CRII: CPS: Hierarchical Control for Constrained Multi-timescale Energy Management

University Of Texas At Dallas, Richardson TX

Investigators

Abstract

Modern control systems, small and large, attempt to optimize resources based on information from more and different kinds of sensors, sensing modalities, environments, and circumstances. This is especially the case for commercial and defense aircraft, vehicles, and ships, that optimize for fuel efficiency, performance, and safety. This research project develops a general control methodology for maximizing overall performance and efficiency, even when operating close to the physical limits of the system, all while ensuring safety and meeting overall objectives. This research project develops a novel "set-based approach" to construct effective hierarchical model predictive control (MPC) with provable guarantees for cyber-physical systems (CPS), where coordination among controllers provides guaranteed satisfaction of actuator and state constraints. The research of this project describes how CPS system constraints can be used to construct specific set-based coordination mechanisms for each controller within the hierarchy that provide provable closed-loop behavior for the entire system, how the underlying topology and dynamic timescales of the system is leveraged to develop system-specific hierarchical control architectures that minimize uncertainty and maximize performance, and how hierarchical control can be used for energy management and, e.g., provide greater capability, efficiency, and reliability for electrified vehicle systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.