Performance Optimization and Stability Guarantees for Multi-tier Real-Time Control Systems

Modern control systems are embracing multi-tier architectures integrating end devices and edge servers. However, due to the distinct control performance demands associated with each control task, it is a formidable challenge to optimize the control performance of multiple control tasks subject to stringent computation resource constraints while guaranteeing stability. Moreover, inherent contradictions exist in the timing aspect between the stability guarantee, which relies on offline analysis, and the run-time control performance, which should be enhanced online. It is essential to bridge the gap between the real-time scheduling of control tasks and their actual control performance. In this paper, we propose a novel real-time scheduling approach for multi-tier control systems, which leverages end devices for executing real-time control tasks and edge devices for runtime coordination. Specifically, we first introduce a new datadriven value function, called time/state/utility functions (TSUF), for modeling control system performance. TSUF captures not only timing but also the dynamic states of the physical plants. Subsequently, we propose value-based control scheduling (VCS), which is a multi-granularity scheduling mechanism based on our TSUF value function. VCS distinguishes the scheduling of stability jobs for ensuring system stability and performance jobs for optimizing real-time control performance based on run-time physical states. Finally, through realistic case studies involving multiple control loops, we demonstrate the advantages of VCS over existing scheduling approaches in terms of both control and real-time performance.