Information manifold and fault detection of multi-agent systems

Abstract

With the increase of the number of agents in multi-agent systems and the rapid increase of the complexity of the overall structure of the system, the fault detection and diagnosis work has brought great challenges. Researchers have carried out considerable research work on fault detection and diagnosis of multi-agent systems, but there is no research on fault state estimation and diagnosis based on the information and state of the whole multi-agent system. Based on the global perspective of information geometry theory, this paper presents two new physical quantities of the information manifold of multi-agent systems, as Lagrangian and energy–momentum tensor, to express the state of the overall information of multi-agent systems, and to characterize the energy state and development trend of faults. In this paper, two new physical parameters are introduced into the research of multi-agent fault detection and diagnosis, and the fault state and trend of multi-agent system are evaluated from the global perspective, which provides more comprehensive theoretical support for designing more scientific and reasonable fault diagnosis and fault recovery strategies. Simulation of the application example confirms the competitive performance of the proposed method.