Fault detection and isolation using viability theory and interval observers

This paper proposes the use of interval observers and viability theory in fault detection and isolation (FDI). Viability theory develops mathematical and algorithmic methods for investigating the viability constraints characterisation of dynamic evolutions of complex systems under uncertainty. These methods can be used for checking the consistency between observed and predicted behaviour by using simple sets that approximate the exact set of possible behaviour (in the parameter or state space). In this paper, FDI is based on checking for an inconsistency between the measured and predicted behaviours using viability theory concepts and sets. Finally, an example is provided in order to show the usefulness of the proposed approach.     

Fault detection for nonlinear discrete-time systems via deterministic learning

Recently, an approach for the rapid detection of small oscillation faults based on deterministic learning theory was proposed for continuous-time systems. In this paper, a fault detection scheme is proposed for a class of nonlinear discrete-time systems via deterministic learning. By using a discrete-time extension of deterministic learning algorithm, the general fault functions (i.e., the internal dynamics) underlying normal and fault modes of nonlinear discrete-time systems are locally-accurately approximated by discrete-time dynamical radial basis function (RBF) networks. Then, a bank of estimators with the obtained knowledge of system dynamics embedded is constructed, and a set of residuals are obtained and used to measure the differences between the dynamics of the monitored system and the dynamics of the trained systems. A fault detection decision scheme is presented according to the smallest residual principle, i.e., the occurrence of a fault can be detected in a discrete-time setting by comparing the magnitude of residuals. The fault detectability analysis is carried out and the upper bound of detection time is derived. A simulation example is given to illustrate the effectiveness of the proposed scheme.     

State estimation and decoupling of unknown inputs in uncertain LPV systems using interval observers

This paper proposes a linear parameter varying (LPV) interval observer for state estimation and unknown inputs decoupling in uncertain continuous-time LPV systems. Two different problems are considered and solved: (1) the evaluation of the set of admissible values for the state at each instant of time; and (2) the unknown input observation, i.e. the design of the observer in such a way that some information about the nature of the unknown inputs affecting the system can be obtained. In both cases, analysis and design conditions, which rely on solving linear matrix inequalities (LMIs), are provided. The effectiveness and appeal of the proposed method is demonstrated using an illustrative application to a two-joint planar robotic manipulator.     

Fault detection for linear distributed-parameter systems using finite-dimensional functional observers

In this article, finite-dimensional residual generators are directly designed for Riesz-spectral systems with bounded input and output operators to detect faults. This is achieved by using finite-dimensional observers, that can estimate linear functionals of the state without spillover. These observers allow for a decoupling of the unknown disturbances from the estimation error dynamics under mild assumptions. Then, a finite-dimensional residual generator is obtained by approximately decoupling the state from the residual, that is generated by the observer states and the outputs. It is shown that the resulting approximation error can be made small by increasing the observer order. Then, fault detection with the finite-dimensional residual generator can be assured by introducing a time-varying threshold. A faulty Euler–Bernoulli beam with structural damping illustrates the proposed finite-dimensional fault detection approach.     

A novel design approach for switched LPV controllers

A novel design procedure for switched linear parameter-varying (LPV) controller is proposed. The new procedure, based on the Youla parameterisation ideas, decomposes the controller design into two steps. One focuses on ensuring global stability and the other on fulfilling the local performance specifications. This scheme allows the design of each local controller independently of each other, which may achieve higher performance without compromising the global stability and also simplifies the synthesis and the implementation of the local controllers. Any standard LPV synthesis procedure can be used to design these controllers. On the other hand, the stability during switching is ensured with convex constraints and no restrictions are imposed on the switching among controllers. The use of the proposed procedure is illustrated with an active magnetic bearing example.     

