Filtering Error System Research Articles

Event-triggered fuzzy filtering for nonlinear networked systems with dynamic quantization and stochastic cyber attacks

In this article, the H∞ filtering issue is considered for discrete-time nonlinear networked systems subject to event-triggered communication scheme, dynamic quantization, and stochastic cyber attacks. The considered nonlinear networked system is described by the Takagi–Sugeno (T–S) fuzzy model. The event-triggered policy and the dynamic quantizer will be considered to realize the effective use of the restricted network bandwidth resources. Moreover, a stochastic variable that satisfies the Bernoulli random binary distribution is employed to characterize the effects of stochastic cyber attacks. This paper focus on the design of full- and reduced-order event-triggered H∞ filters and the dynamic parameter of the quantizer such that the filtering error system is stochastically stable and satisfies a predefined H∞ filtering performance. The sufficient design conditions for the event-triggered H∞ filters and the dynamic parameter of the quantizer are proposed based on linear matrix inequalities (LMIs). Finally, an example based on practical application will be used to verify the effectiveness of the presented design methods.

Event-triggered [formula omitted] filtering for nonlinear networked control systems via T-S fuzzy model approach

This paper tackles the event-triggering filtering problem for a class of nonlinear networked control systems subject to the prescribed disturbance attenuation level. To alleviate the data transmission burden of communication channels, an event-triggering mechanism is adopted, where the data can be transmitted only if certain condition is fulfilled. The T-S fuzzy model approach is utilized to approximate the nonlinear dynamics. It is the purpose of this paper to design a filter for the addressed nonlinear system ensuring that the filtering error system is asymptotically stable whereas the prespecified H∞ criterion is guaranteed. By using Lyapunov approach in combination with matrix analysis method, the sufficient conditions are established for the existence of desired filtering parameters in terms of the solvability of certain linear matrix inequalities. Finally, a numerical simulation example is put forward to demonstrate the validity and effectiveness of the developed theoretical results.

Reliable [formula omitted] filtering of semi-Markov jump systems over a lossy network

The problem of time-varying reliable H∞ filtering for a class of discrete-time semi-Markov jump systems (S-MJSs) over a lossy network is considered in this paper. The communication channels between the system and the filter are supposed to be unreliable, which lead to the existences of randomly occurring sensor nonlinearities and imperfect transmission. Based on the semi-Markov kernel (SMK) method and stochastic analysis technique, some mode-dependent sufficient conditions are derived and time-varying reliable filters are designed, which guarantee that the filtering error system is σ-error mean square stable with an H∞ performance index. Two numerical examples are given to show the usefulness of proposed filter design method.

Event-based asynchronous and resilient filtering for singular Markov jump LPV systems against deception attacks

This article addresses the issue of dissipative asynchronous and resilient filter design for singular Markov jump linear parameter-varying (SMJLPV) systems against deception attacks under the dynamic event-triggered transmission protocol. Firstly, an improved dynamic event-triggered transmission protocol is provided to further relieve the channel congestion caused by the bandwidth limited communication network. Then, the deception attack, which can potentially destroy the integrity of the system, is modelled as a random variable satisfying Bernoulli distribution. Since the filter cannot identify the original system mode accurately, the hidden-Markov-model (HMM) is established to describe the phenomenon that two modes are out of synchronization. By augmenting the states of the original system and the filter, the filtering error systems are converted into SMJLPV systems with partially known transition rates (TRs). Based on the parameter-dependent linear matrix inequalities (PDLMIs), a cooperative design technique for the asynchronous filter and the weighting matrix of the dynamic event-triggered transmission protocol is proposed. Lastly, a numerical instance and a resistance-inductance-capacitance (RLC) switch circuit system are employed to verify the effectiveness of the theoretical results.

Extended dissipative filtering for Markov jump BAM inertial neural networks under weighted try-once-discard protocol

This paper investigates the problem of extended dissipative filtering for bidirectional associative memory inertial neural networks, where the Markov chain is introduced to describe the switching characteristic in the structure and parameters. Moreover, considering the limited network bandwidth, the weighted try-once-discard protocol, as a significant scheduling mechanism in determining which nodes can be accessed between the sensor nodes and the filter, is employed to avoid the data collisions under the constrained communication channel. The objective of the paper is to develop a filter that can ensure that the filtering error system is stochastically stable with extended dissipative performance. Based on the Lyapunov function and an improved decoupling approach, a set of sufficient conditions satisfying the above objective are derived, and the filter gains are obtained. Finally, an illustrative example is employed to verify the validity of the proposed method.

