scholarly journals Synchronization and Control of Linearly Coupled Singular Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Fang Qingxiang ◽  
Peng Jigen ◽  
Cao Feilong
Keyword(s):  
Singular Systems ◽  
Dynamical Behavior ◽  
Sufficient Conditions ◽  
Lyapunov Stability Theory ◽  
Pinning Control ◽  
State Feedback Control ◽  
Linear Matrix ◽  
Coupling Matrix ◽  
The Stability ◽  
And Control

The synchronization and control problem of linearly coupled singular systems is investigated. The uncoupled dynamical behavior at each node is general and can be chaotic or, otherwise the coupling matrix is not assumed to be symmetrical. Some sufficient conditions for globally exponential synchronization are derived based on Lyapunov stability theory. These criteria, which are in terms of linear matrix inequality (LMI), indicate that the left and right eigenvectors corresponding to eigenvalue zero of the coupling matrix play key roles in the stability analysis of the synchronization manifold. The controllers are designed for state feedback control and pinning control, respectively. Finally, a numerical example is provided to illustrate the effectiveness of the proposed conditions.

scholarly journals Stability and Stabilization of Continuous-Time Markovian Jump Singular Systems with Partly Known Transition Probabilities

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Jumei Wei ◽  
Rui Ma
Keyword(s):  
Continuous Time ◽  
Controller Design ◽  
Partial Information ◽  
Transition Probabilities ◽  
Singular Systems ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Markovian Jump ◽  
Stability And Stabilization ◽  
The Stability

This paper investigates the problem of the stability and stabilization of continuous-time Markovian jump singular systems with partial information on transition probabilities. A new stability criterion which is necessary and sufficient is obtained for these systems. Furthermore, sufficient conditions for the state feedback controller design are derived in terms of linear matrix inequalities. Finally, numerical examples are given to illustrate the effectiveness of the proposed methods.

scholarly journals H∞ Filtering for Discrete-Time Nonlinear Singular Systems with Quantization

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Yifu Feng ◽  
Zhi-Min Li ◽  
Xiao-Heng Chang
Keyword(s):  
Discrete Time ◽  
Filter Design ◽  
Design Method ◽  
Singular Systems ◽  
Sufficient Conditions ◽  
Lyapunov Stability Theory ◽  
Linear Matrix ◽  
Nonlinear Singular Systems ◽  
Attenuation Level ◽  
Measurement Output

This paper investigates the problem of H∞ filtering for class discrete-time Lipschitz nonlinear singular systems with measurement quantization. Assume that the system measurement output is quantized by a static, memoryless, and logarithmic quantizer before it is transmitted to the filter, while the quantizer errors can be treated as sector-bound uncertainties. The attention of this paper is focused on the design of a nonlinear quantized H∞ filter to mitigate quantization effects and ensure that the filtering error system is admissible (asymptotically stable, regular, and causal), while having a unique solution with a prescribed H∞ noise attenuation level. By introducing some slack variables and using the Lyapunov stability theory, some sufficient conditions for the existence of the nonlinear quantized H∞ filter are expressed in terms of linear matrix inequalities (LMIs). Finally, a numerical example is presented to demonstrate the effectiveness of the proposed quantized filter design method.

Robust State-Feedback Controller Design for Uncertainty Singular Systems

2011 ◽  
Vol 383-390 ◽  
pp. 32-37
Author(s):  
Li Ming Liang ◽  
Fa Lu Weng ◽  
Yuan Chun Ding
Keyword(s):  
Controller Design ◽  
Singular Systems ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Robust Controller ◽  
Uncertain Singular Systems ◽  
Stability And Stabilization ◽  
The Stability ◽  
Parameter Dependent ◽  
Robust Stability And Stabilization

In this paper the problem of robust stability and stabilization of a class of uncertain singular Systems with uncertainties in both the derivative and state matrices is studied. By using a parameter dependent Lyapunov function, we derive the linear matrix inequalities (LMIs) based sufficient conditions for the stability and stabilization of the system. By solving these LMIs, the robust controller is derived. Finally, the numerical example is given to show the effectiveness of the proposed theorems.

