Distributed simultaneous fault detection and leader-following consensus control for multi-agent systems

In this paper, the problem of distributed simultaneous fault detection and leader-following consensus control (SFDLCC) in a multi-agent network is investigated. In the proposed method, instead of designing two separate units for fault detection and control objectives, a single module is used that conducts both tasks. Based on the extended linear matrix inequality (LMI) technique, an SFDLCC module is designed for each agent which utilizes both the data received from the neighboring agents as well as the available local relative measurements. The SFDLCC unit in each agent generates both the control input and the residual signal such that the effect of the unknown inputs including faults, disturbances and noises on the tracking error and the effect of disturbances and noises on the residual signal are attenuated using finite frequency H_∞ performance index. On the other hand, the effect of fault inputs on the residual signals is enhanced using the finite frequency H_- performance index. Moreover, in the proposed algorithm, the group can not only isolate the faulty agent but also determine whether the fault is in the sensors or actuators. Finally, to illustrate the effectiveness of the proposed methodology, a simulation study is provided.