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: "torque saturation in bipedal robotic walking through control lyapunov function based quadratic programs"
  Abstract: This paper presents a novel method for directly incorporating user-defined control input saturations into the calculation of a control Lyapunov function (CLF)-based walking controller for a biped robot. Previous work by the authors has demonstrated the effectiveness of CLF controllers for stabilizing periodic gaits for biped walkers, and the current work expands on those results by providing a more effective means for handling control saturations. The new approach, based on a convex optimization routine running at a 1 kHz control update rate, is useful not only for handling torque saturations but also for incorporating a whole family of user-defined constraints into the online computation of a CLF controller. The paper concludes with an experimental implementation of the main results on the bipedal robot MABEL.

Connected through hyperedge HE-1 (induced by source paper "episodic learning with control lyapunov functions for uncertain robotic systems"):
  with members:
    - "stable gaussian process based tracking control of euler lagrange systems"
    - "a control lyapunov perspective on episodic learning via projection to state stability"
    - "end to end safe reinforcement learning through barrier functions for safety critical continuous control tasks"
    - "neural lander stable drone landing control using learned dynamics"
    - "the lyapunov neural network adaptive stability certification for safe learning of dynamical systems"
    - "sim to real learning agile locomotion for quadruped robots"
    - "a lyapunov based approach to safe reinforcement learning"
    - "accelerating imitation learning with predictive models"

Connected through hyperedge HE-2 (induced by source paper "learning control lyapunov functions from counterexamples and demonstrations"):
  with members:
    - "path following through control funnel functions"
    - "safe learning of quadrotor dynamics using barrier certificates"
    - "learning lyapunov potential functions from counterexamples and demonstrations"
    - "a theory of formal synthesis via inductive learning"
    - "counterexample guided synthesis of switched controllers for reach while stay properties"
    - "controller synthesis with inductive proofs for piecewise linear systems an smt based algorithm"
    - "counter example guided synthesis of control lyapunov functions for switched systems"
    - "learning deep control policies for autonomous aerial vehicles with mpc guided policy search"

Connected through hyperedge HE-3 (induced by source paper "a control lyapunov perspective on episodic learning via projection to state stability"):
  with members:
    - "episodic learning with control lyapunov functions for uncertain robotic systems"
    - "stagewise safe bayesian optimization with gaussian processes"
    - "neural lander stable drone landing control using learned dynamics"
    - "differentiable mpc for end to end planning and control"
    - "spectral normalization for generative adversarial networks"
    - "regret bounds for robust adaptive control of the linear quadratic regulator"
    - "safe controller optimization for quadrotors with gaussian processes"
    - "safe learning of regions of attraction for uncertain nonlinear systems with gaussian processes"

Connected through hyperedge HE-4 (induced by source paper "control barrier functions theory and applications"):
  with members:
    - "constraint driven coordinated control of multi robot systems"
    - "safe certificate based maneuvers for teams of quadrotors using differential flatness"
    - "the robotarium a remotely accessible swarm robotics research testbed"

Connected through hyperedge HE-5 (induced by source paper "an inverse dynamics approach to control lyapunov functions"):
  with members:
    - "dynamic walking with compliance on a cassie bipedal robot"
    - "momentum control with hierarchical inverse dynamics on a torque controlled humanoid"
    - "an efficiently solvable quadratic program for stabilizing dynamic locomotion"

Connected through hyperedge HE-6 (induced by source paper "frontal plane bipedal zero dynamics control"):
  with members:
    - "asymptotically stable walking of a five link underactuated 3 d bipedal robot"

Connected through hyperedge HE-7 (induced by source paper "feedback control of an exoskeleton for paraplegics toward robustly stable hands free dynamic walking"):
  with members:
    - "an efficiently solvable quadratic program for stabilizing dynamic locomotion"

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)