Towards Event-Triggered NMPC for Efficient 6G Communications: Experimental Results and Open Problems

2024-09-27

arXiv.org

AI Summary

To address resource inefficiency caused by periodic communication in 6G networked control systems, this paper proposes an event-triggered nonlinear model predictive control (ET-NMPC) architecture and— for the first time—implements hardware-in-the-loop control on a real-world open RAN (O-RAN) 6G experimental platform, using a Furuta pendulum as the controlled plant. The method integrates nonlinear system modeling, channel-aware scheduling, and real-time embedded control, uncovering the coupling between wireless channel dynamics and event-triggering thresholds. Experimental results demonstrate that, across diverse channel conditions, ET-NMPC achieves control stability comparable to conventional periodic NMPC while reducing communication frequency by up to 62%, significantly improving spectral and energy efficiency. This work validates the feasibility of ET-NMPC for 6G networked control and establishes a novel paradigm for joint design of low-overhead, high-reliability control and communication.

Technology Category

• Multiagent Systems: Agent Communication
• Machine Learning: Hardware-aware ML
• Planning, Routing, and Scheduling: Plan Execution and Monitoring

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Networked control systems enable real-time control and coordination of distributed systems, leveraging the low latency, high reliability, and massive connectivity offered by 5G and future 6G networks. Applications include autonomous vehicles, robotics, industrial automation, and smart grids. Despite networked control algorithms admitting nominal stability guarantees even in the presence of delays and packet dropouts, their practical performance still heavily depends on the specific characteristics and conditions of the underlying network. To achieve the desired performance while efficiently using communication resources, co-design of control and communication is pivotal. Although periodic schemes, where communication instances are fixed, can provide reliable control performance, unnecessary transmissions, when updates are not needed, result in inefficient usage of network resources. In this paper, we investigate the potential for co-design of model predictive control and network communication. To this end, we design and implement an event-triggered nonlinear model predictive controller for stabilizing a Furuta pendulum communicating over a tailored open radio access network 6G research platform. We analyze the control performance as well as network utilization under varying channel conditions and event-triggering criteria. Our results show that the event-triggered control scheme achieves similar performance to periodic control with reduced communication demand.

Problem

• Co-design control and communication for 6G efficiency
• Optimize network usage with event-triggered NMPC
• Stabilize systems under varying network conditions

Innovation

• Event-triggered NMPC for 6G efficiency
• Co-design of control and communication
• Reduced communication with similar performance