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A distributed normalized nash equilibrium seeking algorithm for power allocation among micro-grids

Science China(Technological Sciences) 2021年第2期64卷 341-352页

作者： FU Zao YU WenWu LU JinHu YAO YiYang MEI Feng School of Cyber Science and Engineering Southeast UniversityNanjing 210096China School of Mathematics Southeast UniversityNanjing 210096China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China State Grid Zhejiang Electric Power Company Information&Telecommunication Branch Hangzhou 310007China

In this paper, a power allocation problem based on the Cournot game and generalized nash game is proposed. After integrating dynamic average consensus algorithm and distributed projection neural network through singular perturbation systems, a normalized nash equilibrium seeking algorithm is presented to solve the proposed power allocation problem in a distributed *** Lyapunov stability with the singular perturbation analysis, the convergence of the proposed algorithm is analyzed. A simulation on IEEE 118-bus confirms that the proposed distributed algorithm can adjust the power allocation according to different situations, while keeping the optimal solution within the feasible set.

关键词： generalized nash game normalized nash equilibrium points distributed nash equilibrium seeking algorithm

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Predicting Strategy of Rational Evader in Cooperative Pursuit:A distributed Bimatrix Zero-sum Game Approach

Predicting Strategy of Rational Evader in Cooperative Pursui...

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第43届中国控制会议

作者： Yixuan Li Jie Hou Xianlin Zeng Zhihong Peng National Key Laboratory of Autonomous Intelligent Unmanned Systems School of Automation Beijing Institute of Technology

Cooperative pursuit problems involve multiple pursuers cooperatively capturing an evader with a faster speed in an unbounded two-dimensional domain. To generate autonomous intelligent behaviors, pursuers must consider the responsive actions of the evader. Predicting the strategy of an evader often relies on the assumption that pursuers know full information, which is unrealistic. This paper proposes a strategy prediction method of multiple pursuers cooperating to predict a rational evader's strategy in a distributed game-theoretic framework. In this setup, each pursuer can only communicate with its neighbors and observe the evader's position, making the strategy prediction challenging. To tackle this issue, we model the strategy prediction problem as a bimatrix zero-sum game. Then, we propose a distributed nash equilibrium seeking algorithm for such a game by combining the consensus averaging, the gradient tracking, and the Frank-Wolfe techniques. Furthermore, we integrate the strategy prediction into an existing cooperative pursuit method. Numerical simulations demonstrate that our method significantly improves the probability of successful capture compared to a state-of-the-art pursuit method.

关键词： cooperative pursuit problem strategy prediction bimatrix zero-sum game distributed nash equilibrium seeking algorithm

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