The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Ju H Park - One of the best experts on this subject based on the ideXlab platform.
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further results on stabilization of chaotic systems based on fuzzy memory sampled data control
IEEE Transactions on Fuzzy Systems, 2018Co-Authors: Ju H ParkAbstract:This note investigates sampled-data control for chaotic systems. A memory sampled-data control scheme that involves a constant signal transmission delay is employed for the first time to tackle the stabilization problem for Takagi–Sugeno fuzzy systems. The advantage of the constructed Lyapunov Functional lies in the fact that it is neither necessarily positive on sampling intervals nor necessarily continuous at sampling instants. By introducing a modified Lyapunov Functional that involves the state of a constant signal transmission delay, a delay-dependent stability criterion is derived so that the closed-loop system is asymptotically stable. The desired sampled-data controller can be achieved by solving a set of linear matrix inequalities. Compared with the existing results, a larger sampling period is obtained by this new approach. A simulation example is presented to illustrate the effectiveness and conservatism reduction of the proposed scheme.
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a novel Lyapunov Functional for stability of time varying delay systems via matrix refined function
Automatica, 2017Co-Authors: Tae H Lee, Ju H ParkAbstract:This paper is concerned with the development of novel stability criteria for time-varying delayed systems. To this end, a new function which consisted of two quadratic functions with a special structural matrix is established to be a Lyapunov Functional candidate. The proposed Lyapunov Functional plays key role to decrease the conservatism of derived conditions which is verified by three numerical examples.
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stability analysis of sampled data systems via free matrix based time dependent discontinuous Lyapunov approach
IEEE Transactions on Automatic Control, 2017Co-Authors: Tae H Lee, Ju H ParkAbstract:In this paper, a new time-dependent discontinuous Lyapunov Functional, namely, free-matrix-based time-dependent discontinuous (FMBTDD) Lyapunov Functional is introduced for stability analysis of sampled-data systems. First, a modified free-matrix-based integral inequality (MFMBII) is derived based on the existing free-matrix-based integral inequality [1] and it is applied to develop a stability criterion for sampled-data systems. And then, inspired by MFMBII, FMBTDD term is established that leads to efficient stability conditions. Four numerical examples are given to demonstrate the effectiveness of the proposed methods.
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further results on sampled data control for master slave synchronization of chaotic lur e systems with time delay
Nonlinear Dynamics, 2015Co-Authors: Shenping Xiao, Hongbing Zeng, Ju H Park, Yajuan LiuAbstract:This paper is concerned with the problem of sampled-data control for master–slave synchronization of chaotic Lur’e systems with time delay. The sampling periods are assumed to be arbitrary but bounded. A new Lyapunov Functional is constructed, in which the information on the nonlinear function and the actual sampling pattern have been taken fully into account. By employing the Lyapunov Functional and a tighter bound technique to estimate the derivative of the Lyapunov Functional, a less conservative exponential synchronization criterion is established by analyzing the corresponding synchronization error systems. Furthermore, the derived condition is employed to design a sampled-data controller. The desired controller gain matrix can be obtained by means of the linear matrix inequality approach. Simulations are provided to show the effectiveness and the advantages of the proposed approach.
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state estimator for neural networks with sampled data using discontinuous Lyapunov Functional approach
Nonlinear Dynamics, 2013Co-Authors: S Lakshmanan, Ju H Park, R Rakkiyappan, Hoyoul JungAbstract:In this paper, the sampled-data state estimation problem is investigated for neural networks with time-varying delays. Instead of the continuous measurement, the sampled measurement is used to estimate the neuron states, and a sampled data estimator is constructed. Based on the extended Wirtinger inequality, a discontinuous Lyapunov Functional is introduced, which makes full use of the sawtooth structure characteristic of sampling input delay. New delay-dependent criteria are developed to estimate the neuron states through available output measurements such that the estimation error system is asymptotically stable. The criteria are formulated in terms of a set of linear matrix inequalities (LMIs), which can be checked efficiently by use of some standard numerical packages. Finally, a numerical example and its simulations are given to demonstrate the usefulness and effectiveness of the presented results.
