TY - JOUR
T1 - A segmented iterative learning scheme-based distributed fault estimation for switched interconnected nonlinear systems
AU - Xu, Shuiqing
AU - Wang, Lejing
AU - Dai, Haosong
AU - Wang, Hai
AU - Chen, Hongtian
AU - Chai, Yi
AU - Zheng, Wei Xing
N1 - Publisher Copyright:
IEEE
PY - 2024
Y1 - 2024
N2 - In this article, a distributed fault estimation (DFE) approach for switched interconnected nonlinear systems (SINSs) with time delays and external disturbances is proposed using a novel segmented iterative learning scheme (SILS). First, through the utilization of interrelated information among subsystems, a distributed iterative learning observer is developed to enhance the accuracy of fault estimation results, which can realize the fault estimation of all subsystems under time delays and external disturbances. Simultaneously, to facilitate rapid fault information tracking and significantly reduce sensitivity to interference, a new SILS-based fault estimation law is constructed by combining the idea of segmented design with the method of variable gain. Then, an assessment of the convergence of the established fault estimation methodology is conducted, and the configurations of observer gain matrices and iterative learning gain matrices are duly accomplished. Finally, simulation results are showcased to demonstrate the superiority and feasibility of the developed fault estimation approach.
AB - In this article, a distributed fault estimation (DFE) approach for switched interconnected nonlinear systems (SINSs) with time delays and external disturbances is proposed using a novel segmented iterative learning scheme (SILS). First, through the utilization of interrelated information among subsystems, a distributed iterative learning observer is developed to enhance the accuracy of fault estimation results, which can realize the fault estimation of all subsystems under time delays and external disturbances. Simultaneously, to facilitate rapid fault information tracking and significantly reduce sensitivity to interference, a new SILS-based fault estimation law is constructed by combining the idea of segmented design with the method of variable gain. Then, an assessment of the convergence of the established fault estimation methodology is conducted, and the configurations of observer gain matrices and iterative learning gain matrices are duly accomplished. Finally, simulation results are showcased to demonstrate the superiority and feasibility of the developed fault estimation approach.
KW - Distributed fault estimation (DFE)
KW - fault estimation law
KW - segmented iterative learning scheme (SILS)
KW - switched interconnected nonlinear systems (SINSs)
UR - http://www.scopus.com/inward/record.url?scp=85192212303&partnerID=8YFLogxK
U2 - 10.1109/TNNLS.2024.3394570
DO - 10.1109/TNNLS.2024.3394570
M3 - Article
AN - SCOPUS:85192212303
SN - 2162-237X
JO - IEEE Transactions on Neural Networks and Learning Systems
JF - IEEE Transactions on Neural Networks and Learning Systems
ER -