Stable model-reference adaptive control and estimation of a wastewater treatment benchmark

In this paper, an approach for estimating key time-varying parameters and for controlling a wastewater treatment benchmark is reported. Combination of a nonlinear estimation procedure and a multivariable reference model control law provides favourable performances for tracking a given model-based reference model despite disturbances and system parameter uncertainties. The convergence of the adaptive scheme is demonstrated via Lyapunov´s method. Simulation study with additive measurement noises, load disturbance and parameter jumps shows the efficiency and significant robustness of the control methodology developed for this nonlinear process.