Adaptive linearizing control of bioreactors

Abstract

In this communication we shall present developments concerning the synthesis of Single-Input, Single-Output (SISO) and Multi-Input, Multi-Output (MIMO) adaptive linearizing algorithms for the operation of bioreactors. Results will be illustrated for the baker’s yeast fermentation process. The synthesis of these non-linear control laws is performed by employing differential geometry techniques with system linearization by state feedback. The controller design includes a step of order reduction of the process state model. The adaptive feature comes from the on-line estimation of the required process time varying parameters. The adaptive algorithm proposed enforces a desired and pre-set second order convergence dynamics as originally introduced by Oliveira et al. (1). Formulating the estimator on this basis leaves the user with the choice of two simple and intuitive tuning parameters with physical meaning - a damping coefficient and a natural period of oscillation.