Hongbing Zeng - One of the best experts on this subject based on the ideXlab platform.
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a new Lyapunov Functional approach to sampled data synchronization control for delayed neural networks
Journal of The Franklin Institute-engineering and Applied Mathematics, 2018Co-Authors: Shenping Xiao, Honghai Lian, Hongbing Zeng, Kok Lay Teo, Xiaohu ZhangAbstract:Abstract This paper discusses the problem of synchronization for delayed neural networks using sampled-data control. We introduce a new Lyapunov Functional, called complete sampling-interval-dependent discontinuous Lyapunov Functional, which can adequately capture sampling information on both intervals from r ( t − τ ¯ ) to r ( t k − τ ¯ ) and from r ( t − τ ¯ ) to r ( t k + 1 − τ ¯ ) . Based on this Lyapunov Functional and an improved integral inequality, less conservative conditions are derived to ensure the stability of the synchronization error system, leading to the fact that the drive neural network is synchronized with the response neural network. The desired sampled-data controller is designed in terms of solutions to linear matrix inequalities. A numerical example is provided to demonstrate that the proposed approaches are effective and superior to some existing ones in the literature.
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free matrix based time dependent discontinuous Lyapunov Functional for synchronization of delayed neural networks with sampled data control
Chinese Physics B, 2017Co-Authors: Wei Wang, Hongbing Zeng, Kok Lay TeoAbstract:This paper is concerned with the synchronization of delayed neural networks via sampled-data control. A new technique, namely, the free-matrix-based time-dependent discontinuous Lyapunov Functional approach, is adopted in constructing the Lyapunov Functional, which takes advantage of the sampling characteristic of sawtooth input delay. Based on this discontinuous Lyapunov Functional, some less conservative synchronization criteria are established to ensure that the slave system is synchronous with the master system. The desired sampled-data controller can be obtained through the use of the linear matrix inequality (LMI) technique. Finally, two numerical examples are provided to demonstrate the effectiveness and the improvements of the proposed methods.
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delay variation dependent stability of delayed discrete time systems
IEEE Transactions on Automatic Control, 2016Co-Authors: Chuanke Zhang, Lin Jiang, Hongbing ZengAbstract:This note is concerned with the stability analysis of linear discrete-time system with a time-varying delay. A generalized free-weighting-matrix (GFWM) approach is proposed to estimate summation terms in the forward difference of Lyapunov Functional, and theoretical study shows that the GFWM approach encompasses several frequently used estimation approaches as special cases. Moreover, an augmented Lyapunov Functional with a delay-product type term is constructed to take into account delay changing information. As a result, the proposed GFWM approach, together with the augmented Lyapunov Functional, leads to a less conservative delay-variation-dependent stability criterion. Finally, numerical examples are given to illustrate the advantages of the proposed criterion.
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further results on sampled data control for master slave synchronization of chaotic lur e systems with time delay
Nonlinear Dynamics, 2015Co-Authors: Shenping Xiao, Hongbing Zeng, Ju H Park, Yajuan LiuAbstract:This paper is concerned with the problem of sampled-data control for master–slave synchronization of chaotic Lur’e systems with time delay. The sampling periods are assumed to be arbitrary but bounded. A new Lyapunov Functional is constructed, in which the information on the nonlinear function and the actual sampling pattern have been taken fully into account. By employing the Lyapunov Functional and a tighter bound technique to estimate the derivative of the Lyapunov Functional, a less conservative exponential synchronization criterion is established by analyzing the corresponding synchronization error systems. Furthermore, the derived condition is employed to design a sampled-data controller. The desired controller gain matrix can be obtained by means of the linear matrix inequality approach. Simulations are provided to show the effectiveness and the advantages of the proposed approach.
Jian Chu - One of the best experts on this subject based on the ideXlab platform.
