Delta算子离散化系统H_∞故障检测滤波器设计

基于线性矩阵不等式(LMI)方法,研究基于Delta算子离散化系统的H∞故障检测问题.把故障和扰动看作广义扰动,利用H∞控制理论,以LMI形式给出了Delta算子离散化系统的H∞故障检测滤波器存在的充分条件.仿真实例表明了设计方法的有效性,所设计的滤波器不但能保证闭环Delta算子系统系统渐近稳定,具有所期望的H∞性能,且保证快速采样时其对故障的检测效果接近于连续系统的检测效果.     

传感器有故障的Delta算子线性不确定系统的鲁棒D–稳定

研究传感器有故障的Delta算子线性不确定系统的鲁棒D–稳定问题, 旨在设计控制器以消除系统不确定性和传感器故障的影响, 确保闭环系统极点落在复平面指定圆盘区域内. 由于传感器故障具有连续的故障模型, 本文采用线性矩阵不等式(LMI)方法, 利用故障模型的结构信息, 得出了Delta算子系统状态反馈鲁棒D–稳定控制器存在的充分条件, 并由此提出相应控制器设计方法. 数值算例表明设计方法的可行性和有效性.     

高速采样下含网络攻击的信息物理系统$H_/H_infty$故障检测

研究高速采样情况下,含有网络攻击的信息物理系统多目标故障检测问题.考虑系统同时存在时变时延、执行器网络攻击和传感器网络攻击,基于Delta算子对上述系统进行离散化处理,建立在高速采样的条件下,故障与攻击并存的离散时间模型.构造H＿/H_∞故障检测滤波器,使系统具有对随机扰动的鲁棒性,且具有对检测信号的高灵敏性.采用Lyapunov-Krasovskii泛函和线性矩阵不等式的方法,提出系统具有渐近稳定性以及H＿/H_∞性能的充分条件.仿真结果验证了所提方法的可行性和有效性.     

Delta算子时滞系统的可靠D--镇定

研究同时含有执行器故障和传感器故障的Delta算子时滞系统的鲁棒可靠D-镇定问题.利用矩阵特征值理论和线性矩阵不等式方法,给出了Delta算子时滞系统D-稳定的充分条件,进而,针对同时含有执行器故障和传感器故障的Delta算子范数有界参数不确定时滞系统,设计鲁棒可靠D-镇定状态反馈控制器,使得对于所有容许的不确定性、执行器故障和传感器故障,Delta算子闭环时滞系统的极点均落在复平面指定圆盘区域内.最后,通过数值算例验证了控制器设计方法的可行性和有效性.     

区间Delta算子系统的鲁棒性分析与控制

研究Delta算子描述的区间系统的鲁棒稳定分析与鲁棒综合设计问题，在给出区间系统的一种等价描述后，利用Delta域的Lyapunov稳定性理论，提出了区间Delta算子系统鲁棒稳定的充分条件及状态反馈控制设计方法，所得结论可以将连续区间系统与离散区间系统的有关结果纳入到Delta算子系统的统一框架中。     

不确定模糊Delta算子系统的鲁棒H∞控制

研究了一类T-S模糊Delta算子系统的鲁棒H_∞控制问题.首先利用LMI形式给出了模糊Delta算子系统鲁棒镇定的充分条件,然后构造了可使闭环系统鲁棒稳定且对可允许的参数变化满足H_∞性能的状态反馈控制律.本文结果统一了连续与离散模糊系统的鲁棒H_∞镇定设计结论,数值算例说明了方法的可行性.     

模糊Delta算子系统的鲁棒稳定性分析与控制

研究一类由Delta算子描述的T-S型模糊系统的鲁棒稳定性与状态反馈控制设计问题。基于Delta域的Lyapunov稳定性理论，利用线性矩阵不等式(LMI)的方法，给出了不确定模糊Delta算子系统鲁棒稳定及存在状态反馈控制器使得闭环系统稳定的充分条件。这不仅将连续与离散不确定模糊系统的有关结果纳入Delta算子系统的统一框架中，也为Delta算子方法在非线性系统中的应用研究提供了一种有效途径。数值算例说明了该方法的有效性。     

具有不确定丢包率和时变采样周期的Delta算子系统故障检测

研究一类由Delta算子描述具有不确定丢包率的时变采样网络控制系统故障检测问题.数据包丢失发生在传感器至控制器、控制器到执行器的数据传输过程中,丢包模型采用两个相互独立的伯努利随机变量表示,假设传感器至控制器通道中的丢包率是不确定的,其均值由常数和不确定值两部分组成.时变采样周期利用有限长切换序列表示可降低保守性.采用Delta域的Lyapunov函数方法,提出所考虑的增广系统渐近稳定且具有${\textstyle H_{\infty     

基于LMI的Delta域内的H_∞状态反馈设计

利用 L MI方法讨论和研究 Delta算子描述下的线性定常系统的 H∞ 控制问题 ,并给出了连续系统、Z变换所得到的离散系统和 Delta算子所描述的系统三者的 H∞ 控制问题的比较。结果表明 ,Delta算子所描述的系统的设计方法更适合于离散系统 ,尤其适合于小采样周期系统     

