Yajuan Liu

Further Results on Stabilization of Chaotic Systems Based on Fuzzy Memory Sampled-Data Control

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.

Sampled-data synchronization of chaotic Lur’e systems via input-delay-dependent-free-matrix zero equality approach

Abstract This paper focuses on the sampled-data synchronization problem of chaotic Lur’e systems (CLSs) by using sampled output of the systems with variable sampling rates. One novel approach, input-delay-dependent-free-matrix zero equality (IDDFMZE) approach, is proposed for the first time. The IDDFMZE approach can not only fully capture the available information on the actual sampling pattern, but deploy more system information at the dynamic partitioning point. A new Lyapunov–Krasovskii functional (LKF) with some new terms is constructed, which can use more information of the activation function at the dynamic partitioning point. Based on the presented IDDFMZE approach and the constructed LKF, developed synchronization criterion is obtained in the form of linear matrix inequalities (LMIs). The desired sampled-data controller is designed under larger sampling period. Finally, the superiority of proposed results is shown by two numerical examples.

Event-Based Reliable Dissipative Filtering for T–S Fuzzy Systems With Asynchronous Constraints

In this paper, event-triggered reliable dissipative filtering is investigated for a class of Takagi–Sugeno (T–S) fuzzy systems. First, a reliable event-triggered communication scheme is introduced to release sampled measurement outputs only if the variation of the sampled vector exceeds a prescribed threshold condition. Second, an asynchronous premise reconstruct method for T–S fuzzy systems is presented, which relaxes the assumption of the prior work that the premises of the plant and the filter are synchronous. Third, the resulting filtering error system is modeled under consideration of event-triggered communication, sensor failure, and asynchronous premise in a unified framework. By adopting the Lyapunov functional method and integral inequality approach, a delay-dependent criterion is developed to guarantee asymptotic stability for the filtering error systems and achieve strict

Differential feature based hierarchical PCA fault detection method for dynamic fault

(Q, S,R)-\alpha

Exponential synchronization of a class of neural networks with sampled-data control

dissipativity. Consequently, suitable filters and the event parameters can be derived by solving a set of linear matrix inequalities. Finally, an example is given to show the effectiveness of the proposed method.

Nonfragile Sampled-Data Synchronization for Delayed Complex Dynamical Networks With Randomly Occurring Controller Gain Fluctuations

By sensor accuracy degradation or unwanted alternating current signals, sensor fault with zero cross point (ZCP) may occur in real systems and conventional data-driven fault detection methods could be invalid. In this regard, this paper proposes a hierarchical principal component analysis (PCA) fault detection method based on the differential features of dynamic faults to detect the fault with ZCPs. The main contribution of this work are as follows: (1) A new differential based feature extraction method is first proposed to well character the dynamic trend of the observation; (2) then, a hierarchical detection criterion is proposed according to the detection ability of each round of PCA anomaly detection; (3) it is convenient to extend the proposed method to other statistical based fault detection techniques whose detection criteria are also a distance defined by fault amplitude.

Stabilization of chaotic systems under variable sampling and state quantized controller

This paper investigates the problem of the master-slave synchronization for a class of neural networks with discrete and distributed delays under sampled-data control. By introducing some new terms, a novel piecewise time-dependent Lyapunov-Krasovskii functional (LKF) is constructed to fully capture the available characteristics of real sampling information and nonlinear function vector of the system. Based on the LKF and Wirtinger-based inequality, less conservative synchronization criteria are obtained to guarantee the exponential stability of the error system, and then the slave system is synchronized with the master system. The designed sampled-data controller can be obtained by solving a set of linear matrix inequalities (LMIs), which depend on the maximum sampling period and the decay rate. The criteria are less conservative than the ones obtained in the existing works. A numerical example is presented to illustrate the effectiveness and merits of the proposed method.

A new method for exponential synchronization of memristive recurrent neural networks

In this paper, the problem of nonfragile sampled-data synchronization of delayed complex dynamical networks with randomly occurring controller gain fluctuations (ROCGFs) is studied. First, more applicable nonfragile memory sampled-data controllers are designed, which involve the signal transmission delay and ROCGFs. The controller gain fluctuations appear in a random way, which obey certain Bernoulli distributed white noise sequences. Second, a modified piecewise Lyapunov–Krasovskii functional (LKF), which involves cubic sawtooth structure term, is constructed for the first time. Third, based on the LKF, less conservative synchronization criteria are established. In comparison with the existing results, the constraint condition of the positive definition of the LKF is less restrictive, since it does not need to be positive definite for all time, but is only required to be positive definite at sampling times. Finally, the effectiveness and advantages of the obtained results are illustrated by two numerical examples.

H ∞ Filtering for a Class of Nonlinear Systems with Interval Time-varying Delay

Abstract This paper investigates the problem of stabilization for chaotic systems based on a T–S fuzzy model under sampled-data control and state quantization. A novel Lyapunov–Krasovskii functional (LKF) is introduced to the sampled-data systems. The benefit of the new approach is that the LKF develops more information about the actual sampling pattern. In addition, some symmetric matrices involved in the LKF are not required to be positive definite. Based on a recently introduced Wirtinger-based integral inequality that has been shown to be less conservative than Jensens inequality, much less conservative stabilization conditions are obtained to ensure the maximal sampling period. Then, the corresponding sampled-data controllers can be synthesized by solving a set of linear matrix inequalities (LMIs). Finally, an illustrative example is given to show the feasibility and effectiveness of the proposed method.

Novel Results for Global Exponential Stability of Uncertain Systems with Interval Time-varying Delay

Abstract This paper investigates the exponential synchronization problem of memristive recurrent neural networks (MRNNs). A novel approach, switching matrix approach, is considered to study synchronization of MRNNs for the first time. All the matrices in the constructed Lyapunov–Krasovskii functional (LKF) are switching according to different switching rules. Based on the switching matrix approach, a new synchronization criterion is established in the form of linear matrix inequalities (LMIs). Compared with some existing methods, the switching matrix approach is more flexible and can improve the synchronization performance with low control cost. Finally, numerical simulations are provided to show the effectiveness and advantages of the proposed results.