Information Lagrangian of Multi-Agent Systems and Its Application in Fault Detection

In multi-agent systems (MASs), the information connections between agents present significant challenges for the fault detection of the system. This paper studies MASs from the perspective of information, constructs and explores the significance and connotation of the information Lagrangian, and relates it to the operational status of MAS as an index for detecting whether a fault has occurred in MAS. In this process, the distribution of the potential function on MAS information manifold is analyzed, the relationship between geodesics, Fisher information distance (FID), and information Lagrangian on the information manifold is studied. The distribution of the MAS information Lagrangian is explained in depth from a perspective of information amount and least action principle. The simulation application verified the effectiveness of the proposed method. As an operating status and fault detection index of MAS, information Lagrangian has clear physical significance, and has scalability potential. Note to Practitioners—This work was motivated by the problem of real-time assessment and fault detection for multi-agent systems. A new quantity: information Lagrangian is proposed as the status assessment and fault detection index of multi-agent systems. Which integrates the operational information of multiple agents and can characterize the overall operational status of MAS. With a clear physical meaning, information Lagrangian can evaluate the overall operating status, achieve fault detection and localization of multi-agent systems without being affected by specific control strategies of the systems. The index proposed in our work can be applied to any configuration of multi-agent systems and have good scalability potential. Single type robots, unmanned aerial vehicles, aerial, or their hybrid multi-agent systems can all apply this index to achieve status assessment and fault detection.