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Adaptive Synchronization of Unknown Complex Dynamical Networks with Derivative and distributed time-varying delay Couplings

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INTERNATIONAL JOURNAL OF FUZZY SYSTEMS 2018年第4期20卷 1088-1097页

作者： Yuan, Xinxin Li, Junmin Li, Jinsha Xidian Univ Sch Math & Stat 245 Xidian Univ Xian 710126 Shanxi Peoples R China

This paper investigates the synchronization problem of unknown non-identical complex dynamical networks with derivative and distributed time-delay couplings. To deal with the unknown topological structure, a new general class of T-S fuzzy model is proposed in this paper. Then, the unknown network is presented by a fuzzy system. In order to achieve synchronization of the above fuzzy network, this paper designs a fuzzy adaptive feedback controller which is only connected with the dynamical behavior of directly related nodes. Meanwhile, a new class of fuzzy Lyapunov function is constructed in this paper. The sufficient asymptotic synchronization condition is obtained in terms of linear matrix inequality. Numerical example is given to demonstrate the effectiveness of the proposed theoretical results.

关键词： T-S fuzzy model Adaptive synchronization Derivative coupling distributed time-varying delay Feedback control

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Dynamic Self-Triggered Impulsive Synchronization of Complex Networks With Mismatched Parameters and distributed delay

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IEEE TRANSACTIONS ON CYBERNETICS 2023年第2期53卷 887-899页

作者： Ding, Dong Tang, Ze Park, Ju H. Wang, Yan Ji, Zhicheng Jiangnan Univ Minist Educ Key Lab Adv Proc Control Light Ind Wuxi 214122 Jiangsu Peoples R China Jiangnan Univ Sch Internet Things Engn Wuxi 214122 Jiangsu Peoples R China Yeungnam Univ Dept Elect Engn Gyongsan 38541 South Korea

Synchronization of complex networks with nonlinear couplings and distributed time-varying delays is investigated in this article. Since the mismatched parameters of individual systems, a kind of leader-following quasisynchronization issues is analyzed via impulsive control. To acquire appropriate impulsive intervals, the dynamic self-triggered impulsive controller is devoted to predicting the available instants of impulsive inputs. The proposed controller ensures the control effects while reducing the control costs. In addition, the updating laws of the dynamic parameter is settled in consideration of error bounds to adapt to the quasisynchronization. With the utilization of the Lyapunov stability theorem, comparison method, and the definition of average impulsive interval, sufficient conditions for realizing the synchronization within a specific bound are derived. Moreover, with the definition of average impulsive gain, the parameter variation scheme is extended from the fixed impulsive effects case to the time-varying impulsive effects case. Finally, three numerical examples are given to show the effectiveness and the superiority of proposed mathematical deduction.

关键词： Synchronization delays Couplings Complex networks Monitoring Protocols Mathematical models Dynamic self-triggered mechanism distributed time-varying delay extended parameter variation scheme quasisynchronization

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Exponential stability of switched positive systems with unstable modes and distributed delays

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JOURNAL OF THE FRANKLIN INSTITUTE 2022年第1期359卷 66-83页

作者： Zhou, Zi-Yu Wang, Yan-Wu Yang, Wu Hu, Meng-Jie Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Minist Educ Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Elect & Elect Engn Wuhan 430074 Peoples R China Yeungnam Univ Dept Elect Engn Gyongsan 38541 South Korea

This paper studies the exponential stability of switched positive system consisting of unstable subsystems with distributed time-varying delay. Unlike the existing results concerning delays, switching behaviors dominating the system can be either stabilizing or destabilizing. The distributed delay is supposed to be slowly varying and upper-bounded. To tackle the difficulties brought by both the switching behaviors with mixed effects and the distributed delay, a multiple discretized Lyapunov-Krasovskii functional is employed to derive sufficient conditions for the exponential stability of the system. Specifically, by adjusting the ratio of the stabilizing switching behaviors, the state divergence caused by unstable subsystems and destabilizing switching behaviors can be compensated. Simulation examples demonstrate the effectiveness of the results. (c) 2021 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

关键词： Switched positive system unstable mode distributed time-varying delay Lyapunov-Krasovskii functional