scholarly journals RobustH∞Control for a Class of Discrete Time-Delay Stochastic Systems with Randomly Occurring Nonlinearities

2014 ◽  
Vol 2014 ◽  
pp. 1-10
Author(s):  
Yamin Wang ◽  
Fuad E. Alsaadi ◽  
Stanislao Lauria ◽  
Yurong Liu
Keyword(s):  
Time Delay ◽  
Discrete Time ◽  
Stochastic Systems ◽  
Sufficient Conditions ◽  
Lyapunov Stability Theory ◽  
Linear Matrix ◽  
Parameter Uncertainties ◽  
Attenuation Level ◽  
Discrete Time Delay ◽  
And Control

In this paper, we consider the robustH∞control problem for a class of discrete time-delay stochastic systems with randomly occurring nonlinearities. The parameter uncertainties enter all the system matrices; the stochastic disturbances are both state and control dependent, and the randomly occurring nonlinearities obey the sector boundedness conditions. The purpose of the problem addressed is to design a state feedback controller such that, for all admissible uncertainties, nonlinearities, and time delays, the closed-loop system is robustly asymptotically stable in the mean square, and a prescribedH∞disturbance rejection attenuation level is also guaranteed. By using the Lyapunov stability theory and stochastic analysis tools, a linear matrix inequality (LMI) approach is developed to derive sufficient conditions ensuring the existence of the desired controllers, where the conditions are dependent on the lower and upper bounds of the time-varying delays. The explicit parameterization of the desired controller gains is also given. Finally, a numerical example is exploited to show the usefulness of the results obtained.

scholarly journals Robust Stabilization of T-S Fuzzy Systems via Improved Integral Inequality

2021 ◽  
Author(s):  
Karthik C ◽  
Nagamani G ◽  
Ramasamy Subramaniyam ◽  
Dafik D
Keyword(s):  
Integral Inequality ◽  
Fuzzy Systems ◽  
Robust Stabilization ◽  
Sufficient Conditions ◽  
Fuzzy Model ◽  
State Feedback Control ◽  
Linear Matrix ◽  
Continuous Stirred Tank Reactor ◽  
Control Gain ◽  
The Stability

Abstract This paper focuses on the state feedback control for uncertain nonlinear model, which can be denoted by Takagi - Sugeno (T-S) fuzzy model. We derive an improved integral inequality as a rearrangement of quadratic matrix-vector form combined with Jensen's inequality. By using this improved inequality, the sufficient conditions guaranteeing the stability of the resulting T-S fuzzy model have been proposed in terms of linear matrix inequalities. With respect to these stability conditions, the stabilization criterion is given for the T-S fuzzy systems with the prescribed control gain matrices. Finally, to check the feasibility and less conservatism of the derived results, numerical examples are given including the physical model such as continuous stirred tank reactor ( CSTR ) model supported by numerical simulations.

Adaptive state estimation of Markov switched neural networks driven by Lévy noise

2019 ◽  
Vol 42 (2) ◽  
pp. 330-336
Author(s):  
Dongbing Tong ◽  
Qiaoyu Chen ◽  
Wuneng Zhou ◽  
Yuhua Xu
Keyword(s):  
Neural Networks ◽  
State Estimation ◽  
Sufficient Conditions ◽  
Lyapunov Stability Theory ◽  
Lévy Noise ◽  
Linear Matrix ◽  
Delayed Neural Networks ◽  
Switched Neural Networks ◽  
Inequality Technique ◽  
Levy Noise

This paper proposes the [Formula: see text]-matrix method to achieve state estimation in Markov switched neural networks with Lévy noise, and the method is very distinct from the linear matrix inequality technique. Meanwhile, in light of the Lyapunov stability theory, some sufficient conditions of the exponential stability are derived for delayed neural networks, and the adaptive update law is obtained. An example verifies the condition of state estimation and confirms the effectiveness of results.