Fault detection for discrete-time networked nonlinear systems with incomplete measurements

This article addresses the problem of fault detection (FD) for discrete-time networked systems with global Lipschitz nonlinearities and incomplete measurements, including time delays, packet dropouts and signal quantisation. By utilising a discrete-time homogeneous Markov chain, an improved model which considers packet dropout compensation has been proposed to describe the above network-induced phenomena. We aim to design a mode-dependent fault detection filter (FDF) such that the FD system is asymptotically mean-square stable and satisfies a prescribed attenuation level. The addressed FD problem is then converted into an auxiliary H _∞ filtering problem of Markov jump system with time-varying delay. A sufficient condition for the existence of the FDF is derived in terms of certain linear matrix inequalities (LMIs). When these LMIs are feasible, the explicit expression of the desired FDF can also be characterised. A numerical example is exploited to show the effectiveness of the results obtained.     

Stabilizing a class of nonlinear parameter-varying systems using interval observer based on a piecewise framework

This article addresses an interval observer-based control for stabilizing a class of nonlinear parameter-varying systems with noisy output by designing a switching surface. An input-dependent interval observer is firstly developed to estimate the lower and upper bounds of the states. Next, a switching-based controller is designed to stabilize the interval observer which implies the stability of the main parameter-varying system. The developed stabilizing switching surfaces are designed based on the outputs of the main system and the bounds of the states of the observer. By choosing an appropriate piecewise Lyapunov function, the closed-loop stability analysis of the interval observer system leads to a set of linear matrix inequalities including stability and Metzler constraints, simultaneously. The effectiveness of the proposed method is verified using the simulation results.     

Fault detection for nonlinear networked control systems with stochastic interval delay characterisation

In this article, we are concerned with the fault detection (FD) problem for nonlinear networked control systems (NCSs) with network-induced stochastic interval delay. By employing the information of probabilistic distribution of networked-induced time-varying delay, nonlinear constraint and the FD filter, nonlinear stochastic delay system model is established. Based on the obtained nonlinear model, utilising FD filter as residual generator, FD of nonlinear NCSs is formulated as nonlinear H _∞-filtering problem. Especially, the stochastic stability and prescribed H _∞ attenuation level are achieved using the Lyapunov functional approach, the desired FD filter is constructed in terms of certain linear matrix inequalities, which depends on not only nonlinear level but also on delay-interval and delay-interval-occurrence-rate. Numerical examples are provided to illustrate the effectiveness and applicability of proposed technique.     

Improved results for linear discrete-time systems with an interval time-varying input delay

This paper addresses the problem of delay-dependent stability analysis and controller synthesis for a discrete-time system with an interval time-varying input delay. By dividing delay interval into multiple parts and constructing a novel piecewise Lyapunov–Krasovskii functional, an improved delay-partitioning-dependent stability criterion and a stabilisation criterion are obtained in terms of matrix inequalities. Compared with some existing results, since a tighter bounding inequality is employed to deal with the integral items, our results depend on less number of linear matrix inequality scalar decision variables while obtaining same or better allowable upper delay bound. Numerical examples show the effectiveness of the proposed method.     

Invariant set-based robust fault detection and optimal fault estimation for discrete-time LPV systems with bounded uncertainties

ABSTRACT

This paper proposes an invariant set-based robust fault detection (FD) and optimal fault estimation (FE) method for discrete-time linear parameter varying (LPV) systems with bounded uncertainties. Firstly, a novel invariant-set construction method for discrete-time LPV systems is proposed if and only if the system is poly-quadratically stable, which need not satisfy the condition that there must exist a common quadratic Lyapunov function for all vertex matrices of the system compared to the traditional invariant-set construction methods. Furthermore, by using a shrinking procedure, we provide minimal robust positively invariant (mRPI) set approximations that are always positively invariant at each step of iteration and allow a priori desired precision to obtain a high sensitivity of FD. Owing to the existence of invariant set-based FD phase, the assumption that the initial faults should be bounded by a given set can be avoided for FE. We compute an optimal parametric matrix gain by minimising the Frobenius norm-based size of the corresponding FE set to obtain the optimal FE performance. Theoretically, any trajectory in the FE tube can be chosen as a specific-value estimation for the real fault signals. Finally, a vehicle dynamics system is used to illustrate the effectiveness of the proposed method.     

