Event-Triggered Fuzzy Bipartite Tracking Control for Network Systems Based on Distributed Reduced-Order Observers

Liang, Hongjing; Guo, Xiyue; Pan, Yingnan; Huang, Tingwen

doi:10.1109/tfuzz.2020.2982618

Cited by 301 publications

(137 citation statements)

References 50 publications

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“…Over the past decades, control problem has attracted respectable attention 1‐16 . The effect of the constraints exists in many practical control systems, such as physical stoppages and chemical reactor temperature.…”

Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy finite‐time fault‐tolerant control of nonlinear systems with state constraints and input quantization

Pan

Yang

et al. 2020

Adaptive Control & Signal

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Summary This article concentrates on an adaptive finite‐time fault‐tolerant fuzzy tracking control problem for nonstrict feedback nonlinear systems with input quantization and full‐state constraints. By utilizing the fuzzy logic systems and less adjustable parameters method, the unknown nonlinear functions are addressed in each step process. In addition, a dynamic surface control technique combined with fuzzy control is introduced to tackle the variable separation problem. The problem for the effect of quantization and unlimited number of actuator faults is tackled by a damping term with smooth function in the intermediate control law. Finite‐time stability is achieved by combining barrier Lyapunov functions and backstepping method. The finite‐time controller is designed such that all the responses of the systems are semiglobal practical finite‐time stable and ensured to remain in the predefined compact sets while tracking error converges to a small neighborhood of the origin in finite time. Finally, simulation examples are utilized to testify the validity of the investigated strategy.

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Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy finite‐time fault‐tolerant control of nonlinear systems with state constraints and input quantization

Pan

Yang

et al. 2020

Adaptive Control & Signal

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“…Pan et al [40] presented a novel singularity-free fixed-time fuzzy control technique for ambiguous constrained n-link robotic system. Liang et al [41] studied the stability analysis, controller design and design of the distributed reduced-order dynamic gain observer. Keeping the advantage of t-intuitionistic fuzzy sets and taking the importance of group theory, this paper presents the theory of t-intuitionistic fuzzy Abelian (cyclic) subgroups of group.…”

Section: Introductionmentioning

confidence: 99%

A Certain Class of t-Intuitionistic Fuzzy Subgroups

et al. 2020

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In this study, the t-intuitionistic fuzzy normalizer and centralizer of t intuitionistic fuzzy subgroup are proposed. The t-intuitionistic fuzzy centralizer is normal subgroup of t-intuitionistic fuzzy normalizer and investigate various algebraic properties of this phenomena. We also introduce the concept of t-intuitionistic fuzzy Abelian and cyclic subgroups and prove that every t-intuitionistic fuzzy subgroup of Abelian (cyclic) group is t-intuitionistic fuzzy Abelian (cyclic) subgroup. We show that the image and preimage of t-intuitionistic fuzzy Abelian (cyclic) subgroup are t-intuitionistic fuzzy Abelian (cyclic) subgroup under group homomorphism. INDEX TERMS t-intuitionistic fuzzy set, t-intuitionistic fuzzy subgroup, t-intuitionistic fuzzy Abelian subgroup, t-intuitionistic fuzzy cyclic subgroup AMS(MOS) Subject Classifications: 03F55, 08A72, 20N25

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“…The rapid popularization of networked control brings transmission burden of network channels. In order to reduce the network burden and improve the utilization of energy, event‐triggered scheme is employed to decrease the number of emitted and transmitted data packets 13‐17 . The scheme is well performed on reducing the waste of resources under the premise of guaranteed performance 18‐21 .…”

Section: Introductionmentioning

confidence: 99%

Design of event‐triggered networked control systems via specific triggering quantizer

Chen

Zhang

et al. 2020

Intl J Robust & Nonlinear

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Based on a new triggering quantizer, this article studies the design of networked control systems with limited bandwidth. The design algorithm is described by the program flow diagram, which implements the functions of sampling, quantization and triggering strategy. By using a specific random variable, the effects of networked issues are captured, so as to process the design procedure. Because of the nonlinearities induced by networked issues, new methods are developed to analyze the system stability. Specifically, two design methods are proposed in order to simplify the analysis and improve the performance. Finally, simulation examples are presented to verify the proposed methods.

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Event-Triggered Fuzzy Bipartite Tracking Control for Network Systems Based on Distributed Reduced-Order Observers

Cited by 301 publications

References 50 publications

Adaptive fuzzy finite‐time fault‐tolerant control of nonlinear systems with state constraints and input quantization

Adaptive fuzzy finite‐time fault‐tolerant control of nonlinear systems with state constraints and input quantization

A Certain Class of t-Intuitionistic Fuzzy Subgroups

Design of event‐triggered networked control systems via specific triggering quantizer

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