Distributed design for active fault diagnosis

The paper deals with active fault diagnosis of stochastic large-scale systems consisting of several subsystems with separate inputs and observations, which are coupled through the system state. The subsystems are described by multiple models expressing their fault-free and faulty behaviour. The transition between the models is governed by a Markov chain. The paper proposes a distributed design of an active fault diagnosis algorithm, which takes into account the coupling among the subsystems in all stages of the algorithm. This results in a higher quality of the excitation signal and consequently in better decisions. The numerical example shows the improved performance of the proposed algorithm in comparison with the algorithms based on the decentralised design.