区间离散广义系统状态反馈鲁棒H∞控制

讨论了一类区间离散广义系统的状态反馈鲁棒H_∞控制问题.在给出区间离散广义系统的等价描述之后,基于系统参数矩阵不等式,得到了问题可解的充分条件,并给出了状态反馈控制器显式表示.所得的控制器保证闭环系统正则,具有因果关系,稳定并且满足给定的H_∞性能指标.数值例子说明了该方法的正确性.     

结构不确定离散系统的最优非脆弱保成本控制

讨论了一类不确定线性离散系统的最优非脆弱保成本控制问题.考虑的系统和状态反馈控制器均具有时变的结构化的不确定性.基于线性矩阵不等式的方法,给出了存在和设计非脆弱保成本控制律的一个充分条件,以及在使二次成本函数上界最小意义下,最优非脆弱保成本控制律的凸优化设计方法.并用数值例子说明该方法降低了成本函数上界的保守性.     

Hankel-norm model approximation for LPV systems with parameter-varying time delays

This article is concerned with Hankel-norm model approximation (HNMA) for linear parameter-varying systems with parameter-varying time delays. For a given stable system, our attention is focussed on the construction of reduced-order models, which approximate the original system well in a Hankel-norm sense. By applying the slack matrix approach, a delay-dependent sufficient condition is proposed for the robustly asymptotic stability with a Hankel-norm error performance for the error system. Then, the HNMA problem is solved by using the projection approach, which casts the model approximation into a sequential minimisation problem subject to linear matrix inequality constraints by employing the cone complementary linearisation algorithm. Finally, a numerical example is provided to illustrate the effectiveness of the proposed methods.     

基于观测器的离散时滞系统的故障诊断

研究含有测量时滞的线性离散系统的故障诊断问题,提出一种测量时滞的无时滞转换方法和基于降维状态观测器而不利用残差体现故障的故障诊断方法.首先通过构造一个含有故障状态的增广系统和进行测量时滞的无时滞转换,将时滞系统的故障诊断问题转化为无时滞增广系统的状态观测问题;然后给出了其诊断误差能按预先指定的指数速率趋于零的故障诊断器的设计方法.仿真算例验证了该方法的可行性和有效性.     

Simultaneous sensor and actuator fault estimation for continuous-time polytopic LPV system

In this paper, we study the problem of state estimation and both actuator and sensor fault detection for Linear Polytopic Parameter-Varying (LPV) system. The contribution of this work consists on the design of a novel robust adaptive observer based on polyquadratic formulations with a new set of relaxation. An optimisation problem is given in term of Linear Matrix Inequalities (LMI) in order to guarantee the stability of the system and the asymptotic convergence of faults error. A comparative study is made to prove the efficiency of the proposed polyquadratic algorithms against the quadratic ones. The performances and effectiveness of the proposed methods are illustrated in a simulation example where constant and variable actuator and sensor faults were detected.     

区间离散Lurie系统的绝对稳定性

用Lyapunov函数研究了具有单调扇形限制的多非线性项的区间离散Lurie系统的鲁棒绝对稳定性, 给出了此类区间离散Lurie系统的鲁棒绝对稳定性的矩阵不等式形式的代数判据, 并与区间对称矩阵稳定性建立了联系.     

Decentralized observers with consensus filters for distributed discrete-time linear systems

This paper presents a decentralized observer with a consensus filter for the state observation of discrete-time linear distributed systems. Each agent in the distributed system has an observer with a model of the plant that utilizes the set of locally available measurements, which may not make the full plant state detectable. This lack of detectability is overcome by utilizing a consensus filter that blends the state estimate of each agent with its neighbors’ estimates. It is proven that the state estimates of the proposed observer exponentially converge to the actual plant states under arbitrarily changing, but connected, communication and pseudo-connected sensing graph topologies. Except these connectivity properties, full knowledge of the sensing and communication graphs is not needed at the design time. As a byproduct, we obtained a result on the location of eigenvalues, i.e., the spectrum, of the Laplacian for a family of graphs with self-loops.