Output tracking control of delayed switched systems via state-dependent switching and dynamic output feedback

Yang, Dan; Li, Xiaodi; Qiu, Jianlong

doi:10.1016/j.nahs.2019.01.006

Cited by 210 publications

(95 citation statements)

References 41 publications

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“…In recent times, differential equation and fractional differential equation models have found their applications in a variety of fields including biology [1][2][3][4][5][6], physics [7][8][9][10], engineering [11][12][13][14], mathematics [15][16][17][18], information technology, and so on [19][20][21][22][23][24][25][26][27]. They are also one of the most rudimentary tools for neural networks.…”

Section: Introduction and Modelingmentioning

confidence: 99%

Finite-time synchronization criterion of graph theory perspective fractional-order coupled discontinuous neural networks

et al. 2020

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In this research work, the finite-time synchronization and adaptive finite-time synchronization criterion of graph theory perspective fractional-order coupled discontinuous neural networks (FCDNNs) are investigated under two different control strategies. By utilizing differential inclusion theory, Filippov framework, suitable Lyapunov functional, and graph theory approach, several sufficient criteria based on discontinuous state feedback control protocol and discontinuous adaptive feedback control protocol are established for ensuring the finite-time synchronization and adaptive finite-time synchronization of FCDNNs. Finally, two numerical cases illustrate the efficiency of the proposed finite-time synchronization results.

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Section: Introduction and Modelingmentioning

confidence: 99%

Finite-time synchronization criterion of graph theory perspective fractional-order coupled discontinuous neural networks

et al. 2020

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“…Time delays, which always cause instability and degrade performance, are ubiquitously present in many NNs due to the signal transmission (see [1,12] and references therein). Switched systems, which provide a unified framework for mathematical modeling of many physical or man-made systems displaying switching features, such as power electronics, flight control systems, network control systems, have been widely studied recently [5,22,23]. The switched system consists of a collection of subsystems and a switching signal governing the switching among them.…”

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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“…As is well known, the time delays can influence the dynamic of systems seriously and may cause some unstable performances such as divergence, oscillation or chaotic. Over the past few years, a great number of research papers have been published to focus on the stability and stabilization of dynamical systems with time delays (see [1][2][3][4][5][6] and the references cited therein). At the same time, it should be mentioned that under some exogenous disturbances, the system states may evolve in a bounded domain rather than converge to an equilibrium point, which indicates that the conventional stability cannot be realized.…”

Section: Introductionmentioning

confidence: 99%

“…(1) The RISpS property is, for the first time, proposed to evaluate the dynamical behaviors for a class of uncertain delayed systems with disturbances, which is quite different from and more comprehensive than the ISS properties investigated in [7-10, 12, 13, 15, 34-36] and the robust stability studied in [16][17][18][19][20][21][22][23][24][25][26][27]. (2) Several previous literature such as [1,3,6,11,23,27] required that the control signal updates continuously with time, which may lead to the unnecessary cost of network resources. In this paper, the event-triggered scheme is introduced to generates a sporadic control sequence while maintaining the desired ISpS dynamical performance for all admissible uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Event-based robust stabilization for delayed systems with parameter uncertainties and exogenous disturbances

2020

Adv Differ Equ

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In this paper, the robust stabilization problem is studied for a class of delayed systems with parameter uncertainties and unknown-but-bounded exogenous disturbances. The robust input-to-state practical stability (RISpS) is introduced to characterize the dynamics of the controlled system. An event-triggered strategy is employed to effectively decrease the transmission consumption of the robust controller. The Zeno behavior is also excluded by combining the information of delayed states with parameter uncertainties. The gain matrix and the event-triggered parameters are co-designed by resorting to the feasibility of several matrix inequalities. An example and its simulations are given to illustrate the proposed approach.

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Output tracking control of delayed switched systems via state-dependent switching and dynamic output feedback

Cited by 210 publications

References 41 publications

Finite-time synchronization criterion of graph theory perspective fractional-order coupled discontinuous neural networks

Finite-time synchronization criterion of graph theory perspective fractional-order coupled discontinuous neural networks

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

Event-based robust stabilization for delayed systems with parameter uncertainties and exogenous disturbances

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