Control of a wastewater treatment process using linear and nonlinear model predictive control

Wastewater treatment processes are used to reduce the amount of polluting substances in waste water resulting from human or industrial consumption. Afterwards, the water is discharged in lakes, rivers, seas, therefore it is important that these systems have an increased efficiency when it comes to treating the waste water. In this paper, we consider a nonlinear wastewater treatment system with four states and one input. We introduce an optimal control problem with state - input constraints, and a corresponding model predictive control scheme and we solve it using ACADO Toolkit. Our main reasons for using the ACADO Toolkit are that it is Open Source, it has a user friendly MATLAB interface and has the advantage of being self - contained (only needs a C++ compiler). We also consider a model predictive control scheme based on the linearization of the nonlinear system at each step, and we solve it using a standard quadratic program solver. From simulations we observe that both approaches produce a similar closed loop behavior, but the linearization based approach is faster in terms of CPU time.