Order reduction of non-linear differential-algebraic process models

Abstract A method for order reduction of non-linear differential-algebraic models arbitrary index is presented. The approach is a direct generalization of a method suggested by Pallaske in 1987 for the reduction of explicit differential equation models. It relies on an optimal orthogonal projection of the solution trajectories into a subspace of the original state space. A rigorous development of the reduction technique is given. Strong emphasis is on implementational issues such as the choice of tuning parameters for a particular problem. A theoretical and numerical evaluation of the method is provided. The case studies discussed include the reduction of a strongly non-linear catalytic fixed bed reactor model.