TY - JOUR
T1 - Finite-time fault detection for stochastic nonlinear networked control systems via interval type-2 T-S fuzzy framework
AU - Zeng, Yi
AU - Wang, Zhenhuan
AU - Wu, Ligang
AU - Lam, Hak-Keung
N1 - Publisher Copyright:
© The Author(s), under exclusive licence to Springer Nature B.V. 2025.
PY - 2025/2/24
Y1 - 2025/2/24
N2 - For security and maintenance purposes, fault detection is remarkable for maintaining the smooth operation of networked control systems (NCSs). In addition, the common nonlinearity and uncertainty as well as complex dynamics such as successive packet dropouts and multiplicative noises in various industrial NCSs will hinder or slow down the fault detection and increase the difficulty of analysis, which prompt us to seek better fault detection design. In view of the above, the problem of finite-time fault detection filtering design for uncertain nonlinear NCSs with multiplicative stochastic noises and successive packet dropout is studied in the paper. The NCS with nonlinearity and uncertainty is modeled as an interval type-2 (IT2) T-S fuzzy NCS, and also, a premise-mismatched IT2 T-S fuzzy fault detection filter is constructed accordingly. The challenges of the above-mentioned fault filter design are to overcome the analysis difficulties caused by the premise-mismatch design and how to increase the membership function (MF) utilization in obtaining the fuzzy filter. After the fault detection residual system is formed, the robust performance subject to finite-time bounded constraint of the residual system is analyzed to make the fault detected timely. Furthermore, a novel IT2 fuzzy finite-time fault detection filter parameter acquisition scheme based on the linear matrix inequality (LMI) technique is proposed. In the proposed method, the premise-mismatched design makes the realization of the filter less difficult and increases the flexibility of design. Also, in the obtained method, a developed membership-function-dependent (MFD) technique is introduced to realize the efficient use of the MF information and reduce the conservativeness of the method, which can also be extended to other problems related to IT2 fuzzy models. Numerical simulation verifies the effectiveness of the proposed finite-time IT2 fuzzy fault detection method.
AB - For security and maintenance purposes, fault detection is remarkable for maintaining the smooth operation of networked control systems (NCSs). In addition, the common nonlinearity and uncertainty as well as complex dynamics such as successive packet dropouts and multiplicative noises in various industrial NCSs will hinder or slow down the fault detection and increase the difficulty of analysis, which prompt us to seek better fault detection design. In view of the above, the problem of finite-time fault detection filtering design for uncertain nonlinear NCSs with multiplicative stochastic noises and successive packet dropout is studied in the paper. The NCS with nonlinearity and uncertainty is modeled as an interval type-2 (IT2) T-S fuzzy NCS, and also, a premise-mismatched IT2 T-S fuzzy fault detection filter is constructed accordingly. The challenges of the above-mentioned fault filter design are to overcome the analysis difficulties caused by the premise-mismatch design and how to increase the membership function (MF) utilization in obtaining the fuzzy filter. After the fault detection residual system is formed, the robust performance subject to finite-time bounded constraint of the residual system is analyzed to make the fault detected timely. Furthermore, a novel IT2 fuzzy finite-time fault detection filter parameter acquisition scheme based on the linear matrix inequality (LMI) technique is proposed. In the proposed method, the premise-mismatched design makes the realization of the filter less difficult and increases the flexibility of design. Also, in the obtained method, a developed membership-function-dependent (MFD) technique is introduced to realize the efficient use of the MF information and reduce the conservativeness of the method, which can also be extended to other problems related to IT2 fuzzy models. Numerical simulation verifies the effectiveness of the proposed finite-time IT2 fuzzy fault detection method.
UR - http://www.scopus.com/inward/record.url?scp=85218681426&partnerID=8YFLogxK
U2 - 10.1007/s11071-025-10956-0
DO - 10.1007/s11071-025-10956-0
M3 - Article
SN - 0924-090X
VL - 113
SP - 16493
EP - 16510
JO - NONLINEAR DYNAMICS
JF - NONLINEAR DYNAMICS
IS - 13
ER -