Estimation from a multisensor environment for systems with multiple packet dropouts and correlated measurement noises

This paper addresses the problem of distributed fusion estimation from measurements with packet dropouts and cross-correlated noises acquired from different sensors. Assuming that the packet dropouts are modelled by independent Bernoulli random variables with different characteristics for each sensor and that measurement noises are cross-correlated at the same and at consecutive sampling times, filtering and smoothing algorithms are derived using the distributed fusion method. The distributed fusion filter and smoother are obtained as a matrix-weighted linear combination of corresponding local least-squares linear estimators, verifying that the mean squared error is minimum. The local linear filtering and fixed-point smoothing algorithms are derived using the first and second-order moments of the signal and the noises present in the observation model. Simulation results are provided to illustrate the feasibility of the proposed algorithms, using the error estimation covariance matrices as measure of the quality of the estimators.     

Robust fault detection of Markovian jump systems with different system modes

This paper deals with the robust fault detection filter (RFDF) design problems for uncertain nonlinear Markovian jump systems with unknown input. By using a observer-based fault detection filter as residual generator, the RFDF design is formulated as an _H∞$H_{\infty }$-filtering problem. Particularly, two different Markov processes are considered for modeling the randomness of system matrix and the state delay. With the aid of the weighting matrix function, the design objective is to find an optimal RFDF, which results in a minimal difference between the reference model and the RFDF to be designed. By using a new convex polyhedron technique and two mode-dependent Lyapunov functional, some new sufficient conditions are established in terms of delay-dependent linear matrix inequalities (LMIs) to synthesize the residual generation scheme. Finally, a numerical example is given to illustrate the effectiveness of the proposed techniques.     

Iterative learning control for a class of nonlinear systems with random packet losses

This paper considers the problem of iterative learning control (ILC) for a class of nonlinear systems with random packet dropouts. It is assumed that an ILC scheme is implemented via a networked control system (NCS), and that during the packet transfer between the remote nonlinear plant and the ILC controller packet dropout occurs. A new formulation is employed to model the packet dropout case, where the random dropout rate is transformed into a stochastic parameter in the system’s representation. Through rigorous analysis, it is shown that under some given conditions, the iterative learning control can guarantee the convergence of the tracking error although some packets are missing. The analysis is also supported by a numerical example.     

Self-synchronization of coupled chaotic FitzHugh–Nagumo systems with unreliable communication links

The problem for self-synchronization of coupled chaotic FitzHugh–Nagumo (FHN) systems with unreliable communication links is investigated in this paper. Different from ordinary coupled chaotic systems, the links between two neurons are long-distance and unreliable. Some special network characteristics, such as nonuniform sampling, transmission-induced delays and data packet dropouts, are analyzed in detail. The sufficient condition in terms of linear matrix inequality (LMI) is obtained to guarantee the asymptotical self-synchronization of coupled chaotic FHN systems with unreliable communication links. Lastly, an illustrative example is provided to show the validity of the proposed sufficient condition.     

Observer-based fault detection for networked control systems with network Quality of Services

This paper addresses the problem of the fault detection for linear time-invariant systems over data networks with limited network Quality of Services (QoS). An integrated index _ηk${\eta }_k$, which related with data dropout, network-induced delay and error sequence, is presented to described the non-ideal QoS, the probabilistic switching between different _ηk${\eta }_k$ is assumed to obey a homogeneous Markovian chain. Then by view of the augmented matrices approach, the fault detection error dynamic systems are transferred to Markov jumping systems (MJSs). With the developed model and using the bounded real lemma (BRL) for MJSs, an _H∞$H_{\infty }$ observer-based fault detection filter is established in terms of linear matrix inequalities (LMIs) to guarantee that the error between the residual and the weighted faults is made as small as possible. A simulation example is provided to show the effectiveness of the present methods.     

Stochastic stabilization of networked control systems with combined stochastic distributed processes

The stochastic stability problem of networked control systems (NCSs) with random time delays and packet dropouts is investigated in this paper. The mathematical NCS model is developed as a stochastic discrete‐time jump system with combined integrated stochastic parameters characterized by two identically independently distributed processes, which accommodate the abrupt variations of network uncertainties within an integrated frame. The effective instant is introduced to establish the relationship between the destabilizing transmission factors and stability of NCSs. The stabilizing state feedback controller gain that depends not only on the delay modes but also on the dropouts modes is obtained in terms of the linear matrix inequalities formulation via the Schur complement theory. A numerical example is given to demonstrate the effectiveness of the proposed method. Copyright © 2014 John Wiley & Sons, Ltd.     

