Packet Dropout Phenomenon Research Articles

A unified method to energy-to-peak filter design for networked Markov switched singular systems over a finite-time interval

For a class of networked singular Markov switched discrete-time systems, this work investigates the finite-time energy-to-peak filtering problem. The system modes information is transmitted though an unreliable communication link in the systems under consideration, where the packet dropout phenomenon, modes information available to the filter and asynchronous phenomenon between filter modes and system modes are randomly occurring with a certain probability and described by some Bernoulli distributed white sequence variables. The objective is focused on designing a unified filter, which covers mode-independent filter, asynchronous filter and mode-dependent filter, so that the estimation error system is finite-time bounded while meets a fixed energy-to-peak performance requirement in the presence of those stochastic phenomena. By employing a probability-dependent Lyapunov–Krasovskii function, some sufficient criteria are established to make sure that there is a feasible solution to the addressed problem. Moreover, with the help of a novel simple matrix decoupling approach, the filter gains are obtained. In the end, we employ a numerical example with simulation to show the serviceability of the presented method.

Recursive filtering for communication-based train control systems with packet dropouts

Abstract Accurate information about the train position and velocity is critically important for Communication-based Train Control (CBTC) systems. However, it is practically difficult to obtain the precise information of such information due mainly to the “inaccurate measurements” induced by the measurement noises and the “unreliable communication” caused by the wireless train-ground communication. In this paper, a recursive filtering algorithm is proposed to generate the estimates of the train position and velocity for CBTC systems subject to the measurement noise and packet dropouts. Firstly, the dynamics of a train is modeled based on the Newton’s motion equation. Then, a Bernoulli distributed sequence is introduced to describe the packet dropout phenomenon of the wireless communication. The purpose of the problem addressed is to design a recursive filter such that there exists an upper bound for the filtering error covariance. Subsequently, such an upper bound is minimized by properly designing the filter parameter recursively. The desired filter parameter is obtained by solving two Riccati-like difference equations that are of a recursive form suitable for online applications. Finally, an illustrative example is given to show the effective of the proposed filter design scheme.

H∞ filtering for discrete-time switched fuzzy systems with randomly occurring time-varying delay and packet dropouts

In this paper, we investigate H∞ filtering problem for a class of discrete-time switched fuzzy systems with randomly occurring time-varying delay and packet dropouts. The fuzzy plant incorporates features of switched systems and Takagi–Sugeno (T-S) fuzzy systems simultaneously. The stochastic time-varying delay and packet dropouts phenomenon are assumed to occur in a random way but satisfy the well-known Bernoulli binary distribution, meanwhile, all the stochastic variables under consideration are mutually independent. By introducing a novel delay-dependent piecewise Lyapunov function, sufficient conditions are established in the form of linear matrix inequalities, which ensure the filtering error system is exponentially stable with prescribed H∞ performance. Finally, an illustrative example is exploited to verify the effectiveness of the proposed approaches.

Synchronization Control for a Class of Discrete-Time Dynamical Networks With Packet Dropouts: A Coding-Decoding-Based Approach.

The synchronization control problem is investigated for a class of discrete-time dynamical networks with packet dropouts via a coding-decoding-based approach. The data is transmitted through digital communication channels and only the sequence of finite coded signals is sent to the controller. A series of mutually independent Bernoulli distributed random variables is utilized to model the packet dropout phenomenon occurring in the transmissions of coded signals. The purpose of the addressed synchronization control problem is to design a suitable coding-decoding procedure for each node, based on which an efficient decoder-based control protocol is developed to guarantee that the closed-loop network achieves the desired synchronization performance. By applying a modified uniform quantization approach and the Kronecker product technique, criteria for ensuring the detectability of the dynamical network are established by means of the size of the coding alphabet, the coding period and the probability information of packet dropouts. Subsequently, by resorting to the input-to-state stability theory, the desired controller parameter is obtained in terms of the solutions to a certain set of inequality constraints which can be solved effectively via available software packages. Finally, two simulation examples are provided to demonstrate the effectiveness of the obtained results.

New results on filter design for sampled‐data systems with packet dropouts and transmission delays

In this study, the problem of H ∞ filtering for sampled-data systems under unreliable communication links is investigated. The phenomena of data packet dropouts and signal transmission delays are addressed in a unified framework. The objective is to design an admissible filter to guarantee the asymptotic stability of the filtering error system and minimise the H ∞ disturbance attenuation level. Thanks to the proposed novel Lyapunov–Krasovskii functional together with the improved Wirtinger's inequality and the reciprocally convex approach, novel sufficient linear-matrix-inequality-based conditions are obtained for the existence and design of admissible filters. Finally, two simulation examples are provided to illustrate the efficiency and less conservativeness of the proposed H ∞ filter design methods.

