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

详细信息    查看全文

• 作者：Shenquan Wang^a ; ^b ; Yulian Jiang^a ; ^{jiangneu@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Yuanchun Li^a ; Derong Liu^c
• 关键词：Networked control systems (NCSs) ; Fuzzy fault detection filter ; Input&ndash ; output method ; Quantization ; Time-varying delays ; Packet dropouts ; Closed-loop design
• 刊名：Fuzzy Sets and Systems
• 出版年：2017
• 出版时间：1 January 2017
• 年：2017
• 卷：306
• 期：Complete
• 页码：1-25
• 全文大小：659 K

文摘

This paper investigates the problem of fault detection (FD) for discrete-time delayed fuzzy networked control systems with quantization and packet dropouts. Different from existing results for FD, the proposed ones are toward closed-loop design problem, that is, the controller gain, and the fault detection filter (FDF) gains are designed simultaneously. The missing phenomenon is assumed to occur, in the communication links for quantizer-to-FDF and controller-to-physical plant, where the missing probability of packet dropouts is governed by an individual random binary distribution, while the quantization errors are treated as sector-bound uncertainties. The discrete-time fuzzy networked system is first transformed into the form of interconnection of two subsystems by applying an input–output method and a two-term approximation approach, which is employed to approximate the time-varying delay. Our attention is focused on the design of fuzzy fault detection filter (FFDF) such that, for all data missing conditions, and measurement quantization, the residual system is stochastically stable with a guaranteed H_∞$H_{\infty }$ performance. Sufficient conditions are first established via introducing some slack matrices to facilitate the FDF design procedure by eliminating the coupling between the Lyapunov matrices and the system matrices. Numerical examples are provided to demonstrate the effectiveness and applicability of the proposed method.