Controller design for rigid spacecraft attitude tracking with actuator saturation
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
On mode-dependent H∞ filtering for network-based discrete-time systems
Signal Processing
Information Sciences: an International Journal
Stability analysis and control design for 2-D fuzzy systems via basis-dependent Lyapunov functions
Multidimensional Systems and Signal Processing
Further improved results on H∞ filtering for discrete time-delay systems
Signal Processing
Mixed H∞ and passive filtering for singular systems with time delays
Signal Processing
Event-triggering in networked systems with probabilistic sensor and actuator faults
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
Analysis on passivity and passification of T-S fuzzy systems with time-varying delays
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Energy and throughput aware fuzzy logic based reconfiguration for MPSoCs
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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This paper investigates the problems of stability analysis and stabilization for a class of discrete-time Takagi-Sugeno fuzzy systems with time-varying state delay. Based on a novel fuzzy Lyapunov-Krasovskii functional, a delay partitioning method has been developed for the delay-dependent stability analysis of fuzzy time-varying state delay systems. As a result of the novel idea of delay partitioning, the proposed stability condition is much less conservative than most of the existing results. A delay-dependent stabilization approach based on a nonparallel distributed compensation scheme is given for the closed-loop fuzzy systems. The proposed stability and stabilization conditions are formulated in the form of linear matrix inequalities (LMIs), which can be solved readily by using existing LMI optimization techniques. Finally, two illustrative examples are provided to demonstrate the effectiveness of the techniques proposed in this paper.