Adaptive and robust-adaptive control strategies for anaerobic wastewater treatment bioprocesses

This paper presents the design and analysis of adaptive and robust-adaptive control strategies for a class of anaerobic wastewater treatment processes. The design procedures are developed under the realistic assumption that both bacterial growth rates and influent flow rates are time-varying and uncertain, but some lower and upper bounds of these uncertainties are known. To achieve these control strategies, firstly, a state asymptotic observer and a robust interval observer for a class of bioprocesses are presented. Secondly, by using these observers, adaptive, robust and robust-adaptive control schemes are developed and analyzed. The adaptive control structure is achieved by combining a linearizing control law with a state asymptotic observer and with a parameter estimator used for on-line estimation of unknown kinetics. The robust control structure is designed by combining a linearizing control law with an interval observer able to estimates a lower and an upper bound of unmeasurable states. Also, the uncertain process parameters are replaced by their lower and upper bounds assumed known. The robust-adaptive controller uses a linearizing control law coupled with an interval observer for the unmeasured states, and with a parameter estimator. These approaches are applied to a particular wastewater treatment bioprocess based on anaerobic fermentation. The effectiveness of the proposed algorithms is validated by several numerical simulations.

► Robust-adaptive control strategies for wastewater treatment processes are designed. ► Only lower and upper time-varying bounds of kinetic uncertainties are known. ► Controllers consist of linearizing laws, interval observers and parameter estimators. ► The interval observer is able to estimate lower and upper bounds of unknown states. ► Good simulation results are obtained for an anaerobic wastewater treatment process.