Hybrid‐triggered fault detection filter design for networked Takagi–Sugeno fuzzy systems subject to persistent heavy noise disturbance

Abstract

Summary In the network environment, the single time‐triggered scheme wastes limited bandwidth resources due to all the sampled data are transmitted to the networks, and the single event‐triggered scheme may increase system error because of ignoring factors such as changes in network utilization. To reduce the design conservatism, this paper is concerned with the hybrid‐triggered L1 fault detection filter design for a class of nonlinear networked control systems (NCSs) described by Takagi–Sugeno (T‐S) fuzzy model. Taking the effects of time‐triggered scheme and event‐triggered scheme into consideration simultaneously, we construct a fuzzy fault detection system. New results on stability and L1 performance are proposed for fuzzy fault detection system by exploiting the Lyapunov–Krasovskii functional and by means of the integral inequality method. Specially, attention is focused on the design of fault detection filter that guarantees a prescribed L1 noise attenuation level γ. Finally, two examples are presented to demonstrate the effectiveness of the proposed method.

Fault Detection for Interval Type-2 T-S Fuzzy Networked Systems via Event-Triggered Control

“…The task of fault diagnosis of the networked system is to transmit the input and output data of the system to the fault diagnosis unit through the network, so as to ensure that the stable operation of the system without fault occurs [6]. The FD methods of networked systems are proposed based on the fuzzy model [7,15,16]. However, there are bad situations under time-triggered FD such as unnecessary data transmission, increased network burden, data loss, and greater network Machines 2022, 10, 347 2 of 17 delay [8].…”

“…The event-triggered mechanism has irreplaceable advantages in the network resource-constrained system. The research on fault diagnosis technology of networked systems with event-triggered mechanisms has received extensive attention from international scholars, which has become a hot research issue in the academic community of automatic control and produced many valuable research results [8,9,[15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32].…”

“…Different event triggering methods are studied such as the adaptive event-triggering mechanism [5,10,22,23,27,29,32], the dynamic event triggering mechanism containing internal dynamic variables [19,28,31], the event triggering mechanism designed by improving constant thresholds [8,15,16,20,21,25,26]. The fault filtering problem of NCSs with interval time-varying time lags is studied by using the fuzzy fault detection filter with a generic structure [17].…”

“…However, the complexity of real systems can no longer be described by simple models. For instance, the membership functions approaches have been proposed based on the restriction that the membership functions of the descriptive model of the systems [15,16,21]. When this issue is considered, the general T-S fuzzy modeling scheme cannot achieve the desired results [15].…”

“…For instance, the membership functions approaches have been proposed based on the restriction that the membership functions of the descriptive model of the systems [15,16,21]. When this issue is considered, the general T-S fuzzy modeling scheme cannot achieve the desired results [15]. The IT2 fuzzy model was developed because of its good proxy for nonlinear systems with parameter uncertainty [29][30][31][32][33][34][35][36][37].…”