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Computer Science > Systems and Control

Title: Lowering the Upper Bounds of the Cost of Robust Distributed Controllers Beyond Quadratic Invariance

Abstract: The problem of robust distributed control arises in several large-scale systems, such as transportation networks and power grid systems. Due to privacy requirements controllers may not have enough information to make globally optimal decisions in a tractable way. This paper investigates computation of sub-optimal control policies which comply with any given information structure. Specifically, we propose a novel family of restrictions of the generally intractable optimization problem. The restriction we suggest rests on splitting quadratic constraints into separate linear constraints in an optimized way. We interpret our theoretical results in terms of the possibility for certain controllers to share input variables and privacy of the information known to controllers. Finally, we consider the platooning of autonomous vehicles and utilize the developed techniques to compute sub-optimal control policies, for which we derive performance bounds.
Subjects: Systems and Control (cs.SY); Optimization and Control (math.OC)
Cite as: arXiv:1803.05528 [cs.SY]
  (or arXiv:1803.05528v1 [cs.SY] for this version)

Submission history

From: Luca Furieri [view email]
[v1] Wed, 14 Mar 2018 22:53:45 GMT (509kb,D)