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Distributed adaptive fuzzy Nash equilibrium seeking algorithms in second-order nonlinear systems under event-triggered communication
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DOI：10.1016/j.automatica.2026.113035.png)
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Abstract
En 中文
This article focuses on the distributed adaptive fuzzy Nash equilibrium (NE) seeking problems for noncooperative games in second-order nonlinear systems over a network under event-triggered communication. Noting that in real-world engineering systems, velocity signals are often subject to noise, so they are not available for control design. To solve the problem of unavailable velocity measurement, an observer with the same dynamic order as the players is designed to estimate the unavailable velocity state of the system, in which nonlinear dynamics are approximated by Takagi–Sugeno fuzzy systems. For each player, the action information of all players is estimated by local computation. To save communication and computation resources, vertex-based and edge-based event-triggered mechanisms (ETMs) are investigated in a unified framework to reduce information transmission. By introducing the Lipschitz continuity condition and the strictly convex cost function, we show the convergence of the proposed NE seeking algorithms. Compared with the existing algorithms of NE seeking, our algorithms consider the widespread nonlinearity, thereby exhibiting the merits of both reality and feasibility. Finally, two examples are offered to demonstrate the proposed NE seeking approaches.
Keywords:
Nash equilibrium
fuzzy systems
second-order nonlinear systems
event-triggered communication
distributed adaptive algorithms
Journal
IF:
5.9
Papers:
1.1W
Citations:
5.2W
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Cited Papers