A Robust Model Predictive Control Method for Networked Control Systems

TL;DR

This paper introduces a robust model predictive control approach tailored for networked control systems, effectively handling delays and packet dropouts to ensure system stability and convergence.

Contribution

It presents a novel prediction consistent method integrated with linear tube MPC, maintaining original MPC properties under network constraints.

Findings

System converges robustly to the origin under mild conditions.

Method effectively compensates for delays and packet losses.

Validated with simulations on a cart pole and stirred tank reactor.

Abstract

Robustly compensating network constraints such as delays and packet dropouts in networked control systems is crucial for remotely controlling dynamical systems. This work proposes a novel prediction consistent method to cope with delays and packet losses as encountered in UDP-type communication systems. The augmented control system preserves all properties of the original model predictive control method under the network constraints. Furthermore, we propose to use linear tube MPC with the novel method and show that the system converges robustly to the origin under mild conditions. We illustrate this with simulation examples of a cart pole and a continuous stirred tank reactor.