Hierarchical Decentralized Stochastic Control for Cyber-Physical Systems
Kesav Kaza, Ramachandran Anantharaman, Rahul Meshram

TL;DR
This paper develops a hierarchical decentralized control framework for cyber-physical systems, analyzing two optimization approaches with different reward horizons, and provides theoretical guarantees and bounds for their policies.
Contribution
It introduces two novel optimization frameworks, COpt and FOpt, for hierarchical decentralized control in CPS, with comprehensive analysis and convergence proofs.
Findings
COpt always outperforms FOpt in value function.
Existence of optimal policies is proven for both frameworks.
Explicit bounds on the difference between COpt and FOpt are derived.
Abstract
This paper introduces a two-timescale hierarchical decentralized control architecture for Cyber-Physical Systems (CPS). The system consists of a global controller (GC), and N local controllers (LCs). The GC operates at a slower timescale, imposing budget constraints on the actions of LCs, which function at a faster timescale. Applications can be found in energy grid planning, wildfire management, and other decentralized resource allocation problems. We propose and analyze two optimization frameworks for this setting: COpt and FOpt. In COpt, both GC and LCs together optimize infinite-horizon discounted rewards, while in FOpt the LCs optimize finite-horizon episodic rewards, and the GC optimizes infinite-horizon rewards. Although both frameworks share identical reward functions, their differing horizons can lead to different optimal policies. In particular, FOpt grants greater autonomy to…
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Taxonomy
TopicsSmart Grid Energy Management · Smart Grid Security and Resilience · Adaptive Dynamic Programming Control
