Distributed state estimation, fault detection and isolation filter design for heterogeneous multi-agent linear parameter-varying systems

TLDR: In this article, the authors present a new approach for the design of distributed state estimation and fault detection and isolation (FDI) filters for a class of linear parameter-varying multi-agent systems, where the state space representations of the agents are not identical.

Abstract: In this study, the authors present a new approach for the design of distributed state estimation and fault detection and isolation (FDI) filters for a class of linear parameter-varying multi-agent systems, where the state-space representations of the agents are not identical. The developed formulation for the FDI offers a distributed filter design method, in which each agent uses sensor measurements both locally and from the neighbouring agents. Each FDI filter is in the ‘unknown input observer’ form which are designed so that their outputs, i.e. residual signals, are: (i) robust with respect to the external disturbance inputs and (ii) sensitive with respect to the fault signals. Moreover, it is shown that using the proposed methodology each agent is able to estimate not only its own states, but also states of its nearest neighbours in the presence of external disturbances and faults. Finally, a numerical example is given to illustrate the efficacy of the main results of the paper.