Stability of Observer Based Predictive Control for Nonlinear Sampled-data Systems

TL;DR

This paper introduces a novel observer-based model predictive control method for nonlinear sampled-data systems, demonstrating its stability and effectiveness through theoretical analysis and a numerical example.

Contribution

It presents a new MPC approach that relies solely on an observer for state estimation, ensuring stability in nonlinear sampled-data systems.

Findings

Semiglobally practically asymptotic stability proven for the closed-loop system.

The approach is validated with a numerical example demonstrating its effectiveness.

Abstract

We propose a new model predictive control (MPC) approach which is completely based on an observer for the state system. For this, we show semiglobally practically asymptotic stability of the closed loop for an abstract observer and illustrate our results for a numerical example.