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local synchronization of chaotic neural networks with sampled data and saturating actuators
IEEE Transactions on Systems Man and Cybernetics, 2014Co-Authors: Peng Shi, Jian ChuAbstract:This paper investigates the problem of local synchronization of chaotic neural networks with sampled-data and actuator saturation. A new time-dependent Lyapunov Functional is proposed for the synchronization error systems. The advantage of the constructed Lyapunov Functional lies in the fact that it is positive definite at sampling times but not necessarily between sampling times, and makes full use of the available information about the actual sampling pattern. A local stability condition of the synchronization error systems is derived, based on which a sampled-data controller with respect to the actuator saturation is designed to ensure that the master neural networks and slave neural networks are locally asymptotically synchronous. Two optimization problems are provided to compute the desired sampled-data controller with the aim of enlarging the set of admissible initial conditions or the admissible sampling upper bound ensuring the local synchronization of the considered chaotic neural networks. A numerical example is used to demonstrate the effectiveness of the proposed design technique.
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sampled data synchronization of chaotic lur e systems with time delays
IEEE Transactions on Neural Networks, 2013Co-Authors: Peng Shi, Jian ChuAbstract:This paper studies the problem of sampled-data control for master-slave synchronization schemes that consist of identical chaotic Lur'e systems with time delays. It is assumed that the sampling periods are arbitrarily varying but bounded. In order to take full advantage of the available information about the actual sampling pattern, a novel Lyapunov Functional is proposed, which is positive definite at sampling times but not necessarily positive definite inside the sampling intervals. Based on the Lyapunov Functional, an exponential synchronization criterion is derived by analyzing the corresponding synchronization error systems. The desired sampled-data controller is designed by a linear matrix inequality approach. The effectiveness and reduced conservatism of the developed results are demonstrated by the numerical simulations of Chua's circuit and neural network.
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discontinuous Lyapunov Functional approach to synchronization of time delay neural networks using sampled data
Nonlinear Dynamics, 2012Co-Authors: Ju H Park, Jian ChuAbstract:This paper investigates the synchronization problem of neural networks with time-varying delay under sampled-data control in the presence of a constant input delay. Based on the extended Wirtinger inequality, a discontinuous Lyapunov Functional is introduced, which makes full use of the sawtooth structure characteristic of sampling input delay. A simple and less conservative synchronization criterion is given to ensure the master systems synchronize with the slave systems by using the linear matrix inequality (LMI) approach. The design method of the desired sampled-data controller is also proposed. Finally, two numerical examples are given to illustrate the effectiveness of the proposed methods.
Kok Lay Teo - One of the best experts on this subject based on the ideXlab platform.
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a new Lyapunov Functional approach to sampled data synchronization control for delayed neural networks
Journal of The Franklin Institute-engineering and Applied Mathematics, 2018Co-Authors: Shenping Xiao, Honghai Lian, Hongbing Zeng, Kok Lay Teo, Xiaohu ZhangAbstract:Abstract This paper discusses the problem of synchronization for delayed neural networks using sampled-data control. We introduce a new Lyapunov Functional, called complete sampling-interval-dependent discontinuous Lyapunov Functional, which can adequately capture sampling information on both intervals from r ( t − τ ¯ ) to r ( t k − τ ¯ ) and from r ( t − τ ¯ ) to r ( t k + 1 − τ ¯ ) . Based on this Lyapunov Functional and an improved integral inequality, less conservative conditions are derived to ensure the stability of the synchronization error system, leading to the fact that the drive neural network is synchronized with the response neural network. The desired sampled-data controller is designed in terms of solutions to linear matrix inequalities. A numerical example is provided to demonstrate that the proposed approaches are effective and superior to some existing ones in the literature.
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free matrix based time dependent discontinuous Lyapunov Functional for synchronization of delayed neural networks with sampled data control
Chinese Physics B, 2017Co-Authors: Wei Wang, Hongbing Zeng, Kok Lay TeoAbstract:This paper is concerned with the synchronization of delayed neural networks via sampled-data control. A new technique, namely, the free-matrix-based time-dependent discontinuous Lyapunov Functional approach, is adopted in constructing the Lyapunov Functional, which takes advantage of the sampling characteristic of sawtooth input delay. Based on this discontinuous Lyapunov Functional, some less conservative synchronization criteria are established to ensure that the slave system is synchronous with the master system. The desired sampled-data controller can be obtained through the use of the linear matrix inequality (LMI) technique. Finally, two numerical examples are provided to demonstrate the effectiveness and the improvements of the proposed methods.
