An efficient model-error model update strategy for multi-stage NMPC with model-error model

Abstract

Multi-stage NMPC with model-error model (MS-MEM) handles structural plant-model mismatch present in the nominal model of the plant in a non-conservative fashion. A model-error model (MEM) that consists of a stable linear time-invariant dynamics and a static time-variant nonlinear mapping is built using the past data such that it captures the unmodeled dynamics of the plant. The scenario tree is built for the nominal and for the extreme realizations of the plant obtained using the nominal model and the model-error model, and a multi-stage decision problem is formulated. In this paper, we propose an efficient strategy to update the model-error model present in the MS-MEM approach if new measurements invalidate the model-error model. The advantages of the proposed scheme over the previous approach where only the gain of the linear model is updated are demonstrated for a continuous stirred tank reactor (CSTR) benchmark example.