Fault detection and optimization for networked control systems with unknown delay and Markov packet dropouts

Considering the influence of the Markovian packet dropouts and the unknown short delay which can be treated as norm-bounded uncertainties, the networked control systems(NCSs) are modeled as the uncertain Markov jump linear systems(UMJLS). Then the mode dependent robust fault detection filters are designed based on the UMJLS model. Furthermore, a time domain optimization approach using the post-filter is proposed to improve the fault detection performance, and the optimal solution of the post-filter is derived in the form of Moore-Penrose inverse of matrix. An adaptive threshold is also designed, and a iterative algorithm is introduced to reduce the computation. Finally, numerical examples show that the proposed method can restrain superiorly the impact of the delays and packet dropouts, and improve the detection capability and detection speed of the fault detection system.