Emilia Fridman - One of the best experts on this subject based on the ideXlab platform.
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stability analysis of networked control systems a discontiuous Lyapunov Functional approach
Conference on Decision and Control, 2009Co-Authors: Kun Liu, Emilia FridmanAbstract:This paper presents a new stability analysis of linear networked control systems. The new method is inspired by discontinuous Lyapunov functions that were introduced in [1] and [2] by using impulsive system representation of the sampled-data and of the networked control systems respectively. In the recent paper [3] piecewise-continuous (in time) Lyapunov-Krasovskii Functionals have been suggested for the stability analysis of sampled-data systems in the framework of input delay approach. Differently from the existing Lyapunov Functionals for systems with time-varying delays, the discontinuous ones can guarantee the stability under the sampling which may be greater than the analytical upper bound on the constant delay that preserves the stability. The objective of the present paper is to extend the discontinuous Lyapunov Functional approach to networked control systems, where the sampling and the network-induced delays are taken into account. Our results depend on the upper bound of the network-induced delay and the improvement is achieved if the latter bound becomes smaller.
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h control of distributed and discrete delay systems via discretized Lyapunov Functional
European Journal of Control, 2009Co-Authors: Emilia Fridman, Gennady TsodikAbstract:The discretized Lyapunov Functional method is extended to linear systems with both, discrete and distributed delays, and to H∞ control. The coefficients associated with the distributed delay are assumed to be piecewise constant. A new Bounded Real Lemma (BRL) is derived in terms of Linear Matrix Inequalities (LMIs) via descriptor approach. In three numerical examples considered for retarded type systems, the resulting values of H∞-norm converge to the exact ones. The analysis results are applied to state-feedback H∞ control of linear neutral systems with discrete and distributed delays, where the controller may be either instantaneous or may contain discrete or distributed delay terms. A numerical example illustrates the efficiency of the design method and the advantage of using distributed delay term in the feedback for H∞ control of systems with state delay.
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discontinuous Lyapunov Functional for linear systems with sawtooth delays
IFAC Proceedings Volumes, 2009Co-Authors: Kun Liu, Emilia FridmanAbstract:Abstract Exponential stability of linear systems with time-varying piecewise-continuous delays is studied. It is assumed that the delay function has a form of a sawtooth with a constant delay derivative ≠ 0. In the recent paper (Fridman, 2009) piecewise-continuous (in time) Lyapunov-Krasovskii Functionals (LKFs) have been suggested for the stability analysis of sampled-data systems (with ≠ = 1) in the framework of input delay approach. Differently from the existing time-independent LKFs for systems with time-varying delays, the discontinuous ones can guarantee the stability under the sampling which may be greater than the analytical upper bound on the constant delay that preserves the stability. The objective of the present paper is to extend the piecewise-continuous LKF method to systems with a general sawtooth delay. The discontinuous terms of LKFs improve the results for all values of, though the most essential improvement corresponds to = 1.
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descriptor discretized Lyapunov Functional method analysis and design
IEEE Transactions on Automatic Control, 2006Co-Authors: Emilia FridmanAbstract:Stability and state-feedback stabilization of linear systems with uncertain coefficients and uncertain time-varying delays are considered. The system under consideration may be unstable without delay, but it becomes asymptotically stable for positive values of the delay. A new descriptor discretized Lyapunov-Krasovskii Functional (LKF) method is introduced, which combines the application of the complete LKF and the discretization method of K. Gu with the descriptor model transformation. For the first time, the new method allows to apply the discretized LKF method to synthesis problems. Moreover, the analysis of systems with polytopic time-invariant uncertainties is less restrictive by the new discretized method. Sufficient conditions for robust stability and stabilization of uncertain neutral type systems are derived in terms of linear matrix inequalities (LMIs) via input-output approach to stability. Numerical examples illustrate the efficiency of the new method.
