Stochastic economic model predictive control for Markovian switching systems

TL;DR

This paper introduces an economic model predictive control framework for nonlinear Markovian switching systems, ensuring stability, feasibility, and performance bounds despite uncertainties.

Contribution

It develops EMPC formulations for uncertain systems that guarantee recursive feasibility, stability, and performance bounds, extending prior deterministic approaches.

Findings

Guarantees recursive feasibility in control design

Provides asymptotic performance bounds

Ensures constrained mean square stability

Abstract

The optimization of process economics within the model predictive control (MPC) formulation has given rise to a new control paradigm known as economic MPC (EMPC). Several authors have discussed the closed-loop properties of EMPC-controlled deterministic systems, however, little have uncertain systems been studied. In this paper we propose EMPC formulations for nonlinear Markovian switching systems which guarantee recursive feasibility, asymptotic performance bounds and constrained mean square (MS) stability.