Robust Multi-stage NMPC under Structural Plant-model Mismatch Without Full-State Measurements

Abstract

We address the problem of robust nonlinear model predictive control (NMPC) under plant-model mismatch in the absence of full-state measurements. We propose an approach that is based on the use of a model-error model (MEM) to handle the estimation errors and the structural plant-model mismatch in a Multi-stage NMPC framework. The MEM which consists of a linear model followed by a nonlinear operator with bounded gain captures the estimation error along with the unmodeled dynamics of the plant. Multi-stage NMPC explicitly considers the presence of feedback in the problem formulation, hence it is less conservative than other robust NMPC schemes. The advantages of the proposed scheme are demonstrated on a benchmark reactor problem.