Sunjie Zhang

Local condition-based finite-horizon distributed H∞-consensus filtering for random parameter system with event-triggering protocols

This paper investigates the distributed H ∞ - consensus filtering problem for a class of discrete time-varying systems with random parameters and event-triggering protocols. An event-triggering protocol for each node is employed to reduce the burden of the network communication. A novel matrix named by information matrix is proposed to describe the complicated correlations among the elements of random matrix. By virtue of the presented information matrix, a weighted covariance matrix can be easily obtained to analyze the system with random parameters. With the aid of the newly constructed dissipation matrix and vector supplied rate functions, a set of local coupled conditions for each node is obtained such that the stochastic vector dissipativity-like over the finite-horizon of the filtering error dynamics can be guaranteed. As well, these sufficient conditions together could effectively solve the distributed H ∞ - consensus filtering problem. Notably, the designed filtering algorithm can be implemented on each node to obtain the desirable distributed filter gains. Finally, the effectiveness and applicability of the proposed algorithm is illustrated by a numerically simulative example.

H ∞ state estimation for memristive neural networks with multiple fading measurements

The attention of this paper is mainly concentrated on the H ∞ state estimators design problem for a kind of discrete-time memristive neural networks (MNNs) with multiple fading measurements. The phenomenon of multiple fading measurements is represented by a set of individual stochastic variables obeying a predetermined distribution on interval 0,1. Firstly, the augmented system comprised of MNNs and the dynamics of estimation errors are put forward to implement the performance analysis. Then, under the framework of the difference inclusion theory combined with the Lyapunov function method, several sufficient conditions are established to guarantee the exponential mean-square stability as well as H ∞ performance index. Furthermore, the desired estimator parameter is obtained in view of the solution of a convex optimization problem. In the end, an illustrative numerical example is exploited to check the reliability and usefulness of the design scheme in this paper.

Security in H2-sense for polytopic uncertain systems with attacks based on model predictive control

Abstract In this paper, the problem of network security in H 2 - sense for a discrete-time linear uncertain system with a polytopic description and subject to randomly occurring deception attacks is discussed. A novel attack model is proposed to reflect the randomly occurring behaviors of the deception attacks by using a set of Bernoulli distributed white sequences with known conditional probabilities. In view of the difficulties in obtaining state values in practical system, we design a static output-feedback controller. However, some equation constraints are brought about and become a hinder in obtaining the upper bound of the objective function. To deal with the problem, a singular decomposition technique is applied. Then, the static output-feedback model predictive control (MPC) algorithm is presented by solving an optimization problem involving some linear matrix inequalities (LMIs), by which security of the network (or the stability of the closed-loop system) could be guaranteed. Finally, a simulation example is utilized to illustrate validity and effectiveness of the proposed technique.

Design and analysis of H∞ filter for a class of T-S fuzzy system with redundant channels and multiplicative noises☆

Abstract This paper investigates the design and analysis problem of H∞ filter for a class of nonlinear systems based on T-S fuzzy models with both multiplicative noises and redundant channels, which are governed by a set of Bernoulli distributed white sequences. The packet dropout’s probability of the i-th channel depends on random Bernoulli variables. The aim of this study is to design and analyze an H∞ filter that can stabilize the T-S fuzzy filtering error dynamics. By utilizing both Lyapunov functional approach and stochastic analysis technique, we establish some sufficient conditions such that the addressed system is asymptotically stable in the mean square with a given H∞ performance. The needed filtering parameters are obtained by making use of the matrix inequalities’ solution. In the end, an example is given to demonstrate the effectiveness and usefulness of the proposed filtering approach.

Event-based containment control for multi-agent systems with packet dropouts

ABSTRACT This paper is concerned with the event-triggered containment control for stochastic multi-agent systems subject to packet dropouts. The adopted event-triggered protocol is with absolutely triggered conditions catering for the requirement of real-time to an extreme. In light of such a protocol, a novel definition of containment control in mean-square sense, named as χ-containment, is proposed to better describe the tracking dynamics of followers. Based on relative measurement outputs, the purpose of this paper is to design an output-feedback controller such that all followers converge into the convex hull spanned by leaders. First, with the help of the property of the Laplacian matrix, the containment control problem is transformed to an easily setting step by step. Then, sufficient conditions with the form of matrix inequalities are derived to guarantee the desired χ-containment which depends on the initial values and the event-triggered thresholds. By introducing a free matrix combined with an orthogonal basis of the null space of control matrix, the controller gain can be obtained by solving a set of linear matrix inequalities. Finally, a simulation example is given to verify the effectiveness of the designed control protocol.

Non-fragile – control for discrete-time stochastic nonlinear systems under event-triggered protocols

Abstract In this paper, the non-fragile – control problem is investigated for a class of discrete-time stochastic nonlinear systems under event-triggered communication protocols, which determine whether the measurement output should be transmitted to the controller or not. The main purpose of the addressed problem is to design an event-based output feedback controller subject to gain variations guaranteeing the prescribed disturbance attenuation level described by the – performance index. By utilizing the Lyapunov stability theory combined with S-procedure, a sufficient condition is established to guarantee both the exponential mean-square stability and the – performance for the closed-loop system. In addition, with the help of the orthogonal decomposition, the desired controller parameter is obtained in terms of the solution to certain linear matrix inequalities. Finally, a simulation example is exploited to demonstrate the effectiveness of the proposed event-based controller design scheme.