Class Of Discrete-time Networked Systems Research Articles

Formula omitted] filter design for discrete-time networked systems with adaptive event-triggered mechanism and hybrid cyber attacks

This paper focuses on the design of H∞ filter for a class of discrete-time networked systems. Given that the network communication resources are becoming limited with the ever-increasing network traffic, an adaptive event-triggered mechanism (AETM) is adopted for the systems to mitigate the pressure of network bandwidth. The considered discrete-time networked systems are envisioned to suffer from both Deception attacks and denial-of-service (DoS) attacks, thereby a novel hybrid cyber attacks model is firstly constructed to integrate the two kinds of attacks. Then, a filtering error system model is established for the discrete-time networked systems under AETM and hybrid cyber attacks. Based on the constructed model, the sufficient conditions that guaranteeing the asymptotic stability and H∞ performance of the concerned filtering error system are analyzed based on Lyapunov–Krasovskii stability theory. Furthermore, the corresponding parameters of the designed filter are derived by solving a set of linear matrix inequalities (LMIs). The effectiveness of the designed filter is finally demonstrated by conducting a numerical example.

Joint State and Fault Estimation for Discrete-Time Networked Systems with Unknown Measurement Delays

This paper addresses the joint state and fault estimation problem for a class of discrete-time networked systems with unknown measurement delays. A novel augmented observer is developed to simultaneously estimate system states, fault signals and the perturbed term caused by measurement delays. For this purpose, an augmented descriptor system is first established by considering the faults and the perturbed term as auxiliary state vectors. Then, a modified state-space observer is constructed to estimate the extended state. Intensive stability analysis is carried out to obtain the sufficient condition for the existence of the desired estimator, and the corresponding optimal observer parameters can be co-designed by solving a convex optimization problem. Finally, a numerical example is exploited to illustrate the effectiveness of the proposed joint estimation scheme.

Finite-time control of discrete-time systems with variable quantization density in networked channels

This paper is concerned with the problem of finite-time control for a class of discrete-time networked systems. The measurement output and control input signals are quantized before being transmitted in communication network. The quantization density of the network is assumed to be variable depending on the throughputs of network for the sake of congestion avoidance. The variation of the quantization density modes satisfies persistent dwell-time &#x0028 PDT &#x0029 switching which is more general than dwell-time switching in networked channels. By using a quantization-error-dependent Lyapunov function approach, sufficient conditions are given to ensure that the quantized systems are finite-time stable and finite-time bounded with a prescribed H&#x221E performance, upon which a set of controllers depending on the mode of quantization density are designed. In order to show the effectiveness of the designed H&#x221E controller, we apply the developed theoretical results to a numerical example.

Simultaneous H2/H∞ fault detection and control for networked systems with application to forging equipment

This paper investigates the simultaneous fault detection and control (SFDC) problems for a class of discrete-time networked systems with multiple stochastic delays and data missing. Both faults and disturbances are assumed to be in low frequency domain. The communication delays are uniformly modeled by multiple random variables obeying the Bernoulli distributions, which are mutually correlated by a prior Pearson correlation coefficient matrix. Then the closed-loop system is formulated as a special jump linear system. The generalized definitions of the H2 and H∞ indexes for such underlying systems are proposed to measure the detection and control performances, respectively. Then a mixed H2/H∞ SFDC approach is proposed to achieve the desired detection and control objectives. To cope with the H2 performance index in a given frequency range directly, by Parseval lemma and S-procedure, a relaxed condition is presented to reduce the conservatism of the existing results. And the integrated detector/controller is derived in terms of solving a set of linear matrix inequalities (LMIs). The developed method is applied to the large forging equipment drive systems, and simulation results demonstrate the effectiveness of the results.

Mode Dependent H∞ Filtering for Discrete-Time Networked Systems with Random Measurement Missing and Delays

The article investigates the H∞ filtering problem for a class of discrete-time networked systems with random measurement losses and delays. Markov chain is used here to model measurement losses and delays in a unified framework. Based on the mode-dependent Lyapunov function approach, the necessary and sufficient conditions are derived to guarantee the exponential stability with a prescribed H∞ disturbance attenuation performance for the filtering error system. By using a novel design scheme, the explicit expressions of mode dependent filter parameters are given in the form of linear matrix inequalities (LMIs) which can be readily solved by using the LMI TOOLBOX in MATLAB. At last, a numerical example is given to illustrate the feasibility and effectiveness of the proposed method.

State estimation for networked systems with randomly occurring quantisations

In this article, the state estimation problem is investigated for a class of discrete-time networked systems with randomly occurring quantisations. Logarithmic quantisers with different quantisation laws are considered and a Bernoulli distributed stochastic sequence is utilised to determine which quantiser is used at a certain time instant. After converting the quantisation effects into sector-bounded parameter uncertainties, a sufficient condition ensuring the existence of desirable estimators is proposed by using Lyapunov function approach, and parameters of the desired estimator are further obtained. Simulation is carried out on a networked three-tank system in order to illustrate the applicability of the proposed state estimation technique.

