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Estimation and adaptive control of a fed-batch bioprocess

This paper deals with estimation and adaptive control strategies for a biotechnological process, which is in fact a lipase production process that takes place inside a fed-batch bioreactor. The lipase production process is highly nonlinear and, furthermore, the available on-line measurements are lack and the reaction kinetics is not perfectly known. On-line state estimation strategies based on extended Luenberger observer and asymptotic observer approach are derived. The unknown kinetic parameters of the bioprocess are estimated by using nonlinear techniques, such as regressive parameter estimator and high-gain observer. The control goal is to maximize the lipase production by controlling the substrate feeding rate. A nonlinear feedback control law is obtained by means of exact linearization technique. By coupling this controller with the parameter estimation algorithms, a nonlinear adaptive controller is obtained. Numerical simulations are included in order to test the behavior and the performance of the proposed estimation and control strategies.