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delay-dependent stability criteria of uncertain Markovian jump neural networks with discrete interval and distributed time-varying delays

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NEUROCOMPUTING 2015年 158卷 167-173页

作者： Ali, M. Syed Arik, Sabri Saravanakurnar, R. Thiruvalluvar Univ Dept Math Vellore 632115 Tamil Nadu India Istanbul Univ Dept Comp Engn TR-34320 Istanbul Turkey

In this paper, a class of uncertain neural networks with discrete interval and distributed time-varying delays and Markovian jumping parameters (MJPs) are carried out. The Markovian jumping parameters are modeled as a continuous-time, finite-state Markov chain. By using the Lyapunov-Krasovskii functionals (LKFs) and linear matrix inequality technique, some new delay-dependent criteria is derived to guarantee the mean-square asymptotic stability of the equilibrium point. Numerical simulations are given to demonstrate the effectiveness of the proposed method. The results are also compared with the existing results to show the less conservativeness. (C) 2015 Elsevier B.V. All rights reserved.

关键词： distributed time-varying delay Interval time-varying delay Linear matrix inequality (LMI) Markovian jumping parameters Neural networks

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delay-dependent dissipativity of neural networks with mixed non-differentiable interval delays

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NEUROCOMPUTING 2017年 267卷 85-94页

作者： Lv, Xiaoxiao Li, Xiaodi Shandong Normal Univ Sch Math & Stat Jinan 250014 Shandong Peoples R China Shandong Normal Univ Inst Data Sci & Technol Jinan 250014 Shandong Peoples R China

This paper investigates the global dissipativity and globally exponential dissipativity for neural networks with both interval time-varying delays and interval distributed time-varying delays. By constructing a set of appropriated Lyapunov-Krasovskii functionals and employing Newton-Leibniz formulation and free weighting matrix method, some dissipativity criteria that are dependent on the upper and lower bounds of the time-varying delays are derived in terms of linear matrix inequalities (LMIs), which can be easily verified via the LMI toolbox. Moreover, a positive invariant and globally attractive set is derived via the established LMIs. Finally, two numerical examples and their simulations are provided to demonstrate the effectiveness of the proposed criteria. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Neural networks Dissipativity Linear matrix inequality Interval time-varying delay distributed time-varying delay

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Adaptive backstepping neural control of state-delayed nonlinear systems with full-state constraints and unmodeled dynamics

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INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING 2017年第11期31卷 1704-1722页

作者： Zhang, Tianping Xia, Meizhen Zhu, Jiaming Yangzhou Univ Coll Informat Engn Dept Automat Yangzhou 225127 Jiangsu Peoples R China

In this paper, the problem of adaptive neural control is discussed for a class of strict-feedback time-varying delays nonlinear systems with full-state constraints and unmodeled dynamics, as well as distributed time-varying delays. The considered nonlinear system with full-state constraints is transformed into a nonlinear system without state constraints by introducing a one-to-one asymmetric nonlinear mapping. Based on modified backstepping design and using radial basis function neural networks to approximate the unknown smooth nonlinear function and using a dynamic signal to handle dynamic uncertainties, a novel adaptive backstepping control is developed for the transformed system without state constraints. The uncertain terms produced by state time delays and distributed time delays are compensated for by constructing appropriate Lyapunov-Krasovskii functionals. All signals in the closed-loop system are proved to be semiglobally uniformly ultimately bounded. A numerical example is provided to illustrate the effectiveness of the proposed design scheme.

关键词： adaptive control distributed time-varying delay neural networks nonlinear systems state constraints unmodeled dynamics

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New Filter Design for Static Neural Networks with Mixed time-varying delays 12th

New Filter Design for Static Neural Networks with Mixed Time...

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12th International Conference on Intelligent Computing (ICIC)

作者： Liu, Guoquan Zhou, Shumin Luo, Xianxi Zhang, Keyi East China Univ Technol Jiangxi Prov Engn Res Ctr New Energy Technol & Eq Nanchang 330013 Peoples R China

ISBN: (纸本)9783319422947;9783319422930

This paper focuses on designing a H-infinity filter for a class of static neural networks with mixed time-varying delays. Here the mixed time-varying delays contain both discrete and distributed time-varying delays. Based on a Lyapunov-Krasovskii functional combined with a zero equation, a suitable H-infinity filter is obtained for the static neural networks model. The filter can be solved by a linear matrix inequality (LMI). Two numerical examples are presented to validate the proposed method. In addition, the obtained filter can be applied to design the control systems with delays.

