human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "making the grid truly smart autonomous system identification in modemless dc microgrids"
  Abstract: We introduce novel framework for autonomous learning of the own configuration in direct current (DC) MicroGrids (MG) with high penetration of power electronic converters and without access to an external communication system. The framework is implemented within the decentralized primary droop control loop, enabling the controllers to learn (i) the generation capacities of dispatchable power sources, (ii) the load demands, and (iii) the admittances of the distribution system lines. Its development is founded on the fact that the steady state bus voltages in droop-controlled MG depend on the generation capacities, the load and the admittance matrix of the distribution system, through a non-linear, implicit model that can be estimated via asymptotically efficient Maximum Likelihood Estimation procedure. To define a well-conditioned estimation problem, we employ solution based on the concept of decentralized, coordinated training where the primary droop controllers temporarily switch between operating points, following a protocol that relies on predefined, amplitude-modulated training sequences. The numerical evaluations verify the analysis and confirm the practical potential of the framework.

Question: Please tell me which class the center node 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)