Bandwidth reduction methods for packetized MPC over lossy networks

TL;DR

This paper proposes two bandwidth reduction techniques for packetized MPC over lossy networks, combining multi-horizon optimization and transmission rate reduction, validated with real 5G hardware-in-the-loop testing.

Contribution

It introduces a novel controller design that integrates multi-horizon MPC and communication-rate reduction, with theoretical guarantees and practical validation.

Findings

Reduced bandwidth usage and computational load demonstrated in hardware-in-the-loop tests.

Theoretical guarantees on feasibility and constraint satisfaction under packet loss.

Effective rate reduction strategy maintains reference-tracking performance.

Abstract

We study the design of an offloaded model predictive control (MPC) operating over a lossy communication channel. We introduce a controller design that utilizes two complementary bandwidth-reduction methods. The first method is a multi-horizon MPC formulation that decreases the number of optimization variables, and therefore the size of transmitted input trajectories. The second method is a communication-rate reduction mechanism that lowers the frequency of packet transmissions. We derive theoretical guarantees on recursive feasibility and constraint satisfaction under minimal assumptions on packet loss, and we establish reference-tracking performance for the rate-reduction strategy. The proposed methods are validated using a hardware-in-the-loop setup with a real 5G network, demonstrating simultaneous improvements in bandwidth efficiency and computational load.