关键词： Filter design Static neural networks Lyapunov-Krasovskii functional distributed time-varying delay

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H_∞ state estimation of stochastic neural networks with mixed time-varying delays

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SOFT COMPUTING 2016年第9期20卷 3475-3487页

作者： Saravanakumar, R. Ali, M. Syed Hua, Mingang Thiruvalluvar Univ Dept Math Vellore 632115 Tamil Nadu India Hohai Univ Coll Internet Things Engn Changzhou 213022 Peoples R China

This paper is concerned with state estimation problem of stochastic neural networks with discrete interval and distributed time-varying delays. The time-varying delay is need to be bounded and continuous. By constructing a suitable Lyapunov-Krasovskii functional with triple integral terms and linear matrix inequality technique, the delay-dependent criteria are conferred so that the error system is stochastically asymptotically mean-square stable with performance. The desired estimator gain matrix can be characterized in terms of the solution to linear matrix inequalities, which can be easily solved by some standard numerical algorithms. Numerical simulations are given to demonstrate the effectiveness of the proposed method. The results are also compared with existing methods.

关键词： distributed time-varying delay H-infinity state estimation Interval time-varying delay Linear matrix inequality Stochastic neural networks

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Improved H_∞ Performance Analysis of Uncertain Markovian Jump Systems with Overlapping time-varying delays

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COMPLEXITY 2016年第S1期21卷 460-477页

作者： Ali, M. Syed Saravanakumar, R. Thiruvalluvar Univ Dept Math Vellore 632115 Tamil Nadu India

In this article, we study the problem of robust H-infinity performance analysis for a class of uncertain Markovian jump systems with mixed overlapping delays. Our aim is to present a new delay-dependent approach such that the resulting closed-loop system is stochastically stable and satisfies a prescribed H-infinity performance level chi. The jumping parameters are modeled as a continuous-time, finite-state Markov chain. By constructing new Lyapunov-Krasovskii functionals, some novel sufficient conditions are derived to guarantee the stochastic stability of the equilibrium point in the mean-square. Numerical examples show that the obtained results in this article is less conservative and more effective. The results are also compared with the existing results to show its conservativeness. (C) 2016 Wiley Periodicals, Inc.

关键词： distributed time-varying delay interval time-varying delay H-infinity performance analysis linear matrix inequality Markovian jumping parameters overlapping delays

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Robust exponential synchronization for neutral complex networks with discrete and distributed time-varying delays: A descriptor model transformation method

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OPTIMAL CONTROL APPLICATIONS & METHODS 2014年第6期35卷 676-695页

作者： He, Ping Zhang, Qingling Jing, Chun-Guo Chen, Chang-Zhong Fan, Tao Northeastern Univ Sch Informat Sci & Engn Shenyang 110819 Liaoning Peoples R China Northeastern Univ Inst Syst Sci Shenyang 110819 Liaoning Peoples R China Northeastern Univ Qinhuangdao Sch Comp & Commun Engn Qinhuangdao 066004 Herts Peoples R China Sichuan Univ Sci & Engn Sch Automat & Elect Informat Zigong 643000 Sichuan Peoples R China Sichuan Univ Sci & Engn Artificial Intelligence Key Lab Sichuan Prov Zigong 643000 Sichuan Peoples R China

In this paper, the robust exponential synchronization problem for a class of neutral complex networks with discrete and distributed time-varying delays is investigated. Some delay-dependent synchronization criteria are derived by using the descriptor model transformation method;the stability condition of error dynamical networks based on the Lyapunov-Krasovskii functional is obtained via linear matrix inequality (LMI) formulation. Finally, numerical examples are presented to show the effectiveness of the proposed theoretical results. Copyright (c) 2013 John Wiley & Sons, Ltd.

关键词： complex network robust exponential synchronization neutral time-varying delay discrete time-varying delay distributed time-varying delay descriptor model transformation LMI

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