A hybrid controller combining model- and knowledge-based methods applied to a bioprocess

This paper presents a new concept for the nitrification control in the treatment of highly polluted waste waters. The approach is based both on mathematical and empirical modelling. Three basic stages within this so-called hybrid control concept can be distinguished. To determine the substrate degradation rates of the micro-organisms involved in the degradation process, a mathematical model using gas analysis is used. In the second stage the substrate degradation rates are used as inputs to an extended Kalman filter for estimating the capacity utilisation efficiency of the two species of bacteria involved. The knowledge-based fuzzy controller finally maximises the estimated capacity utilisation efficiency using empirical process knowledge. The experiments carried out in a lab-scale reactor demonstrate that even with highly varying ammonia concentrations in the reactor effluent, the nitrogen concentrations in the reactor effluent can be kept within legal limits