A tool to analyze robust stability for model predictive controllers

A strategy based on Nonlinear Programming (NLP) sensitivity is developed to establish stability bounds on the plant/model mismatch for a class of opti mization-based Model Predictive Control (MPC) algorithms. By extending well -known nominal stability properties for these controllers, we derive a suff icient condition for robust stability of these controllers. This condition can also be used to assess the extent of model mismatch that can be tolerat ed to guarantee robust stability. In this derivation we deal with MPC contr ollers with final time constraints or infinite time horizons. Also for this initial study we concentrate only on discrete time systems and unconstrain ed state feedback control laws with all of the states measured. To illustra te this approach we give two examples. a linear first-order dynamic system and a nonlinear SISO system involving a first order reaction. (C) 1999 Else vier Science Ltd. All rights reserved.