally, the advantage of estimating the external disturbance is highlighted through its use in a disturbance rejection control to counteract its undesirable effect.
hybrid observer, super twisting algorithm, adaptive observer, asymptotic observer, continuous bioreactor
93B11, 93D11