Fault-Tolerant Control for an Internet-Based Three-Tank System: Accommodation to Sensor Bias Faults

This paper focuses on the fault-tolerant control problem for an Internet-based three-tank system in the presence of possible sensor bias faults. The Internet-based three-tank system is an experimental setup that can be regarded as a typical networked system for evaluating networked fault-diagnosis and fault-tolerant control methods. Packet dropout phenomenon in the sensor-to-controller link is considered in this paper, and the fault type we deal with is chosen as the sensor bias fault. Fault-diagnosis unit is designed toward an auxiliary system. Sensor bias faults can be detected by comparing the residual signal generated by the fault detection filter and a prescribed threshold. After that, the fault can be isolated by using the residual analysis approach. Once the fault is isolated, it can be estimated iteratively in the least-squares sense. A fault accommodation method is proposed, and a fault-tolerant control strategy is achieved based on the fault information provided by the fault-diagnosis unit. The approach brought forward in this paper is demonstrated via an experimental study on the practical Internet-based three-tank system. Results show the effectiveness and the applicability of the proposed techniques.

Cloud-Based Fault Tolerant Control for a DC Motor System

The fault tolerant control problem for a DC motor system is investigated in a cloud environment. Packet dropout phenomenon introduced by the limited-capacity communication channel is considered. Actuator faults are taken into consideration and fault diagnosis and fault tolerant control methods towards actuator faults are proposed to enhance the reliability of the whole cloud-based DC motor system. The fault diagnosis unit is then established with purpose of obtaining fault information. When the actuator fault is detected by comparing the residual signal with a predefined threshold, a residual matching approach is utilized to locate the fault. The fault can be further estimated by a least-squares filter. Based on the fault estimation, a fault tolerant controller is designed to guarantee the stability as well as the control performance of the DC motor system. Simulation result on a DC motor system shows the efficiency of the fault tolerant control method proposed in this paper.

Output-Feedback Control for Nonlinear Stochastic Systems With Successive Packet Dropouts and Uniform Quantization Effects

In this paper, the dynamic output-feedback control problem is studied for a class of discrete-time nonlinear stochastic systems with successive packet dropouts and uniform quantization effects. The stochastic system under investigation involves state-, control-, and disturbance-dependent noises (also called ( ${x}$ , ${u}$ , ${v}$ )-dependent noises) that bring in substantial difficulties in the stability analysis. The phenomenon of successive packet dropouts is governed by a binary switching random sequence. The measurement output is subject to the uniform quantization which results in the norm-bounded disturbances, and the concept of input-to-state stability in probability is introduced to deal with this kind of disturbances. In virtue of intensive stochastic analysis, several sufficient conditions are established to guarantee that the closed-loop system is input-to-state stable in probability under the effects of probabilistic packet dropouts as well as uniform quantizations. As an easy consequence, the design problem with linear output-feedback controllers is discussed for the benefits of practical applications and some simplified conditions are derived. Finally, a numerical example is presented to illustrate the effectiveness of the proposed method.

Resilient H∞ filtering for discrete-time uncertain Markov jump neural networks over a finite-time interval

In this paper, the resilient finite-time H∞ filtering problem for discrete-time uncertain Markov jump neural networks with packet dropouts is investigated. The purpose is to design a filter which is insensitive with respect to filter gain uncertainties subjects to an H∞ performance level. The data packet dropouts phenomenon modeled by a stochastic Bernoulli distributed process is also considered. In terms of the linear matrix inequalities methodology, some sufficient conditions which guarantee that the filtering error system is finite-time bounded with a prescribed H∞ performance level are established. Based on the conditions, an explicit expression for the desired filter is given. A numerical example is provided to illustrate the validness of the proposed scheme.

Fault detection for switched positive systems under successive packet dropouts with application to the Leslie matrix model

SummaryIn this paper, the problem of fault detection filter design is dealt with for a class of switched positive systems with packet dropouts on the channel between the sensors and the filters. The phenomena of packet dropouts are governed by a Bernoulli process, and a stochastic switched positive system is established based on the augmented states of the plants and filters. Two criteria are developed to evaluate the performance of the fault detection for the system under investigation. Sufficient conditions are established on the existence of the desired filters for the mean‐square stability with an L1 disturbance attenuation level, and an index for the L− fault sensitivity is also derived through constructing a switched Lyapunov function in term of linear programming. Two illustrative examples, one of which is concerned with the Leslie matrix model, are provided to show the effectiveness and applicability of the proposed results. Copyright © 2015 John Wiley & Sons, Ltd.

