Bandwidth reduction methods for packetized MPC over lossy networks
This addresses bandwidth constraints for offloaded MPC systems in networked control applications, but it is incremental as it builds on existing MPC methods.
The paper tackled the problem of reducing bandwidth usage for packetized model predictive control (MPC) over lossy networks by introducing a controller design with multi-horizon MPC and communication-rate reduction, validated on a real 5G setup to show simultaneous improvements in bandwidth efficiency and computational load.
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.