Observer‐based dissipative control for networked control systems: A switched system approach

This article studies the problem of observer‐based dissipative control problem for wireless networked control systems (NCSs). The packet loss and time delay in the network are modeled by a set of switches, using that a discrete‐time switched system is formulated. First, results for the exponential dissipativity of discrete‐time switched system with time‐varying delays are proposed by using the average dwell time approach and multiple Lyapunov–Krasovskii function. Then, the results are extended to drive the controller design for considered wireless NCS. The attention is focused on designing an observer‐based state feedback controller which ensures that, for all network‐induced delay and packet loss, the resulting error system is exponentially stable and strictly dissipative. The sufficient conditions for existence of controllers are formulated in the form of linear matrix inequalities (LMIs), which can be easily solved using some standard numerical packages. Both observer and controller gains can be obtained by the solutions of set of LMIs. Finally, numerical examples are provided to illustrate the applicability and effectiveness of the proposed method. © 2014 Wiley Periodicals, Inc. Complexity 21: 297–308, 2015     

On designing H∞ fault estimator for switched nonlinear systems of neutral type

This paper deals with the problem of fault estimation for a class of switched nonlinear systems of neutral type. The nonlinearities are assumed to satisfy global Lipschitz conditions and appear in both the state and measured output equations. By employing a switched observer-based fault estimator, the problem is formulated as an H_∞ filtering problem. Sufficient delay-dependent existence conditions of the H_∞ fault estimator (H_∞-FE) are given in terms of certain matrix inequalities based on the average dwell time approach. In addition, by using cone complementarity algorithm, the solutions to the observer gain matrices are obtained by solving a set of linear matrix inequalities (LMIs). A numerical example is provided to demonstrate the effectiveness of the proposed approach.     

Adjustable dimension descriptor observer based fault estimation for switched nonlinear systems with partially unknown nonlinear dynamics

This paper focuses on the fault estimation problem for switched systems with partially unknown nonlinear dynamics, actuator and sensor faults, simultaneously. The fault estimation observers are constructed, in which the observer dimension is not fixed and can be selected in a certain range. Both the disturbance decoupling and disturbance attenuation are considered, where the unknown nonlinear dynamics can be decoupled and the effect of modeling error and measurement disturbance is attenuated. Based on the average dwell time and the piecewise Lyapunov function, the observer parameter matrices can be calculated by solving LMIs and matrix equations. Finally, two examples are listed to verify the proposed fault estimation approach.     

Nonfragile H∞ output tracking control for uncertain singular Markovian jump delay systems with network‐induced delays and data packet dropouts

This article deals with the problem of nonfragile H_∞ output tracking control for a kind of singular Markovian jump systems with time‐varying delays, parameter uncertainties, network‐induced signal transmission delays, and data packet dropouts. The main objective is to design mode‐dependent state‐feedback controller under controller gain perturbations and bounded modes transition rates such that the output of the closed‐loop networked control system tracks the output of a given reference system with the required H_∞ output tracking performance. By constructing a more multiple stochastic Lyapunov–Krasovskii functional, the novel mode‐dependent and delay‐dependent conditions are obtained to guarantee the augmented output tracking closed‐loop system is not only stochastically admissible but also satisfies a prescribed H_∞‐norm level for all signal transmission delays, data packet dropouts, and admissible uncertainties. Then, the desired state‐feedback controller parameters are determined by solving a set of strict linear matrix inequalities. A simple production system example and two numerical examples are used to verify the effectiveness and usefulness of the proposed methods. © 2015 Wiley Periodicals, Inc. Complexity 21: 396–411, 2016     

小波包变换及代价函数设计综述

小波包是小波理论的重要组成部分,在非平稳信号特征检测和故障诊断中具有广泛的应用。小波包教学是小波分析教学的一个难点,也是一个较容易忽视的知识点。本文分析了小波包理论,归纳总结了小波包目标函数,以及它们适用的领域,并提出了新的目标函数。本文可以对小波包的教学提供一些新的思路。     

An LMI approach to positive real control for discrete time-delay systems

This paper focuses on the problem of positive real controlfor discrete time-delay systems. The problem we address is thedesign of a dynamic output feedback controller, which guaranteesthe asymptotic stability of the closed-loop system and achievesthe extended strictly positive realness of a certain closed-looptransfer function. Then, a condition for extended strictly positiverealness for discrete-delay systems is developed. Based on this,a sufficient condition for the existence of the desired controllersis proposed in terms of three linear matrix inequalities (LMIs).When these LMIs are feasible, an explicit parametrization ofthe desired output feedback controller is presented. An illustrativeexample is given to demonstrate the applicability of the proposedapproach.     

网络化非周期采样控制系统的主动时间滞后控制:随机脉冲切换系统方法

研究了一类带有随机丢包的非周期采样网络化控制系统的镇定问题.不同于传统观点往往将时滞看作系统稳定性的消极因素,考虑时间滞后对系统稳定性的积极影响,并提出一个新颖的主动时间滞后控制方法来镇定该系统.为了分析时间滞后控制的积极作用并获得较低保守性的结论,首先把带随机丢包的非周期采样系统建模为带固定切换率的随机脉冲切换系统,...     

