Brief paper: Sampled-data control of networked linear control systems
Automatica (Journal of IFAC)
Delay-dependent H∞ filter design for discrete-time fuzzy systems with time-varying delays
IEEE Transactions on Fuzzy Systems
Piecewise quadratic stability of fuzzy systems
IEEE Transactions on Fuzzy Systems
Analysis and synthesis of nonlinear time-delay systems via fuzzy control approach
IEEE Transactions on Fuzzy Systems
Robust H∞ control for uncertain discrete-time-delay fuzzy systems via output feedback controllers
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Event-based H∞ filtering for networked system with communication delay
Signal Processing
An entropy approach to filtering for networked control systems
International Journal of Computer Applications in Technology
Information Sciences: an International Journal
H∞ state feedback controller design for continuous-time T-S fuzzy systems in finite frequency domain
Information Sciences: an International Journal
Insensitive reliable H∞ filtering against sensor failures
Information Sciences: an International Journal
A novel dropout compensation scheme for control of networked T-S fuzzy dynamic systems
Fuzzy Sets and Systems
Non-fragile H∞ filter design for discrete-time fuzzy systems with multiplicative gain variations
Information Sciences: an International Journal
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This paper is concerned with H∞-design for a class of networked control systems (NCSs) with multiple state-delays via the Takagi-Sugeno (T-S) fuzzy model. The transfer delays and packet loss that are induced by the limited bandwidth of communication networks are considered. The focus of this paper is on the analysis and design of a full-order H∞ filter, such that the filtering-error dynamics are stochastically stable, and a prescribed H∞ attenuation level is guaranteed. Sufficient conditions are established for the existence of the desired filter in terms of linear-matrix inequalities (LMIs). An example is given to illustrate the effectiveness and applicability of the proposed design method.