Title
Adaptive Neural Fault-Tolerant Control For A Class Of Stochastic Switched Nonlinear Systems
Abstract
This paper addresses the adaptive neural fault-tolerant control (FTC) problem for a class of stochastic switched nonstrict-feedback nonlinear systems, which have actuator faults that incorporate loss of effectiveness, stuck, and outage. Based on the character of the Gaussian function, the problem of nonstrict-feedback form is solved well. In the process of designing the controller, neural networks (NNs) are utilized to estimate the unknown functions. The problem of actuator faults is handled by designing the FTC method that is obtained by introducing a smooth function and backstepping technique. Then, the control effect satisfies that all the signals in the resulting closed-loop system are bounded and the tracking error converges to a small neighborhood around the origin. To illustrate the high efficiency of the proposed control method, a vivid simulation example is given in the end.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2927715
IEEE ACCESS
Keywords
DocType
Volume
Adaptive fault-tolerant control, neural networks, nonstrict-feedback form, stochastic nonlinear systems, switched systems
Journal
7
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Di Cui100.34
Ben Niu247829.91
Dong Yang311618.09
Tasawar Hayat400.34
Fuad E. Alsaadi51818102.89