Formula omitted] filtering for networked linear systems with multiple packet dropouts and random delays

This paper is concerned with an H∞ filtering problem for the network-based linear systems with multiple packet dropouts and random delays. Due to the limited bandwidths of communication channels, the measured outputs will be delayed or even be lost during the transmission from the sensor to the remote filter, where the delays are randomly varying but bounded and packet dropouts are possibly consecutive. Based on a recent developed model that describes the phenomena of packet dropouts and time delays simultaneously, an H∞ filter is designed to ensure the filtering error system to be mean-square exponentially stable and guarantee a prescribed H∞ filtering performance. A sufficient condition for the existence of such a filter is provided via a linear matrix inequality (LMI) method. The effectiveness and applicability of the proposed algorithm is demonstrated by a practical F-404 aircraft engine system.

Finite‐time energy‐to‐peak filtering for Markov jump repeated scalar non‐linear systems with packet dropouts

This study is concerned with the finite-time energy-to-peak filtering problem for Markov jump repeated scalar non-linear systems with packet dropouts. The packet dropout phenomenon occurs in a random way and is modelled by a stochastic variable satisfying the Bernoulli distribution. The purpose of the study is to design a filter such that the resulting filtering error system is stochastically finite-time bounded, and a prescribed energy-to-peak performance level is achieved over a finite time interval. By using the mode-dependent diagonally dominant Lyapunov function approach, some strict linear matrix inequality-based conditions are established for the existence of an admissible filter, and a corresponding explicit parameterisation of such a filter is obtained. Finally, a numerical example with simulation is presented to demonstrate the effectiveness of our proposed approach.

Networked Strong Tracking Filtering with Multiple Packet Dropouts: Algorithms and Applications

This paper focuses on the design problem of a recursive networked strong tracking filter (NSTF) for a class of nonlinear networked systems with parameter perturbations and unknown inputs. The sensors for the networked system are allowed to be spatially distributed in a large geographical area, and signals are transmitted via a shared communication channel with limited capacity. For this kind of system structure, the measurements from different sensors may experience probabilistic data loss with different probabilities. A series of Bernoulli sequences is employed to describe the multiple packet dropout rates. Parameter perturbations and unknown inputs in the system are considered in the filter design process. A recursive networked extended Kalman filter is first derived in the least mean square sense by taking the packet dropout phenomenon into account. Then, a fading factor is introduced in the filter structure in order to cope with the parameter perturbations and unknown system inputs, and a recursive NSTF is derived by developing the so-called networked orthogonal principle. It is shown that the proposed NSTF is capable of providing satisfactory estimation results even in the presence of system parameter perturbations and/or unknown system inputs. A simulation study is carried out on a practical Internet-based three-tank system, and the estimation results show the effectiveness and applicability of the proposed filtering techniques.

Linear estimation for networked control systems with random transmission delays and packet dropouts

In networked control systems, random delays and packet dropouts are inevitable during data transmissions due to the limited communication capacity. The phenomena of random delays and packet dropouts of both sides from a sensor to an estimator and from a controller to an actuator are modeled via employing two groups of Bernoulli random variables. By defining some new variables, the original system with random delays and packet dropouts is equivalently transformed into a stochastic parameterized system. The optimal linear filter, predictor and smoother in the linear minimum variance sense are presented via the orthogonality projection approach. They depend on the probabilities of the stochastic parameters. The solutions to the optimal linear estimators are given by three equations including a Riccati, a Lyapunov and a simple difference. The stability of the proposed estimators is analyzed. At last, a sufficient condition for the existence of the steady-state estimators is given for time-invariant systems. Two examples are provided to verify the effectiveness of the proposed algorithms.

Robust H∞ filtering for a class of complex networks with stochastic packet dropouts and time delays.

The robust H ∞ filtering problem is investigated for a class of complex network systems which has stochastic packet dropouts and time delays, combined with disturbance inputs. The packet dropout phenomenon occurs in a random way and the occurrence probability for each measurement output node is governed by an individual random variable. Besides, the time delay phenomenon is assumed to occur in a nonlinear vector-valued function. We aim to design a filter such that the estimation error converges to zero exponentially in the mean square, while the disturbance rejection attenuation is constrained to a given level by means of the H ∞ performance index. By constructing the proper Lyapunov-Krasovskii functional, we acquire sufficient conditions to guarantee the stability of the state detection observer for the discrete systems, and the observer gain is also derived by solving linear matrix inequalities. Finally, an illustrative example is provided to show the usefulness and effectiveness of the proposed design method.