Robust Stability and Performance Analysis of Uncertain Systems Using Linear Matrix Inequalities

A wide variety of problems in system and control theory can be formulated or reformulated as convex optimization problems involving linear matrix inequalities (LMIs), that is, constraints requiring an affine combination of symmetric matrices to be positive semidefinite. For a few very special cases, there are analytical solutions to these problems, but in general LMI problems can be solved numerically in a very efficient way. Thus, the reduction of a control problem to an optimization problem based on LMIs constitutes, in a sense, a solution to the original problem. The objective of this article is to provide a tutorial on the application of optimization based on LMIs to robust control problems. In the first part of the article, we provide a brief introduction to optimization based on LMIs. In the second part, we describe a specific example, that of the robust stability and performance analysis of uncertain systems, using LMI optimization.     

Stabilization of nonlinear networked systems with sensor random packet dropout and time-varying delay

In this paper, a nonlinear stochastic system model is proposed to describe the networked control systems (NCSs) with both random packet dropout and network-induced time-varying delay. Based on this more general nonlinear NCSs model, by choosing appropriate Lyapunov functional and employing new discrete Jensen type inequality, a sufficient condition is derived to establish the quantitative relation of maximum allowable delay upper bound, packet dropout rate and the nonlinear level to the exponential stability of the nonlinear NCSs. Design procedures for output feedback controller are also presented in terms of utilizing cone complementarities linearization algorithm or solving corresponding linear matrix inequalities (LMIs). Illustrative examples are provided to demonstrate the effectiveness of the proposed method.     

Detecting and approximating fault lines from randomly scattered data

Discretely defined surfaces that exhibit vertical displacements across unknown fault lines can be difficult to approximate accurately unless a representation of the faults is known. Accurate representations of these faults enable the construction of constrained approximation models that can successfully overcome common problems such as over-smoothing. In this paper we review an existing method for detecting fault lines and present a new detection approach based on data triangulations and discrete Gaussian curvature (DGC). Furthermore, we show that if the fault line can be described non-parametrically, then accurate support vector machine (SVM) models can be constructed that are independent of the type of triangulation used in the detection algorithms. We shall also see that SVM models are particularly effective when the data produced by the detection algorithms are noisy. We compare the performances of the various new and established models.     

Robust reliable L2 – L∞ control for continuous‐time systems with nonlinear actuator failures

This article examines the reliable L₂ – L_∞ control design problem for a class of continuous‐time linear systems subject to external disturbances and mixed actuator failures via input delay approach. Also, due to the occurrence of nonlinear circumstances in the control input, a more generalized and practical actuator fault model containing both linear and nonlinear terms is constructed to the addressed control system. Our attention is focused on the design of the robust state feedback reliable sampled‐data controller that guarantees the robust asymptotic stability of the resulting closed‐loop system with an L₂ – L_∞ prescribed performance level γ > 0, for all the possible actuator failure cases. For this purpose, by constructing an appropriate Lyapunov–Krasovskii functional (LKF) and utilizing few integral inequality techniques, some novel sufficient stabilization conditions in terms of linear matrix inequalities (LMIs) are established for the considered system. Moreover, the established stabilizability conditions pave the way for designing the robust reliable sampled‐data controller as the solution to a set of LMIs. Finally, as an example, a wheeled mobile robot trailer model is considered to illustrate the effectiveness of the proposed control design scheme. © 2016 Wiley Periodicals, Inc. Complexity 21: 309–319, 2016     

Stability analysis on delayed neural networks based on an improved delay-partitioning approach

In this paper, the asymptotical stability is investigated for a class of delayed neural networks (DNNs), in which one improved delay-partitioning idea is employed. By choosing an augmented Lyapunov-Krasovskii functional and utilizing general convex combination method, two novel conditions are obtained in terms of linear matrix inequalities (LMIs) and the conservatism can be greatly reduced by thinning the partitioning of delay intervals. Moreover, the LMI-based criteria heavily depend on both the upper and lower bounds on time-delay and its derivative, which is different from the existent ones. Though the results are not presented via standard LMIs, they still can be easily checked by resorting to Matlab LMI Toolbox. Finally, three numerical examples are given to demonstrate that our results can be less conservative than the present ones.     

On Dynamic Output Feedback Guaranteed Cost Control of Uncertain Discrete-Delay Systems: LMI Optimization Approach

In this paper, we consider a design problem of dynamic output feedback controller for guaranteed cost stabilization of discrete-delay systems with norm-bounded time-varying parameter uncertainties. A linear-quadratic cost function is considered as a performance measure for the closed-loop system. Based on the Lyapunov second method, several stability criteria for the existence of the controller are derived in terms of linear matrix inequalities (LMIs). The solutions of the LMIs can be obtained easily using existing efficient convex optimization techniques. A numerical example is given to illustrate the proposed method.