Abstract
Mathematical programs with complementarity constraints (MPCC) can arise in process models that contain discrete decisions such as switches, phase changes, and flow reversal. Path-following methods are an important part of advanced-step nonlinear model predictive control (NMPC) due to the ability to deal with changes in the active-set of constraints. In this work, we introduce a path-following algorithm for parametric MPCC demonstrated on a flash tank case study. We show that this algorithm can successfully track the solution without the need for fine discretization or identifying the exact points where active-set changes occur, which are important properties for NPMC implementation.