Exponential stability and periodicity of memristor-based recurrent neural networks with time-varying delays

2017 ◽  
Vol 10 (02) ◽  
pp. 1750027 ◽  
Author(s):  
Wei Zhang ◽  
Chuandong Li ◽  
Tingwen Huang
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Sufficient Conditions ◽  
Functional Approach ◽  
Linear Matrix ◽  
Time Varying ◽  
Matrix Inequality ◽  
Matrix Inequalities ◽  
Inclusion Theory ◽  
The Stability

In this paper, the stability and periodicity of memristor-based neural networks with time-varying delays are studied. Based on linear matrix inequalities, differential inclusion theory and by constructing proper Lyapunov functional approach and using linear matrix inequality, some sufficient conditions are obtained for the global exponential stability and periodic solutions of memristor-based neural networks. Finally, two illustrative examples are given to demonstrate the results.

scholarly journals Adaptive Cluster Synchronization for Nondelayed and Delayed Coupling Complex Networks with Nonidentical Nodes

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Ze Tang ◽  
Jianwen Feng
Keyword(s):  
Sufficient Conditions ◽  
Pinning Control ◽  
Cluster Synchronization ◽  
Linear Matrix ◽  
Control Cost ◽  
Synchronization Problem ◽  
Delayed Coupling ◽  
Control Scheme ◽  
Successful Control ◽  
Synchronization Pattern

We focus on the cluster synchronization problem for a kind of general networks with nondelayed and delayed coupling. Based on the pinning control scheme, a small fraction of the nodes in each cluster are pinned for successful control, and the states of the whole dynamical networks can be globally forced to the objective cluster states. Sufficient conditions are derived to guarantee the realization of the cluster synchronization pattern for all initial values by means of the Lyapunov stability theorem and linear matrix inequalities (LMIs). By using the adaptive update law, relative smaller control gains are obtained, and hence the control cost can be substantially lower. Numerical simulations are also exploited to demonstrate the effectiveness and validity of the main result.

The Control of a Neural Complex Network

2014 ◽  
Vol 687-691 ◽  
pp. 444-446
Author(s):  
Fan Di Zhang
Keyword(s):  
Neural Network ◽  
Community Structure ◽  
Lyapunov Stability ◽  
Control Strategy ◽  
Sufficient Conditions ◽  
Lyapunov Stability Theory ◽  
Pinning Control ◽  
Projective Synchronization ◽  
Cluster Synchronization ◽  
Special Cases

In this paper, the synchronization of a neural network with community structure is investigated. Cluster projective generalizes previously existing synchronization schemes. The cluster projective synchronization is more general that includes projective synchronization and cluster synchronization, as its special cases. The cluster projective synchronization of these networks is discussed via some pinning control strategy. Several sufficient conditions for the network to achieve cluster projective synchronization are derived based on Lyapunov stability theory. Numerical simulations are used to demonstrate the effectiveness and feasibility of the proposed scheme.

Simultaneous actuator and sensor fault estimation for neutral-type systems via intermediate observer

2021 ◽  
pp. 014233122110585
Author(s):  
Yuheng Wei ◽  
Dongbing Tong ◽  
Qiaoyu Chen ◽  
Yuqing Sun ◽  
Wuneng Zhou
Keyword(s):  
Neutral Type ◽  
Sufficient Conditions ◽  
Lyapunov Stability Theory ◽  
Type Systems ◽  
Matching Condition ◽  
Descriptor System ◽  
Fault Estimation ◽  
Linear Matrix ◽  
Sensor Faults ◽  
Neutral Type Systems

This study addresses the fault estimation (FE) issue for neutral-type systems with sensor faults and actuator faults through the intermediate observer. First, it is well-known that the observer matching condition (OMC) ought to be met for most traditional FE methods, which is actually difficult to satisfy for many systems. In order to overcome this limitation, a suitable variable is designed and the intermediate observer is proposed to estimate the actuator and sensor faults for neutral-type systems simultaneously. Second, based on linear matrix inequalities, sufficient conditions are derived, which guarantee the existence of the intermediate observer. An augmented descriptor system is constructed for the neutral-type systems. By the Lyapunov stability theory, states of error systems are ultimately bounded. Finally, two examples demonstrate the effectiveness and practicability of the designed strategy.

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