Multivariable adaptive predictive control of an aerated lagoon for a wastewater treatment process

The application of an adaptive multivariable predictive model-based control scheme for the control of biotechnological processes is reported. Control design consists of regulating the residual concentrations of two main variables of a multistage wastewater treatment process. Unavailability of measurements leads to the development of an identification technique derived to estimate simultaneously unavailable state variables and time-varying parameters of a nonlinear process. Convergence of the estimation scheme is demonstrated via a theorem and its proof using Lyapunov's method. The estimated variables are used in the explicit design of the control algorithm. Good simulation results have been obtained in regulation, tracking, disturbance rejection and transient behaviour, showing the efficiency of this adaptive control strategy.