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Wuneng Zhou,Yan Gao,Dongbing Tong,Chuan Ji,Jian’an Fang 제어·로봇·시스템학회 2013 International Journal of Control, Automation, and Vol.11 No.4
In this letter, the analysis problem of adaptive exponential synchronization in pth moment is considered for neutral-type neural networks with time delays and Markovian switching. By utilizing a new nonnegative function and the M-matrix approach, several sufficient conditions to ensure the adaptive exponential synchronization in pth moment for neutral-type neural networks are derived. Via the adaptive feedback control techniques, some suitable parameters update laws are found. To illustrate the effectiveness of the M-matrix-based synchronization conditions derived in this letter, numerical example is provided finally.
Wuneng Zhou,Chuan Ji,Jinping Mou,Dongbing Tong,Yan Gao 제어·로봇·시스템학회 2013 International Journal of Control, Automation, and Vol.11 No.5
This article focuses on the problem of adaptive target synchronization for the Wireless Sensor Networks (WSNs). By applying the LaSalle-type invariance principle and the M-matrix approach for stochastic differential delay equations with Markovian switching, several sufficient conditions to ensure adaptive target synchronization and adaptive exponential target synchronization in pth moment for WSNs with Markov delays and stochastic noises are derived. We further investigate the adaptive exponential target synchronization in probabilistic sense for the WSNs and obtain the almost sure adaptive exponential target synchronization. Via the adaptive feedback control techniques, some suitable parameters update laws are attained. We finally show some numerical simulations to illustrate the effectiveness of the results derived in this paper.
Non-linear Feedback Control of a Novel Chaotic System
Wuneng Zhou,Zhong Li,Wolfgang A. Halang,Lin Pan 제어·로봇·시스템학회 2009 International Journal of Control, Automation, and Vol.7 No.6
From the classical Lü chaotic system a new simple three-dimensional autonomous system is derived, which exhibits a three-scroll chaotic attractor. An approach to control this novel attractor by non-linear feedback functions is proposed. The results obtained reveal that the trajectories of the chaotic attractor can be controlled to reach certain target periodic orbits or points. Finally, some numerical simulations are provided to show the effectiveness and feasibility of the controller design method developed.
Bipartite Containment Control for Multi-agent Systems Under Fixed and Markov Switching Topologies
Xuan Gu,Wuneng Zhou,You Wu,Wanpeng Wu,Guang Yang 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.4
The distributed bipartite containment control problem of a set of general linear multi-agent systems with structural balanced symbolic graph is studied. The containment control analysis of communication topology under fixed topology and Markov switching topologies are given. Different from the traditional multi-agent containment control, a distributed observer and bipartite containment protocol are designed based on relative neighbour information. Algebraic graph theory and Lyapunov stability theory are applied to make the bipartite containment error and estimation error converge to zero under the action of the containment control protocol, thus making follower agents converge asymptotically to the states of leader agents. Finally, the effectiveness of the theoretical method is verified by simulation examples.
Exponential Stability of Neural Networks with Markovian Switching Parameters and General Noise
Xin Zhang,Wuneng Zhou,Yuqing Sun 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.4
This paper investigates the problem of exponential stability of Neural Networks (NNs) with Markovianparameters and general noise. The model in this paper with general noise is more suitable for many real nervoussystems than NNs with white noise. Criteria for the exponential stability of the NNs with Markovian switchingparameters and general noise in both the mean square and p-th moment are derived by utilizing the random analysismethod and Lyapunov functional method techniques. The exponential stability of NNs without Markovian switchingis given as a special case. Finally, simulation result in two examples are discussed to illustrate the theoreticalresults.
Dongbing Tong,Wuneng Zhou,Han Wang 제어·로봇·시스템학회 2014 International Journal of Control, Automation, and Vol.12 No.5
This paper discusses the exponential state estimation problem for stochastic complex dynamical networks involving multi-delayed and adaptive control. A new approach, very different to the linear matrix inequality (LMI) method, has been developed to solve the above problem. Meanwhile, some sufficient conditions are derived to ensure the exponential stability in pth moment for the dynamics of state estimator error. The feedback gain update law is found by the adaptive control technique. An il-lustrative example is provided to show the usefulness and effectiveness of the proposed design method.
Dynamics Analysis of a New Simple Chaotic Attractor
Lin Pan,Wuneng Zhou,Jian’an Fang 제어·로봇·시스템학회 2010 International Journal of Control, Automation, and Vol.8 No.2
In this paper, a novel simple chaotic system is discussed. Some basic dynamical properties, such as Lyapunov exponents, Poincaré mapping, fractal dimension, bifurcation diagram, continuous spectrum and chaotic dynamical behaviors of the novel chaotic system are studied, either numerically or analytically. The obtained results show clearly that the system discussed in this Letter is a novel chaotic system and deserves a further detailed investigation.
Yuhua Xu,Wuneng Zhou,Jian-an Fang 제어·로봇·시스템학회 2012 International Journal of Control, Automation, and Vol.10 No.2
To simulate more realistic networks, we introduce a complex dynamical network model with double non-delayed and double delayed coupling and further investigate its synchronization phenomenon in this paper. Based on Lyapunov stability theory, adaptive synchronization criteria is obtained. Analytical result shows that under the designed adaptive controllers, the complex dynamical network with double non-delayed and double delayed coupling can asymptotically synchronize to a given trajectory. What is more, the coupling matrix is not assumed to be symmetric or irreducible. Finally, simulation results show the method is effective.
Dongbing Tong,Liping Zhang,Wuneng Zhou,Jun Zhou,Yuhua Xu 제어·로봇·시스템학회 2016 International Journal of Control, Automation, and Vol.14 No.3
In this paper, the problem of the adaptive synchronization control is considered for neural networkswith uncertainty and stochastic noise. Via utilizing stochastic analysis method and linear matrix inequality (LMI)approach, several sufficient conditions to ensure the adaptive synchronization for neural networks are derived. Bythe adaptive feedback methods, some suitable parameters update laws are found. Finally, a simulation result isprovided to substantiate the effectiveness of the proposed approach.
Shuang Liu,Chunmei Duan,Wuneng Zhou 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.9
This paper deals with the stochastic stability problem of the closed-loop system under deception attacks based on an adaptive event-triggering scheme (AETS) with saturation constraint. Some novel stability criteria related to networked control systems under deception attacks are devised by taking the fixed threshold which is difficult to adapt to changeable systems into account. An adaptive event-triggering scheme with saturation constraint involving a threshold variable with system states is proposed to reduce network load, and the desired controller gain matrix is obtained by employing the linear matrix inequalities (LMIs) technique. Moreover, the LyapunovKrasovskii method is used to obtain sufficient conditions for ensuring the stability of the system. In the end, the simulation results are shown to indicate the validity of the proposed method.