H∞ filtering for networked systems with partly known distribution transmission delays

This paper studies the H∞ filtering problem for a class of discrete-time networked systems with partly known distribution transmission delays. It is assumed that the random sensor-filter delay satisfies Markovian characteristics, but the transition probabilities of the delay transferring from one value to others are partly known. A novel measurement model is proposed to reflect the random delay of the transmission modes and the resulting filtering error system is modeled as a Markovian jump system (MJS) with multiple modes and state delay. Sufficient conditions are derived for the filtering error system to be stochastically stable and ensure a prescribed H∞ disturbance attenuation level bound by using mode-dependent Lyapunov functional approach. Based on the derived conditions, a design procedure for the H∞ filter is also presented. A numerical example is provided to show the design process of the filter and the effectiveness of the proposed method.

Robust Fault Detection for Networked Systems with Distributed Sensors

This paper is concerned with the robust fault detection problem for a class of discrete-time networked systems with distributed sensors. Since the bandwidth of the communication channel is limited, packets from different sensors may be dropped with different missing rates during the transmission. Therefore, a diagonal matrix is introduced to describe the multiple packet dropout phenomenon and the parameter uncertainties are supposed to reside in a polytope. The aim is to design a robust fault detection filter such that, for all probabilistic packet dropouts, all unknown inputs and admissible uncertain parameters, the error between the residual (generated by the fault detection filter) and the fault signal is made as small as possible. Two parameter-dependent approaches are proposed to obtain less conservative results. The existence of the desired fault detection filter can be determined from the feasibility of a set of linear matrix inequalities that can be easily solved by the efficient convex optimization method. A simulation example on a networked three-tank system is provided to illustrate the effectiveness and applicability of the proposed techniques.

Robust fault detection for networked systems with communication delay and data missing

In this paper, the robust fault detection problem is investigated for a class of discrete-time networked systems with unknown input and multiple state delays. A novel measurement model is utilized to represent both the random measurement delays and the stochastic data missing phenomenon, which typically result from the limited capacity of the communication networks. The network status is assumed to vary in a Markovian fashion and its transition probability matrix is uncertain but resides in a known convex set of a polytopic type. The main purpose of this paper is to design a robust fault detection filter such that, for all unknown inputs, possible parameter uncertainties and incomplete measurements, the error between the residual signal and the fault signal is made as small as possible. By casting the addressed robust fault detection problem into an auxiliary robust H ∞ filtering problem of a certain Markovian jumping system, a sufficient condition for the existence of the desired robust fault detection filter is established in terms of linear matrix inequalities. A numerical example is provided to illustrate the effectiveness and applicability of the proposed technique.

Network‐based robust fault detection with incomplete measurements

AbstractIn this paper, we deal with the robust fault detection problem for a class of discrete‐time networked systems with unknown inputs. Three types of incomplete measurements frequently occurred in a network environment are simultaneously considered, which include (1) measurements with communication delays, (2) measurements with packet dropouts, and (3) measurements with signal quantization. A unified measurement model utilizing a set of Kronecker delta functions is proposed to describe the delay and missing phenomenon, and the quantization is assumed to be of the logarithmic type. Attention is focused on the analysis and design of a robust full‐order fault detection filter such that, for all admissible unknown inputs and incomplete measurements, the error between residual and fault is kept as small as possible. By augmenting the states of the original system and the fault detection filter, the addressed robust fault detection problem is converted into an auxiliary robust H∞ filtering problem. Parameter‐dependent and delay‐probability‐dependent approaches are developed in the design process in order to have a less conservative result. Sufficient conditions for the existence of the desired robust fault detection filters are established in terms of certain linear matrix inequalities (LMIs), and explicit parameters of the desired filter are then characterized if these LMIs are feasible. A numerical example is provided to illustrate the applicability of the proposed technique. Copyright © 2008 John Wiley & Sons, Ltd.

Networked fault detection with random communication delays and packet losses

This article deals with the fault detection problem for a class of discrete-time networked systems with multiple state delays and unknown input. Two kinds of incomplete measurements, namely measurements with random communication delays and measurements with stochastic packet losses, are simultaneously considered. By properly augmenting the states of the original system and the fault detection filter, the fault detection filter design problem can be formulated as an H ∞ filtering problem. Attention is focused on the design of a fault detection filter such that, for all unknown input and incomplete measurements, the error between residual and weighted fault is made as small as possible. A sufficient condition for the existence of the desired fault detection filter is established in terms of a linear matrix inequality. A numerical example is provided to illustrate the effectiveness and applicability of the proposed techniques.

Fault Detection for Networked Systems with Incomplete Measurements

This paper investigates the fault detection problem for a class of discrete-time networked systems. Three kinds of typically encountered incomplete measurements induced by the limited-capacity communication channel are simultaneously considered, which include 1) measurements with communication delays; 2) measurements with data missing; and 3) measurements with signal quantization. Attention is focused on the analysis and design of a full-order fault detection filter such that, for all admissible unknown inputs and incomplete measurements, the error between residual and fault is kept as small as possible. Sufficient conditions for the existence of the desired fault detection filter are first established in terms of certain linear matrix inequalities (LMIs), then the explicit expression of the desired filter is characterized when these LMIs are feasible. A simulation example is provided to illustrate the effectiveness and applicability of the proposed method.