Fault detection and control co-design for discrete-time delayed fuzzy networked control systems subject to quantization and multiple packet dropouts

Distributed H∞ Consensus Fault Detection for Uncertain T‐S Fuzzy Systems with Time‐Varying Delays Over Lossy Sensor Networks

“…In the above model formulation (23), the two-term approximation method is employed to pull out the uncertainty and to estimate the time-varying delay (k) precisely. This approximation idea was used for the time-varying delay systems in [9,16,17,39], and the resulted approximation gives a much smaller upper bound of the l 2 -induced norm of uncertainty than the existing results. In view of Lemma 2, we can observe that the l 2 norm of  2 in (23) from input to output is bounded by one.…”

“…Consequently, a fault detection technology is needed to monitor the system behaviour by indicating the occurrence, location and size of the fault. Over the past decades, fruitful results regarding fault detection have been obtained [10][11][12][13][14][15][16][17][18][19]. However, most of these results on fault detection focus on the centralised architecture, which may not be suitable to distributed sensor networks.…”

“…One such challenge is the network-induced packet-dropout phenomenon that has recently drawn considerable research attention. Various approaches have been presented in the literature to model the packet dropout phenomenon [6][7][8][9], [13][14][15][16][17]. It should be pointed out that, almost all the literature concerning packet-dropout phenomenon have been specifically considered for networked control systems (NCSs) [16,17,25].…”

H ∞ Control of Networked Control System With Data Packet Dropout via Observer-Based Controller

“…The probability of data packet dropout was governed by an individual random Bernoulli distribution. The residual system was stochastically stable with a given H ∞ performance under the designed fault filter [14]. The problem of robust integral sliding mode control for NCS with multiple data packet dropout was researched.…”

Network-based control of discrete-time Systems with nonlinear perturbation and transmitting data constraint

“…By introducing some scalars into matrix cross-term bounding technique, [8] presented a new approach for the state feedback controller, with less conservatism, based on the Bilinear Matrix Inequalities (BMIs) and the descriptor model transformation. [9] focused on discrete-time delayed fuzzy networked control systems subject to quantization and multiple packet dropouts, and proposed a fault detection and control co-design method. But these results are not applicable to discrete-time network control systems with nonlinearity.…”