BACKGROUNDThis work addresses the design of robust adaptive control strategies for a lactic fermentation process carried out inside a continuous stirred tank reactor (CSTR). This bioprocess is widely used in bioindustry for lactic acid production, and it is characterized by strong nonlinearities and uncertainties. Under the realistic assumption that the reaction kinetics and the influent flow rates are unknown and time-varying, but lower and upper bounds of the uncertainties are known, two innovative robust adaptive control structures are proposed. RESULTSThe control strategies are designed by combining a linearizing control law with two novel parameter estimators able to estimate the unknown reaction rates. The first strategy uses a modified observer based estimator and the second one utilizes an interval parameter estimator. The control objective is to adjust the plant load so as to convert the glucose into lactic acid via fermentation, which is directly correlated with the economic aspects of lactic acid production. Numerical simulations are performed in order to validate the proposed solution. CONCLUSIONBy using the proposed control strategies the process is maintained at certain operating points that correspond to a maximum lactic production rate and a minimal residual glucose concentration. The simulations performed by considering various uncertainties and noisy measurement data show that the proposed novel robust adaptive controllers are suitable to control this kind of fermentation processes. (c) 2017 Society of Chemical Industry