Finite-Time Event-Triggered $\mathcal{H}_{\infty }$ Control for T–S Fuzzy Markov Jump Systems

Shen, Hao; Li, Feng; Yan, Huaicheng; Karimi, Hamid Reza; Lam, Hak‐Keung

doi:10.1109/tfuzz.2017.2788891

Cited by 426 publications

(139 citation statements)

References 50 publications

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“…Remark 7. Different from the LKF constructed in other works, 1,2,14,34,37 which need to be positive definite all the time, the LKF in this paper is only required to be positive definite at end points of each subinterval Π k,j . As a consequence, the obtained criterion has less conservatism. ]…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, aperiodic sampling ETCS presented in (2) is necessary and more reasonable. Additionally, the mode-dependent aperiodic sampling ETCS (2) becomes the mode-dependent periodic sampling ETCS in some works 1,2,31,37 when k ≡ and reduces to the common ETCS in other works [34][35][36] when k ≡ , ( (t)) = , Φ( (t)) = Φ ( and Φ are constant and constant matrix, respectively). The ETCS developed here is thus more general.…”

Section: Problem Description and Preliminariesmentioning

confidence: 99%

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Strictly dissipative stabilization of multiple‐memory Markov jump systems with general transition rates: A novel event‐triggered control strategy

Xie

Zhang

Zeng

et al. 2020

Intl J Robust & Nonlinear

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Summary This paper investigates the strictly dissipative stabilization problem for multiple‐memory Markov jump systems with network communication protocol. Firstly, for reducing data transmission, we put forward a novel mode‐dependent event‐triggered communication scheme based on aperiodically sampled data. Secondly, a Markov jump system with general transition rates is considered to make the result more applicable, where the transition rates of some jumping modes allow to be completely known, or partially known, or even completely unknown. Thirdly, a less restrictive Lyapunov‐Krasovskii functional, which is only required to be positive definite at end points of each subinterval of the holding intervals, is first introduced for event‐triggered control issue. Based on the above methods, a sufficient condition with less conservatism is obtained to ensure the stochastic stability and dissipativity of the resulting closed‐loop system. Meanwhile, an explicit design method of the desired controller is achieved. Finally, two numerical examples are presented to demonstrate the effectiveness and advantage of the proposed method.

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Section: Resultsmentioning

confidence: 99%

Section: Problem Description and Preliminariesmentioning

confidence: 99%

Strictly dissipative stabilization of multiple‐memory Markov jump systems with general transition rates: A novel event‐triggered control strategy

Xie

Zhang

Zeng

et al. 2020

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…In the recent years, event-triggered control has received increasing attention in real time control systems. Especially to the case of battery-powered wireless devices, reducing the number of network transmissions has an important effect on the battery lifespan [14,15]. Therefore, how to saving limited network resource is a significant and challenging task.…”

Section: Introductionmentioning

confidence: 99%

Synchronization of decentralized event-triggered uncertain switched neural networks with two additive time-varying delays

Vadivel

Ali

Alzahrani

et al. 2020

NAMC

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This paper addresses the problem of synchronization for decentralized event-triggered uncertain switched neural networks with two additive time-varying delays. A decentralized eventtriggered scheme is employed to determine the time instants of communication from the sensors to the central controller based on narrow possible information only. In addition, a class of switched neural networks is analyzed based on the Lyapunov-Krasovskii functional method and a combined linear matrix inequality (LMI) technique and average dwell time approach. Some sufficient conditions are derived to guarantee the exponential stability of neural networks under consideration in the presence of admissible parametric uncertainties. Numerical examples are provided to illustrate the effectiveness of the obtained results. and source are credited. Recently, a new type of systems with two additive time-varying delays were proposed in [8], and the stability problem was further discussed in [11]. In networked systems, signals are communicated from one point to another may experience two network segments, which can possibly produce two time-varying delays with different properties by cause of variable network transmission conditions [13,23,28]. Moreover, synchronization has been extensively studied due to its strong potential applications in engineering, such as secure communication, robot queue, and chemical reaction [10,27]. Synchronization strategies can have communication between nodes, which cause the network congestion and waste the network resources. In order to overcome the conservativeness of synchronization strategies, the event-triggered strategy is proposed. Many results have been reported in the literature for synchronization-based event-triggered problem [17,19,25]. In addition, to the best of our knowledge, synchronization of uncertain switched neural networks with two additive delay components via decentralized event-triggered scheme has not been completely investigated, which motivates the study of this paper.Based on the above discussions, in this paper, the problem of synchronization of decentralized event-triggered uncertain switched neural networks with two additive delay components is considered. By utilizing a novel Lyapunov-Krasovskii functional, integral techniques, some sufficient conditions are expressed in terms of linear matrix inequalities http://www.journals.vu.lt/nonlinear-analysis

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“…1,2 To this end, designing a controller to provide the desired performance for the considered system is a very essential and challenging task. On this basis, the research on different types of nonlinear control methods has been paid much attention in the past several decades, such as backstepping method, [3][4][5] adaptive technique, [6][7][8]  ∞ method, 9,10 fuzzy control, 11,12 and sliding mode control (SMC). [13][14][15] Among these nonlinear control methods, SMC has been regarded as one of the most effective approaches to handle the nonlinear uncertain systems because it exhibits the good properties on robustness against the uncertainties and simplicity in implementation.…”

Section: Introductionmentioning

confidence: 99%

A novel adaptive nonsingular terminal sliding mode controller design and its application to active front steering system

Ding

Liu

Park

2019

Intl J Robust & Nonlinear

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Summary Note that the amplitude of chattering existing in the sliding mode control method is proportional to the magnitude of the control gain. Therefore, the key issue to diminish the chattering is to decrease the value of sliding mode controller's gain to an acceptable minimal level defined by the so‐called reaching condition for the sliding mode's existence. For this reason, the nonsingular terminal sliding mode (NTSM) control method and the adaptive technique have been considered in this paper to develop a novel adaptive NTSM control method, which can be used to search the minimal value of the control gain automatically in the presence of the external disturbances. Meanwhile, the average value of a high‐frequency switching signal in the adaptive law can be provided by Arie Levant's differentiator rather than a low‐pass filter. The rigorous mathematical proof verifies that the system states can converge to the origin within a finite time under the proposed adaptive NTSM controller. Both the academic example and the practical application to an active front steering system are illustrated to show that the presented adaptive NTSM controller has better control performance than the conventional sliding mode controller.

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Finite-Time Event-Triggered $\mathcal{H}_{\infty }$ Control for T–S Fuzzy Markov Jump Systems

Cited by 426 publications

References 50 publications

Strictly dissipative stabilization of multiple‐memory Markov jump systems with general transition rates: A novel event‐triggered control strategy

Strictly dissipative stabilization of multiple‐memory Markov jump systems with general transition rates: A novel event‐triggered control strategy

Synchronization of decentralized event-triggered uncertain switched neural networks with two additive time-varying delays

A novel adaptive nonsingular terminal sliding mode controller design and its application to active front steering system

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