.png){kind=icon}
.png){kind=icon}
Return
Multiple Pursuer Multiple Evader Differential Games
.png){kind=icon}
OA
AI
DOI：10.1109/TAC.2020.3003840.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this article an N-pursuer versus M-evader team conflict is studied. This article extends classical differential game theory to simultaneously address weapon assignments and multiplayer pursuit-evasion scenarios. Saddle-point strategies that provide guaranteed performance for each team regardless of the actual strategies implemented by the opponent are devised. The players' optimal strategies require the codesign of cooperative optimal assignments and optimal guidance laws. A representative measure of performance is employed and the Value function of the attendant game is obtained. It is shown that the Value function is continuously differentiable and that it satisfies the Hamilton-Jacobi-Isaacs equation-the curse of dimensionality is overcome and the optimal strategies are obtained. The cases of N=M and N > M are considered. In the latter case, cooperative guidance strategies are also developed in order for the pursuers to exploit their numerical advantage. This article provides a foundation to formally analyze complex and high-dimensional conflicts between teams of N pursuers and M evaders by means of differential game theory.
Keywords:
Games
State feedback
Government
Aerospace electronics
Switches
Weapons
Autonomous systems
intelligent control
optimal control
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7
Papers:
1.3W
Citations:
6.7W