Distributed H ∞ filtering for sensor networks with switching topology

In this article, the distributed H ∞ filtering problem is investigated for a class of sensor networks under topology switching. The main purpose is to design the distributed H ∞ filter that allows one to regulate the sensor's working modes. Firstly, a switched system model is proposed to reflect the working mode change of the sensors. Then, a stochastic sequence is adopted to model the packet dropout phenomenon occurring in the channels from the plant to the networked sensors. By utilising the Lyapunov functional method and stochastic analysis, some sufficient conditions are established to ensure that the filtering error system is mean-square exponentially stable with a prescribed H ∞ performance level. Furthermore, the filter parameters are determined by solving a set of linear matrix inequalities (LMIs). Our results relates the decay rate of the filtering error system to the switching frequency of the topology directly and shows the existence of such a distributed filter when the topology is not varying very frequently, which is helpful for the sensor state regulation. Finally, the effectiveness of the proposed design method is demonstrated by two numerical examples.

Recursive estimation for descriptor systems with multiple packet dropouts and correlated noises

In this paper, the problem of recursive estimation is studied for a class of descriptor systems with multiple packet dropouts and correlated noises. The multiple packet dropouts phenomenon is considered to be random and described by a binary switching sequence that obeys a conditional probability distribution. The autocorrelated measurement noise is characterized by the covariances between different time instants. The descriptor system is transformed into a regular line system with an algebraic constraint. By using an innovation analysis method and the orthogonal projection theorem, recursive estimators including filter, predictor and smoother are developed for each subsystem and the process noise. Further, the recursive filter, predictor and smoother are obtained for the original descriptor system with possible multiple packet dropouts phenomenon and correlated noises. Simulation results are provided to demonstrate the effectiveness of the proposed approaches.

$H_\infty$ Filtering for Networked Systems With Multiple Time-Varying Transmissions and Random Packet Dropouts

This paper is concerned with the H∞ filtering for networked systems with multiple time-varying transmissions and random packet dropouts. We design a remote H∞ filter for these two networked issues such that the filtering error system is exponentially stable and achieves a prescribed H∞ performance level. A switched system approach is used to model the multiple time-varying transmission process, and a set of stochastic variables are employed to describe the random packet dropout phenomenon. By the switched system theory and some stochastic analysis methods, a sufficient condition for the existence of the H∞ filter is derived in terms of linear matrix inequalities (LMIs). Moreover, the filter gains are determined by solving an optimization problem. Two numerical examples are given to illustrate the effectiveness of the proposed design method.

Stability analysis of networked control systems with round-robin scheduling and packet dropouts

In this paper, the stability of networked control systems (NCSs) with communication constraints at both channels is investigated. A Conventional Round-Robin Scheduling (CRRS) is applied to deal with the communication constraints issue for its simple structure. Furthermore, a Dynamic Round-Robin Scheduling (DRRS), which can preserve the controllability and the detectability of the systems, is considered. For the unreliable communication channels, two independent homogeneous Markov chains are selected to model the packet dropouts phenomenon in the sensor-to-controller (S/C) channel and the controller-to-actuator (C/A) channel. According to the periodic property of the Round-Robin Scheduling (RRS), an auxiliary system with augmented Markov chain is established by the lifting technique to facilitate the stability analysis of the closed-loop system. A necessary and sufficient condition of the exponential mean-square stability for the NCSs is derived. Two illustrative examples are shown to demonstrate the effectiveness of the proposed stability analysis method.

Optimal linear estimators for systems with multiple random measurement delays and packet dropouts

This article is concerned with the optimal linear estimation problem for linear discrete-time stochastic systems with possible multiple random measurement delays and packet dropouts, where the largest random delay is limited within a known bound and packet dropouts can be infinite. A new model is constructed to describe the phenomena of multiple random delays and packet dropouts by employing some random variables of Bernoulli distribution. By state augmentation, the system with random delays and packet dropouts is transferred to a system with random parameters. Based on the new model, the least mean square optimal linear estimators including filter, predictor and smoother are easily obtained via an innovation analysis approach. The estimators are recursively computed in terms of the solutions of a Riccati difference equation and a Lyapunov difference equation. A sufficient condition for the existence of the steady-state estimators is given. An example shows the effectiveness of the proposed algorithms.