Formula omitted] filtering for nonlinearly coupled complex networks subjected to unknown varying delays and multiple fading measurements

In this paper, the robust filtering problem for uncertain complex networks with time-varying state delay and stochastic nonlinear coupling based on H∞ performance criterion is studied. The random connections of coupling nodes are represented by utilizing independent random variables and the multiple fading measurements phenomenon is characterized by introducing diagonal matrices with independent stochastic elements. Moreover, the probabilistic time-varying delays in the measurement outputs are described by white sequences with the Bernoulli distributions. Furthermore, All system’s matrices are supposed to have uncertainty and a quadratic bound is assumed for nonlinear part of the network. This bound can be obtained by solving a sum of squares (SOS) optimization problem. By applying the Lyapunov theory, we design a robust filter for each node of the network so that the filtering error system is asymptomatically stable and the H∞ performances are met. Then, the parameters of the filters are achieved by solving a linear matrix inequality (LMI) feasibility problem. Finally, the applicability and performance of the proposed H∞ filtering approach are demonstrated via a practical example.

Resilient H-infinity filtering for networked nonlinear Markovian jump systems with randomly occurring distributed delay and sensor saturation

The H∞ filtering problem for a class of networked nonlinear Markovian jump systems subject to randomly occurring distributed delays, nonlinearities, quantization effects, missing measurements and sensor saturation is investigated in this paper. The measurement missing phenomenon is characterized via a random variable obeying the Bernoulli stochastic distribution. Moreover, due to bandwidth limitations, the measurement output is quantized using a logarithmic quantizer and then transmitted to the filter. Further, the output measurements are affected by sensor saturation since the communication links between the system and the filter are unreliable and is described by sector nonlinearities. The objective of this work is to design a quantized resilient filter that guarantees not only the stochastic stability of the augmented filtering error system but also a prespecified level of H∞ performance. Sufficient conditions for the existence of desired filter are established with the aid of proper Lyapunov–Krasovskii functional and linear matrix inequality approach together with stochastic analysis theory. Finally, a numerical example is presented to validate the developed theoretical results.

Dissipativity-Based Filtering of Time-Varying Delay Interval Type-2 Polynomial Fuzzy Systems Under Imperfect Premise Matching

This article investigates the dissipativity-based filtering problem for the nonlinear systems subject to both uncertainties and time-varying delay in the time-delay interval type-2 (IT2) polynomial fuzzy framework. Filter design is a challenging issue for complex nonlinear systems especially when uncertainties and time delay exist. The IT2 polynomial fuzzy model is an effective and powerful approach to analyze and synthesize uncertain nonlinear systems. This is the first attempt to design both the full-order and reduced-order IT2 polynomial fuzzy filter to ensure that the filtering error system is asymptotically stable under the dissipativity constraint. The design of filtering is based on the imperfect premise matching scheme where the number of fuzzy rules and shapes of membership functions of the designed fuzzy filter can differ from those of the IT2 polynomial fuzzy model, to provide greater design flexibility and lower implementation burden. By utilizing the Lyapunov–Krasovskii-functional-based approach, the information of membership functions, time delay, and system states is taken into account in the design process to develop the relaxed membership-function-dependent and delay-dependent filtering existence criteria. Finally, simulation results are presented to illustrate the effectiveness of the filtering algorithm reported in this article.

Finite‐time event‐triggered H∞ filtering of the continuous‐time switched time‐varying delay linear systems

AbstractThe finite‐time event‐triggered H∞ filtering of the continuous‐time switched time‐varying delay linear (CSTDL) systems is addressed in the paper. Firstly, by the merging switching signal technique, the CSTDL system and its filtering switched system are established as a filtering error system (FES) with augmented switching signal. And asynchronous switching of switched system modes and filter modes occurs since a mode‐dependent event‐triggered transmission scheme (METS) which determines the system output and switching signal is addressed. Secondly, the sufficient conditions are given to make certain that the FES is finite‐time bounded (FTB) and has a specified H∞ performance by using the average dwell time (ADT) and multi‐Lyapunov functional method. Furthermore, a finite‐time H∞ filter is composed based on the inequalities of the parameters of the METS. Ultimately, a numerical example is inspired to manifest the availability of the effects in the study.

