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Network-based H∞ control for T–S fuzzy systems with an adaptive event-triggered communication scheme

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TLDR
An adaptive event-triggered communication scheme for NCSs is presented, and an asynchronous premise re-construct method for networked T–S fuzzy systems is proposed, which relaxes the assumption of the prior work that the premises of the plant and the PDC control rules are synchronous.
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This article is published in Fuzzy Sets and Systems.The article was published on 2017-12-15. It has received 133 citations till now. The article focuses on the topics: Fuzzy control system & Asynchronous communication.

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Citations
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Journal ArticleDOI

Fuzzy Control Systems: Past, Present and Future

TL;DR: This paper reviews the key features of the three above types of fuzzy systems and points out the historical rationale for each type and its current research mainstreams, and focuses on fuzzy model-based approaches developed via Lyapunov stability theorem and linear matrix inequality (LMI) formulations.
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A review on stability analysis of continuous-time fuzzy-model-based control systems

TL;DR: The focus of this paper is to promote the concept of membership-function-dependent (MFD) stability analysis, which makes use of the information of membership functions aiming to relax the stability conditions compared with the dominant membership- function-independent (MFI) stabilityAnalysis in the literature.
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Quantized Static Output Feedback Fuzzy Tracking Control for Discrete-Time Nonlinear Networked Systems With Asynchronous Event-Triggered Constraints

TL;DR: The objective of this article is to design a quantized event-triggered tracking controller such that the resulting system is asymptotically stable and the given tracking performance is guaranteed.
Journal ArticleDOI

Quantized Stabilization for T–S Fuzzy Systems With Hybrid-Triggered Mechanism and Stochastic Cyber-Attacks

TL;DR: This paper examines quantized stabilization for Takagi–Sugeno (T–S) fuzzy systems with a hybrid-triggered mechanism and stochastic cyber-attacks to guarantee the asymptotical stability of networked control systems by using Lyapunov stability theory and linear matrix inequality techniques.
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Exponential Stabilization of Takagi–Sugeno Fuzzy Systems With Aperiodic Sampling: An Aperiodic Adaptive Event-Triggered Method

TL;DR: A new exponential stability criterion is presented to establish the quantitative relationship among the adaptive adjusted event threshold, the decay rate, the upper bound, and the lower bound of variable sampling period, simultaneously.
References
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Book

Stability of Time-Delay Systems

TL;DR: Preface, Notations 1.Introduction to Time-Delay Systems I.Robust Stability Analysis II.Input-output stability A.LMI and Quadratic Integral Inequalities Bibliography Index
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A Survey of Recent Results in Networked Control Systems

TL;DR: This work reviews several recent results on estimation, analysis, and controller synthesis for NCSs, and addresses channel limitations in terms of packet-rates, sampling, network delay, and packet dropouts.
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Event-Triggered Real-Time Scheduling of Stabilizing Control Tasks

TL;DR: This note investigates a simple event-triggered scheduler based on the paradigm that a real-time scheduler could be regarded as a feedback controller that decides which task is executed at any given instant and shows how it leads to guaranteed performance thus relaxing the more traditional periodic execution requirements.
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Reciprocally convex approach to stability of systems with time-varying delays

TL;DR: This paper suggests the lower bound lemma for such a combination, which achieves performance behavior identical to approaches based on the integral inequality lemma but with much less decision variables, comparable to thosebased on the Jensen inequalityLemma.
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A cone complementarity linearization algorithm for static output-feedback and related problems

TL;DR: This paper describes a linear matrix inequality (LMI)-based algorithm for the static and reduced-order output-feedback synthesis problems of nth-order linear time-invariant (LTI) systems with n/sub u/ and n/ sub y/) independent inputs (respectively, outputs).
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