Predefined-time event-triggered generalized Nash equilibrium seeking for aggregative games and its application to...

Area of Science:

• Game Theory
• Distributed Systems
• Optimization

Background:

• Resource allocation in competitive multi-generator systems presents complex challenges.
• Existing generalized Nash equilibrium (GNE) seeking algorithms often exhibit asymptotic convergence, limiting practical application speed.
• Aggregative games with coupling equality constraints require efficient distributed solutions.

Purpose of the Study:

• To develop a distributed algorithm for predefined-time generalized Nash equilibrium (GNE) seeking in aggregative games.
• To achieve high-speed GNE computation while minimizing the interaction burden among agents.
• To address resource allocation problems in competitive multi-generator systems.

Main Methods:

• A novel distributed algorithm incorporating a time base generator (TBG) for predefined-time convergence.
• An average tracking technique to ensure distributed evaluation of aggregative terms within predefined time.
• A dynamic event-triggered mechanism (DETM) to reduce agent interaction and maintain convergence.

Main Results:

• The proposed algorithm achieves GNE computation within a predefined time, outperforming asymptotic methods.
• The dynamic event-triggered mechanism effectively reduces communication overhead.
• The algorithm demonstrates practical applicability through a smart charging system for electric vehicles.

Conclusions:

• The developed algorithm offers a significant advancement in distributed GNE seeking for aggregative games.
• Predefined-time convergence and reduced interaction burden are key benefits for real-world applications.
• The smart charging system serves as a validated use case for the proposed GNE seeking strategy.