Simultaneous fault detection and control design for a network of multi-agent systems

The problem of simultaneous fault detection and control (SFDC) of linear continuous-time multi-agent systems is addressed in this paper. A mixed H∞/H- formulation of the SFDC problem by using distributed detection filters subject to only relative output measurements is presented. Using our proposed methodology, all agents reach a model reference consensus while simultaneously the agents collaborate with one another to detect the occurrence of faults in the team. Indeed, each agent not only can detect its own fault but also is capable of detecting its neighbor\u27s faults. It is shown that through a decomposition approach the computational complexity of solving the problem is effectively reduced. The extended linear matrix inequalities (LMIs) is used to reduce the conservativeness of the SFDC results by introducing additional matrix variables to eliminate the couplings of Lyapunov matrices with the system matrices. Simulation results corresponding to a team of unmanned underwater vehicles (UUVs) illustrate the effectiveness and capabilities of the proposed design methodology