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Stability Certificates for Receding Horizon Games

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arxiv 2404.12165 v1 pith:QPURYX7S submitted 2024-04-18 eess.SY cs.SY

classification eess.SYcs.SY
keywords stabilityagentscertificatescontrolgamesconstraintsdynamicensure
verification ladder T0 review T1 audit T2 compute T3 formal
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Game-theoretic MPC (or Receding Horizon Games) is an emerging control methodology for multi-agent systems that generates control actions by solving a dynamic game with coupling constraints in a receding-horizon fashion. This control paradigm has recently received an increasing attention in various application fields, including robotics, autonomous driving, traffic networks, and energy grids, due to its ability to model the competitive nature of self-interested agents with shared resources while incorporating future predictions, dynamic models, and constraints into the decision-making process. In this work, we present the first formal stability analysis based on dissipativity and monotone operator theory that is valid also for non-potential games. Specifically, we derive LMI-based certificates that ensure asymptotic stability and are numerically verifiable. Moreover, we show that, if the agents have decoupled dynamics, the numerical verification can be performed in a scalable manner. Finally, we present tuning guidelines for the agents' cost function weights to fulfill the certificates and, thus, ensure stability.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Robust Receding Horizon Games with Additive Uncertainty

    math.OC 2026-07 accept novelty 6.0 of 10

    Tube-based robust receding-horizon games guarantee recursive feasibility under additive disturbances and drive each agent’s nominal state to a steady-state variational GNE, with actual states entering an mRPI neighborhood.

  2. Sampled-data Systems: Stability, Contractivity and Single-iteration Suboptimal MPC

    eess.SY 2025-05 conditional novelty 6.0 of 10

    A sampled-data control loop is exponentially stable for small sampling periods, and even a single optimization iteration per sample suffices when the idealized continuous-feedback model is contractive.

  3. Approximate solutions to games of ordered preference

    eess.SY 2025-07 conditional novelty 5.0 of 10

    A warm-started iterated best response algorithm computes approximate equilibria for lexicographic preference games about 100 to 1000 times faster than the baseline MCP solver in small traffic simulations, but optimali...

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