human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "lowering the upper bounds on 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. In many practical scenarios controllers might not know enough information to make globally optimal decisions in a tractable way. This paper proposes a novel class of tractable optimization problems whose solution is a controller complying with any given information structure. The approach we suggest is based on decomposing intractable information constraints into two subspace constraints in the disturbance feedback domain. The resulting control policy is optimal when a condition known as Quadratic Invariance (QI) holds, whereas it provides an upper bound to the minimum cost when QI does not hold. We discuss how to perform the decomposition 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 show that our method can lead to improved performance guarantees with respect to other approaches, by applying the developed techniques to the platooning of autonomous vehicles.

Includes members:
  Member "provably safe cruise control of vehicular platoons":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed synthesis of local controllers for networked systems with arbitrary interconnection topologies")
  Member "optimal distributed control for platooning via sparse coprime factorizations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "spectrum resource management for multi access edge computing in autonomous vehicular networks")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.SY(Systems and Control)