Finite-time synchronization of time-delayed neural networks with unknown parameters via adaptive control

Li, Shanqiang; Peng, Xiuyan; Tang, Yu; Shi, Yujing

doi:10.1016/j.neucom.2018.04.053

Cited by 38 publications

(24 citation statements)

References 38 publications

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“…(2) = 1.2,̃(̃̃( )) = [0, 0] and̃(⋅, ⋅) shown in equality (39). Substituting these parameters into Assumption 4, it is derived that Assumption 4 holds.…”

Section: Remark 26 Inmentioning

confidence: 99%

“…How to get * ? In this situation, finite-time problems of many systems have been attracting increasing interest [31][32][33][34][35][36][37][38][39][40][41][42]. For example, Liu et al [31] investigated finite/fixedtime synchronization of complex networks with stochastic disturbances.…”

Section: Introductionmentioning

confidence: 99%

“…In [34], finite-time robust passive control for a class of switched reaction-diffusion stochastic complex dynamical networks with coupling delays and impulsive control was considered. According to the obtained results of [31][32][33][34][35][36][37][38][39][40][41][42], it is observed that in some effective finite-time * estimation approaches for synchronization, passivity, and consensus, the proposed systems were derived. Unfortunately, to our knowledge, few researchers focused attention on finite-time synchronization of linear or nonlinear coupled Markovian switching multiweighted complex networks.…”

Section: Introductionmentioning

confidence: 99%

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Finite‐Time Synchronization and Synchronization Dynamics Analysis for Two Classes of Markovian Switching Multiweighted Complex Networks from Synchronization Control Rule Viewpoint

et al. 2019

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This paper is mainly concerned with how nonlinear coupled one impacts synchronization dynamics of a class of nonlinear coupled Markovian switching multiweighted complex networks (NCMSMWCNs). Firstly, sufficient conditions of finite-time synchronization for a class of NCMSMWCNs and a class of linear coupled Markovian switching multiweighted complex networks (LCMSMWCNs) are investigated. Secondly, based on the derived results, how nonlinear coupled one affects synchronization dynamics of the NCMSMWCNs is analyzed from synchronization control rule. Thirdly, in order to further explore how nonlinear coupled one affects synchronization dynamics of the NCMSMWCNs, synchronization dynamics relationship of the NCMSMWCNs and the LCMSMWCNs is built. Furthermore, this relationship can also show how linear coupled one affects synchronization dynamics of the LCMSMWCNs. At last, numerical examples are provided to demonstrate the effectiveness of the obtained theory.

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“…(2) = 1.2,̃(̃̃( )) = [0, 0] and̃(⋅, ⋅) shown in equality (39). Substituting these parameters into Assumption 4, it is derived that Assumption 4 holds.…”

Section: Remark 26 Inmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Finite‐Time Synchronization and Synchronization Dynamics Analysis for Two Classes of Markovian Switching Multiweighted Complex Networks from Synchronization Control Rule Viewpoint

et al. 2019

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“…Consequently, in practical applications, more attention is paid to what happens on a finite-time interval rather than an infinite-time interval. Recently, many research results on finite-time control of time-delay systems have been derived [28][29][30][31][32][33][34][35].However, it is not difficult to see that the existing results mainly focus on the finite-time dissipative control for stochastic interval systems with time delay, or Lyapunov stability of stochastic systems with time delay. To the best of our knowledge, the problems of finite-time stability for stochastic delay interval systems have not been fully considered, which motivates this study.…”

mentioning

confidence: 99%

mentioning

confidence: 99%

Finite-Time Stabilization for Stochastic Interval Systems with Time Delay and Application to Energy-Storing Electrical Circuits

2019

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In this paper, the problem of stochastic finite-time stabilization is investigated for stochastic delay interval systems. A nonlinear state feedback controller with input-to-state delay is introduced. By employing the Lyapunov-Krasovskii functional method, some sufficient conditions on stochastic finite-time stabilization are derived for closed-loop stochastic delay interval systems using the Itô's differential formula. Suitable nonlinear state feedback controllers can be designed in terms of linear matrix inequalities. The obtained results are finally applied to an energy-storing electrical circuit to illustrate the effectiveness of the proposed method.Electronics 2019, 8, 175 2 of 17 conditions were established in Reference [17]. The robust input-to-state stability of neural networks with Markovian switching in the presence of random disturbances or time delays was studied in Reference [18]. The stability analysis of semi-Markov switched stochastic systems was introduced in Reference [20]. The finite frequency approach to controlling Markov jump linear systems with incomplete transition probabilities was investigated in Reference [23].In addition, It is worth noting that most of the existing results on stability are focused on Lyapunov stability defined on an infinite-time interval [24,25]. Compared with Lyapunov stability, finite-time stability is such a stability property that the system states approach zero at a finite time instant rather than infinity [26,27]. It should be pointed out that finite-time stability systems might have not only faster convergence but also better robustness and disturbance rejection capabilities. Consequently, in practical applications, more attention is paid to what happens on a finite-time interval rather than an infinite-time interval. Recently, many research results on finite-time control of time-delay systems have been derived [28][29][30][31][32][33][34][35].However, it is not difficult to see that the existing results mainly focus on the finite-time dissipative control for stochastic interval systems with time delay, or Lyapunov stability of stochastic systems with time delay. To the best of our knowledge, the problems of finite-time stability for stochastic delay interval systems have not been fully considered, which motivates this study. Meanwhile, more and more applications related to energy-storing electrical circuits are appearing everywhere playing an increasingly important part in our lives and in industrial production. Up to now, a lot of investigations on energy-storing electrical circuits have been published, e.g., finite-time control [36], stability [37], and passivity [38,39]. However, in the existing results related to energy-storing electrical circuits, the stochastic disturbance is not considered, and the values of electronic components are exact. This is almost impossible in practical energy-storing electrical circuits.This paper aims to investigate the finite-time stabilization problem of stochastic delay interval systems. To tackle this problem, a nonlinea...

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Predefined‐time adaptive fuzzy tracking control for switched nonlinear systems

Jin,

Wang,

Zhao

2024

Asian Journal of Control

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The paper focuses on the issue of predefined‐time adaptive fuzzy tracking control for switched nonlinear systems. The complicated unknown nonlinear function is approximated by utilizing the fuzzy logic system. A novel adaptive fuzzy control scheme is proposed by using the common Lyapunov function and backstepping technology on the basis of the definition of predefined‐time stability, which can preset the setting time of tracking errors. The findings indicate that the presented controller can ensure that all signals remain bounded in the closed‐loop system under arbitrary switching conditions, and the tracking error can converge to the neighborhood near the origin within a predefined time. The feasibility of the developed control approach is further proved through an example of numerical simulation.

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Finite-time synchronization of time-delayed neural networks with unknown parameters via adaptive control

Cited by 38 publications

References 38 publications

Finite‐Time Synchronization and Synchronization Dynamics Analysis for Two Classes of Markovian Switching Multiweighted Complex Networks from Synchronization Control Rule Viewpoint

Finite‐Time Synchronization and Synchronization Dynamics Analysis for Two Classes of Markovian Switching Multiweighted Complex Networks from Synchronization Control Rule Viewpoint

Finite-Time Stabilization for Stochastic Interval Systems with Time Delay and Application to Energy-Storing Electrical Circuits

Predefined‐time adaptive fuzzy tracking control for switched nonlinear systems

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