Goal-Oriented State Information Compression for Linear Dynamical System Control
Li Wang, Chao Zhang, Samson Lasaulce, Lina Bariah, and Merouane Debbah

TL;DR
This paper develops a method for optimally allocating limited communication resources in linear dynamical systems to minimize control performance loss, providing a closed-form solution and practical guidelines.
Contribution
It introduces a novel resource allocation policy for compressed state information in control systems, with a closed-form solution and improved performance over uniform policies.
Findings
Optimal resource allocation policy derived in closed-form
Simulation shows significant performance gains
Guidelines for communication timing and method
Abstract
In this paper, we consider controlled linear dynamical systems in which the controller has only access to a compressed version of the system state. The technical problem we investigate is that of allocating compression resources over time such that the control performance degradation induced by compression is minimized. This can be formulated as an optimization problem to find the optimal resource allocation policy. Under mild assumptions, this optimization problem can be proved to have the same well-known structure as in [1], allowing the optimal resource allocation policy to be determined in closed-form. The obtained insights behind the optimal policy provide clear guidelines on the issue of "when to communicate" and "how to communicate" in dynamical systems with restricted communication resources. The obtained simulation results confirm the efficiency of the proposed allocation…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Control Systems Optimization