Interval Type-2 Fuzzy Passive Filtering for Nonlinear Singularly Perturbed PDT-Switched Systems and Its Application

The problem of designing a passive filter for nonlinear switched singularly perturbed systems with parameter uncertainties is explored in this paper. Firstly, the multiple-time-scale phenomenon is settled effectively by introducing a singular perturbation parameter in the plant. Secondly, the interval type-2 fuzzy set theory is employed where parameter uncertainties are expressed in membership functions rather than the system matrices. It is worth noting that interval type-2 fuzzy sets of the devised filter are different from the plant, which makes the design of the filter more flexible. Thirdly, the persistent dwell-time switching rule, as a kind of time-dependent switching rules, is used to manage the switchings among nonlinear singularly perturbed subsystems, and this rule is more general than dwell-time and average dwell-time switching rules. Next, sufficient conditions are provided for guaranteeing that the filtering error system is globally uniformly exponentially stable with a passive performance. Furthermore, on the basis of the linear matrix inequalities, the explicit expression of the designed filter can be obtained. Finally, a tunnel diode electronic circuit is rendered as an example to confirm the correctness and the validity of the developed filter.

Mode-Dependent Event-Triggered Fault Detection for Nonlinear Semi-Markov Jump Systems With Quantization: Application to Robotic Manipulator

This paper is studied with fault detection issue for nonlinear semi-Markov jump systems. In particular, the mode-dependent mechanism of event-triggered transmission is developed for improving communication efficiency. Furthermore, the mode-dependent quantization method is utilized to cope with the limited network bandwidth. These strategies are chosen for more effective utilization of system mode information with less conservatism. Mode-dependent filter type fault detectors are constructed and sufficient conditions are established by Lyapunov-Krasovskii functionals, such that the filter error system can achieve the desired dissipative performance. In the end, the designed fault detection method is verified through a practical example of robotic manipulator.

New approach to finite frequency Filter Design for two-dimensional T-S fuzzy systems

This paper considers the problem of filter design for two-dimensional (2D) discrete-time non-linear systems in Takagi-Sugeno (T-S) fuzzy mode. The problem to be solved in the paper is to find a H∞ filter model such that the filtering error system is asymptotically stable. A numerical example is employed to illustrate the validity of the proposed methods.

Resilient Security Filtering for Networked Switched Systems With Event-Driven Measurements

This paper is concerned with event-driven filtering for networked switched systems with unreliable links. In order to improve the anti-interference performance of the filter, stochastic cyber-attacks and random parametric perturbations are considered in the filter design. The update of the measurement is determined by a newly proposed intermittent event-driven mechanism, which helps to save limited bandwidth resources. By constructing a new Lyapunov-Krasovskii functional (LKF) without positivity and continuity constraints in a triggering interval, sufficient conditions are obtained such that the filtering error system is exponentially mean-square stable with a weighted H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance. The resilient filter and event-driven mechanism are then co-designed. Finally, the results obtained are applied to a switched circuit system.

Quantized passive filtering for switched delayed neural networks

The issue of quantized passive filtering for switched delayed neural networks with noise interference is studied in this paper. Both arbitrary and semi-Markov switching rules are taken into account. By choosing Lyapunov functionals and applying several inequality techniques, sufficient conditions are proposed to ensure the filter error system to be not only exponentially stable, but also exponentially passive from the noise interference to the output error. The gain matrix for the proposed quantized passive filter is able to be determined through the feasible solution of linear matrix inequalities, which are computationally tractable with the help of some popular convex optimization tools. Finally, two numerical examples are given to illustrate the usefulness of the quantized passive filter design methods.

Event-triggered L1 filtering for uncertain networked control systems with multiple sensor fault modes

Considering the influence of sensor fault modes on the system performance in communication network, under the discrete event-triggered communication scheme (DETCS), the problems of the robust [Formula: see text] filtering for a class of uncertain networked control systems (NCSs) with multiple sensor fault modes and persistent and amplitude-bounded disturbance constraints are investigated. A set of stochastic variables are adopted to describe the sensor faults, the filtering error system is established, which characterizes the effects of sensor faults and DETCS. By constructing an appropriate delay-dependent Lyapunov-Krasovskii functional, new results on stability and robust [Formula: see text] performance are proposed for the filtering error system according to Lyapunov theory and the integral inequality method, and the co-design method for gaining the desired [Formula: see text] filter parameters and event-triggering parameters is given in terms of linear matrix inequalities (LMIs). We notice that with the structrue of Lyapunov-Krasovskii functional which considers the piecewise-linear sawtooth structure characteristic of transmission delay, a less conservative result is obtained. Finally, three examples are provided to illustrate the feasibility of the proposed method.

