Robust event-triggered reliable control for T-S fuzzy uncertain systems via weighted based inequality

Nagamani, G.; Joo, Young Hoon; Soundararajan, G.; Mohajerpoor, Reza

doi:10.1016/j.ins.2019.09.034

Cited by 43 publications

(21 citation statements)

References 45 publications

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“…More especially, some remarkable works have been done in the event‐triggered mechanism for T–S fuzzy system by using simple time‐varying delay. In [23], robust event‐triggered reliable control for T–S fuzzy uncertain systems have been studied with weighted based inequality. Event‐ triggered control has been designed for T–S fuzzy networked systems with distributed delay method and transmission delay in [24] and network‐based

H_{\infty}

control for T–S fuzzy systems with an adaptive event‐triggered communication scheme has been discussed in [32].…”

Section: Resultsmentioning

confidence: 99%

“…Recently, event‐triggered synchronisation control has been proposed in [31] for the T–S fuzzy neural networked systems based on simple time‐delay method. The model considered in the present study is more practical than that proposed by [23, 24, 31, 32], in light of the fact that they consider usual ETM has been studied with T–S fuzzy system based on the simple time‐varying delay approach, but in this paper, we consider a new adaptive event‐triggered mechanism for successive time delay method with the combination of dissipativity performance. In addition, the proposed dissipative analysis is the relation of applied energy to the system with energy started in the system, that is why we analyse ETM this issue in our paper to save the communication resources and have many real‐life application, which is another advantage of our paper.…”

Section: Resultsmentioning

confidence: 99%

“…In [22], extended dissipative analysis has been discussed for uncertain T–S fuzzy system with time‐varying delay and randomly occurring gain variations. Furthermore, in [23], the authors proposed event‐triggered reliable control for T–S fuzzy uncertain systems with weighted based inequality. Quite recently in [24], event‐triggered control (ETC) of T–S fuzzy networked system has been studied for distributed delay method.…”

Section: Introductionmentioning

confidence: 99%

“…Motivated by the above discussions, in this paper, the extended dissipativity for T–S fuzzy system via STD signal is discussed in terms of the event‐triggered mechanism. The existing methods in [23, 24], are dealt with only event‐triggered approach for T–S fuzzy system. In this paper, we projected STD approach with one benchmark problem, which further shows the significance of our research.…”

Section: Introductionmentioning

confidence: 99%

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Robust event‐triggered T–S fuzzy system with successive time‐delay signals and its application

Vadivel

Joo

2020

IET Control Theory & Appl

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This study isrelevant to the topic of a robust event‐triggered mechanism for the Takagi–Sugeno (T–S) fuzzy system with successive time‐delay (STD) signals and its application, where the uncertainties satisfy the randomly occurring form. Firstly, an event‐triggered communication scheme is introduced, which can adaptively adjust the communication threshold to save limited communication resource. The primary aim of this study is to model an event‐triggered mechanism with STD, which ensures that the suggested T–S fuzzy system achieves extended dissipative with permissible uncertainties. Secondly, by using the relaxed integral inequality technique, single and double auxillary function‐based integral inequalities to evaluate the derivative of the designed Lyapunov–Krasovskii functional, quadratically stable condition is established for the delayed fuzzy system in terms of linear matrix inequalities and analyse the H∞,thinmathspaceL2−L∞, passivity, mixed H∞ and passivity, false(scriptQ,scriptS,scriptRfalse)‐dissipativity execution by choosing the weighting matrices can be solved simultaneously in a standard framework based on the idea of extended dissipative. Finally, simulation studies are given to verify the effectiveness of the derived results, among them one example was supported by the real‐life application of the benchmark problem in the sense of STD signals.

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H_{\infty}

control for T–S fuzzy systems with an adaptive event‐triggered communication scheme has been discussed in [32].…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Robust event‐triggered T–S fuzzy system with successive time‐delay signals and its application

Vadivel

Joo

2020

IET Control Theory & Appl

Self Cite

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“…A flexible manufacturing system can be applied either on static or dynamic system [11]. Robotic Flexible Manufacturing Systems can be used in many fields such as: medicine [12,13], thermodynamic domain [14], optimal numerisation [15], motion [16], assembly system [17], automotive [18], fuzzy system [19].…”

Section: Introductionmentioning

confidence: 99%

Multi-Robot based Control System

Gharbi¹

2021

IJACSA

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One of the most important challenge in Robotic Flexible Manufacturing Systems (RFMS) is how to develop a Multi-Robot based control system in which the robot is able to take intelligent decision to a changing environment. The problematic is how to ensure the flexibility with the proposed multi-robot based control system based on triggering strategies. The flexibility of the whole system is expanded by the capacity of the flexible robots to effectively ensure tasks assigned to it. Through this paper, three contributions can be presented: (i) the RFMS based Control Architecture by presenting in details the main components and methods, (ii) the planning model, and (iii) the different levels of flexibility in RFMS.

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Extended dissipative performance for a complex dynamical networks based on adaptive event‐triggered filter method subject to hybrid attacks

Tajudeen,

Ali,

Rajchakit

et al. 2023

Adaptive Control & Signal

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SummaryThe challenge of adaptive event‐triggered based filter design for complex dynamical networks with time‐varying coupling delays under hybrid attack is studied in this research. A new model of complex dynamical networks with input constraints, involving denial‐of‐service (DoS) attack, replay attack, and deception attack is designed. An adaptive event‐triggered scheme is applied to filter design, which adaptively modifies the communication threshold level in order to reduce the effect of the transmission load. By using Lyapunov theory and inequality techniques, a novel necessary condition is proposed that guarantees mean‐square asymptotically stability with extended dissipative performance. The proposed filter parameters are then given an explicit expression, which is solved using a set of linear matrix inequalities. Finally, two numerical results are presented to demonstrate the validity of the theoretical result suggested.

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Robust event-triggered reliable control for T-S fuzzy uncertain systems via weighted based inequality

Cited by 43 publications

References 45 publications

Robust event‐triggered T–S fuzzy system with successive time‐delay signals and its application

Robust event‐triggered T–S fuzzy system with successive time‐delay signals and its application

Multi-Robot based Control System

Extended dissipative performance for a complex dynamical networks based on adaptive event‐triggered filter method subject to hybrid attacks

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