Dynamic optimization for activated sludge integrated design

This work presents an algorithmic approach to allow for the Integrated Design of processes and their control systems taking into account the controllability and the stability properties of the resulting system. The application of the proposed method has been carried out taking as an example model an alternative configuration to an activated sludge process belonging to a real wastewater treatment plant. In the Integrated Design, the process parameters are evaluated simultaneously with the parameters of the control system by solving a multiobjective constrained non-linear optimization problem. The considered cost function includes the investment and the operation costs and the constraints are selected to ensure that the values of some controllability are within specified ranges (disturbances sensitivity gains and the Integral Square Error norm), to ensure stability conditions using Lyapunov theory and also to guarantee bounds on the Ho, performance and many others convex performance criteria. The methodology is posed in the Linear Matrix Inequality (LMIs) framework by means of two types of models, a set of dynamical non-linear equations of the plant and a set of linearized models, iteratively obtained during the numerical optimization process.