Event-Triggered H ∞ Filtering for Markovian Jump Neural Networks under Random Missing Measurements and Deception Attacks

This paper concentrates on the event-triggered H ∞ filter design for the discrete-time Markovian jump neural networks under random missing measurements and cyber attacks. Considering that the controlled system and the filtering can exchange information over a shared communication network which is vulnerable to the cyber attacks and has limited bandwidth, the event-triggered mechanism is proposed to relieve the communication burden of data transmission. A variable conforming to Bernoulli distribution is exploited to describe the stochastic phenomenon since the missing measurements occur with random probability. Furthermore, seeing that the communication networks are vulnerable to external malicious attacks, the transferred information via the shared communication network may be changed by the injected false information from the attackers. Based on the above consideration, sufficient conditions for the filtering error system to maintain asymptotically stable are provided with predefined H ∞ performance. In the end, three numerical examples are given to verify the proposed theoretical results.

Robust finite frequency H∞ distributed memory filter design for networked control systems with polytopic uncertainty

AbstractThis paper addresses the robust finite frequency (FF) distributed filtering problem for uncertain networked control system (NCS) that consists of heterogeneous subsystems. By using past output measurements and considering the frequency information of disturbance signals, the designed distributed memory filter is able to guarantee that the filtering error system is well‐posed, stable and has the FF performance. Based on the extended finite frequency bounded realness lemma for uncertain NCSs, the existence condition of robust FF distributed memory filter is derived. Moreover, it is shown that by taking advantage of more past output measurements of NCS, the proposed design procedure can derive a distributed filter that achieves a lower performance bound. Finally, a practical example is given to show the effectiveness of the proposed filter design method.

Event-Triggered Communication and Annular Finite-Time H∞ Filtering for Networked Switched Systems.

Event-triggered communication mechanism (ETCM) provides an efficient way to reduce unwanted network traffic. This article studies the co-design of an ETCM and an annular finite-time (AFT) H∞ filter for networked switched systems (NSSs). First, the AFT definition and ETCM are presented. Second, a set of mode-dependent average dwell-time (MADT) switching rules is given. By resorting to a delay-dependent Lyapunov functional approach, some feasible AFT H∞ filters are designed. Third, it is proved that the filtering error system (FES) has a good performance in attenuating the external disturbances. Finally, the feasibility of the developed method is verified via simulation.

Input-Output Finite-Time Generalized Dissipative Filter of Discrete Time-Varying Systems With Quantization and Adaptive Event-Triggered Mechanism.

This article discusses the issue of input-output finite-time generalized dissipative filter design for a class of discrete time-varying systems. First, an adaptive event-triggered mechanism (AETM) with an adaptive law is proposed to adjust the threshold in the AETM according to the error between the system states and the filter states. Such an AETM determines whether the measurement output should be transmitted or not, which is more effective to economize the communication resources comparing with the traditional event-triggered mechanism. Second, in view of network-induced delays, the quantization and the AETM, a time-varying filter error system (TV-FES) is modeled. Then, a new augmented time-varying Lyapunov functional containing triple sum terms is provided. Based on the new finite-sum inequality and improved reciprocally convex combination lemma, delay-dependent conditions are obtained, which can ensure the TV-FES to be input-output finite-time stable and satisfy the given generalized dissipative performance. Moreover, the recursive linear matrix inequalities are presented to obtain the desired filter gains. Finally, numerical examples demonstrate the superiority and feasibility of the proposed method in this article.

Finite-frequency memory filter design for uncertain linear discrete-time systems: A polynomially parameter-dependent approach

This paper investigates the robust filtering problem for linear uncertain systems affected by noises in restricted frequency intervals. Different from traditional filter schemes, a finite-frequency memory filter is designed to generalize conventional memoryless ones in such a way that a sequence of latest output measurements are employed for current estimation. To be specific, a memory filter is sought which ensures that for all admissible uncertainties, the filtering error system is asymptotically stable with a prescribed noise-attenuation level in the restricted frequency range. To accomplish this, the finite-frequency specification is characterized by the generalized Kalman–Yakubovich–Popov (KYP) lemma, aiming at improving the capability of noise-attenuation over the given frequency range. Moreover, the homogeneous polynomially parameter-dependent technique is adopted to facilitate filter design and reduce conservatism further. Based on the proposed scheme, we prove rigorously that additional past output measurements contribute to less conservative results. Finally, a quarter-car model with an active-suspension system is used to validate the proposed scheme.