Estimation and control strategies for a lipase production process

This paper deals with the design of a control system for a lipase production process. The aim is to maximise the enzyme production when the process is operating in fed-batch mode, by controlling the substrate feeding rate and by using the only on-line measurement available, C.E.R., given by gas analysis. At first, a dedicated estimation strategy is proposed to cope with the lack of on-line measurements. This strategy is based on minimal use of the complex and nonlinear process model in which kinetic parameters are not perfectly known. It consists in splitting the estimation problem into three cascade sub-problems and solving them by appropriate algorithms for which stability and convergence are proved under realistic conditions. The whole estimation (three state variables and two kinetic parameters) is tested and tuned by simulation and then successfully applied and validated on the real process. In the second part, an analysis of the process model is carried out to define the best operating conditions for maximised production. Then, a nonlinear controller is developed to maintain the process under these efficient operating conditions (ratio substrate/biomass kept constant). It is implemented on the process by coupling it with the previous estimation algorithm. The whole system is tested in simulation under realistic, conditions. It can be shown that it clearly increases lipase production and ensures process reliability, as the process becomes insensitive to disturbances.