Global Nonfragile Synchronization in Finite Time for Fractional-Order Discontinuous Neural Networks With Nonlinear Growth Activations

Peng, Xiao; Cao, Jinde

doi:10.1109/tnnls.2018.2876726

Cited by 116 publications

(36 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this section, by designing the controller u(t), we propose some synchronization conditions in terms of LMIs between system (17) and (18). First, we design the following state feedback controller:…”

Section: Resultsmentioning

confidence: 99%

“…Synchronization, which is a fundamental phenomenon of dynamical behavior in network systems, has been extensively studied in the past few decades, thus, a large number of results on synchronization have been reported, such as exponential synchronization, adaptive synchronization, lag synchronization, fixed/finite-time synchronization, projective synchronization, complete synchronization, and cluster synchronization, dissipativity synchronization, H-infinity synchronization. [16][17][18][19][20][21][22][23][24][25][26] In Reference 16, the authors investigated the global exponential synchronization problem for CVDNs by exploiting delayed impulsive control under stochastic perturbations. In Reference 17, the authors considered the global finite-time synchronization for fractional-order discontinuous neural networks by the nonfragile control approach.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Fixed‐time synchronization for discontinuous delayed complex‐valued networks with semi‐Markovian switching and hybrid couplings via adaptive control

Liu

Cao

2020

Adaptive Control & Signal

Self Cite

View full text Add to dashboard Cite

In this article, the global fixed-time synchronization issue is considered for semi-Markovian switching discontinuous complex-valued dynamical networks (CVDNs) with hybrid couplings and time-varying delays, in which CVDNs are not divided into two real value systems, contrary to existing literature. First, a new fixed-time convergence principle for complex-valued nonlinear system with semi-Markovian switching is developed. Second, to realize the fixed-time synchronization, the state feedback controller with integral term and adaptive controller are designed, respectively. Under the complex-valued differential inclusions framework, by utilizing Lyapunov-Krasovskii functional method and inequality analysis technique, the global fixed-time synchronization conditions are addressed in terms of linear matrix inequalities. Finally, two numerical simulations are given to illustrate the validity of the presented theoretical results.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fixed‐time synchronization for discontinuous delayed complex‐valued networks with semi‐Markovian switching and hybrid couplings via adaptive control

Liu

Cao

2020

Adaptive Control & Signal

Self Cite

View full text Add to dashboard Cite

show abstract

“…The problem of finitetime guaranteed cost control for FONNs was considered in Thuan et al (2018). Recently, problem of global nonfragile synchronization in finite time for fractional-order discontinuous neural networks with nonlinear growth activations functions has been studied in Peng et al (2019) using nonsmooth analysis method combined with Lur'e Postnikov-type Lyapunov functional.…”

Section: Introductionmentioning

confidence: 99%

Finite-time $$H_{\infty }$$ control of uncertain fractional-order neural networks

Thuận

Huyền

2020

Comp. Appl. Math.

View full text Add to dashboard Cite

The problem of finite-time H ∞ control for uncertain fractional-order neural networks is investigated in this paper. Using finite-time stability theory and the Lyapunov-like function method, we first derive a new condition for problem of finite-time stabilization of the considered fractional-order neural networks via linear matrix inequalities (LMIs). Then a new sufficient stabilization condition is proposed to ensure that the resulting closed-loop system is not only finite-time bounded but also satisfies finite-time H ∞ performance. Three examples with simulations have been given to demonstrate the validity and correctness of the proposed methods. Keywords Fractional order neural networks • Finite-time boundedness • H ∞ control problem • Linear matrix inequalities

show abstract

“…It is known to us all, time delays are often inevitable due to internal or external uncertainties in signal transmission. And the produced time delays may cause the stability of the system and even results in oscillation, divergence, and instability phenomena 27‐30 . Thus, much achievement has been devoted to analyze dynamic behaviors of MNNs with various types of time delays (see, eg, References 6 and 31‐35).…”

Section: Introductionmentioning

confidence: 99%

New results on stability analysis and extended dissipative conditions for uncertain memristive neural networks with two additive time‐varying delay components and reaction‐diffusion terms

Cao

Xiong

et al. 2020

Intl J Robust & Nonlinear

Self Cite

View full text Add to dashboard Cite

This article deals with the problems of exponential stability and extended dissipative analysis for a class of uncertain memristive neural networks (MNNs) with additive time-varying delays and reaction-diffusion terms. On the basis of generalized Lyapunov functional approach, Hardy-Poincarè inequality, Jensen's inequality, as well as some other inequality techniques, it is shown that the issues of exponential stability and extended dissipativity for the uncertain reaction-diffusion MNNs are solvable if a set of linear matrix inequalities (LMIs) proposed are feasible. As a special case, the conditions on exponential stability and extended dissipativity for the uncertain MNNs with additive time-varying delays are also obtained and given in terms of nonlinear matrix inequalities (NMIs). The obtained NMIs can be transformed as general LMIs via using a new quadratic convex combination skill. Moreover, the developed sufficient conditions for the uncertain delayed MNNs with and without reaction-diffusion terms can be easily checked by Matlab LMI control toolbox, and three numerical examples with simulation are provided to show the effectiveness and applicability of the theoretical results.

show abstract

Global Nonfragile Synchronization in Finite Time for Fractional-Order Discontinuous Neural Networks With Nonlinear Growth Activations

Cited by 116 publications

References 47 publications

Fixed‐time synchronization for discontinuous delayed complex‐valued networks with semi‐Markovian switching and hybrid couplings via adaptive control

Fixed‐time synchronization for discontinuous delayed complex‐valued networks with semi‐Markovian switching and hybrid couplings via adaptive control

Finite-time $$H_{\infty }$$ control of uncertain fractional-order neural networks

New results on stability analysis and extended dissipative conditions for uncertain memristive neural networks with two additive time‐varying delay components and reaction‐diffusion terms

Contact Info

Product

Resources

About