Delta算子系统的状态反馈鲁棒镇定与鲁棒H∞控制

研究Delta算子描述的线性不确定离散系统的鲁棒镇定与H∞控制问题,提出了“Delta算子系统二次稳定与二次可镇定”的概念,推导出Delta算子不确定系统鲁棒二次可镇定的充要条件及其状态反馈控制律,基于Delta算子界实引理,给出闭环不确定系统具有H∞范数界的充分条件和状态反馈设计,所得结论将连续与离散系统的有关结果统一于Delta算子框架。     

基于Delta算子的线性系统输入输出能量解耦

本文提出了Delta算子描述的线性系统的输入) 输出能量解耦方法.它使得任何一个输入能量主要控制对应的一个输出的能量,对其它输出能量的影响尽可能小.所得结论将连续与离散系统的有关结果统一于Delta算子系统.􀁱     

基于趋近律方法的Delta算子滑模变结构控制系统

针对高速信号不确定滑模变结构控制系统的抖振问题,提出一种基于Delta算子离散化方法的不确定Delta算子系统的滑模变结构控制器。基于反正切函数给出了一种改进的Delta算子离散趋近律,将系统的不确定部分用其上、下确界代替,然后设计滑模变结构控制律。仿真结果表明了该方法的可行性和有效性,对内部参数摄动和外部干扰具有良好的完全鲁棒性。因此,基于该趋近律方法设计的滑模变结构控制系统既能在有限时间内快速趋近切换面,又最终稳定于平衡状态。     

State feedback design for singularly perturbed system using unified approach

The state feedback design for singuhrly perturbed systems described in Delta operator is considered. The composite state feedback controller for slow and fast subsystems is designed by using the direct method. The obtained results can bring previous conclusions of continuous and discrete time systems into the unified Delta framework. A simulation example is presented to demonstrate the validity and efficiency, of the design.     

Fault detection and isolation in manufacturing systems with an identified discrete event model

In this article a generic method for fault detection and isolation (FDI) in manufacturing systems considered as discrete event systems (DES) is presented. The method uses an identified model of the closed-loop of plant and controller built on the basis of observed fault-free system behaviour. An identification algorithm known from literature is used to determine the fault detection model in form of a non-deterministic automaton. New results of how to parameterise this algorithm are reported. To assess the fault detection capability of an identified automaton, probabilistic measures are proposed. For fault isolation, the concept of residuals adapted for DES is used by defining appropriate set operations representing generic fault symptoms. The method is applied to a case study system.     

Design of stochastic fault tolerant control for H2 performance

In this paper, the controller synthesis problem for fault tolerant control systems (FTCS) with stochastic stability and H₂ performance is studied. System faults of random nature are modelled by a Markov chain. Because the real system fault modes are not directly accessible in the context of FTCS, the controller is reconfigured based on the output of a fault detection and identification (FDI) process, which is modelled by another Markov chain. Then state feedback and output feedback control are developed to achieve the mean square stability (MSS) and the H₂ performance for both continuous‐time and discrete‐time systems with model uncertainties. Copyright © 2006 John Wiley & Sons, Ltd.     

Delta算子系统简述

本文围绕Delta算子系统基本理论,对Delta算子系统的最新进展做了简要的综述.首先,本文介绍Delta算子系统的研究背景.其次,给出Delta算子系统的基本性能,并与传统移位算子离散系统进行性能对比.再次,阐述了Delta算子系统在鲁棒控制、滤波器设计、时滞系统、故障诊断及滑模控制上的研究进展.然后,对Delta算子系统在有限频域和网络化控制两个方向上的未来研究工作做出了展望.最后,通过一个仿真表明:Delta算子系统在快速采样条件下具有数值优势.     

A gain-varying UIO approach with adaptive threshold for FDI of nonlinear F16 systems

A discrete gain-varying unknown input observer (UIO) method is presented for actuator fault detection and isolation (FDI) problems in this paper. A novel residual scheme together with a moving horizon threshold is proposed. This design methodology is applied to a nonlinear F16 system with polynomial aerodynamics coefficient expressions, where the coefficient expressions for the F16 system and UIOs may be slightly different. The simulation results illustrate that a satisfactory FDI performance can be achieved even when the F16 system is under the environment of model uncertainties, exogenous noise and measurement errors.     

Distributed sensor fault diagnosis in a class of interconnected nonlinear uncertain systems

In this paper, a distributed sensor fault detection and isolation (FDI) method is developed for a class of interconnected nonlinear uncertain systems. In the distributed FDI architecture, a FDI component is designed for each subsystem in the interconnected system. For each subsystem, its corresponding local FDI component is designed by utilizing local measurements and certain communicated information from neighboring FDI components associated with subsystems that are directly interconnected to the particular subsystem under consideration. Under certain assumptions, adaptive thresholds for distributed sensor fault detection and isolation in each subsystem are derived, ensuring robustness with respect to interactions among subsystems and system modeling uncertainty. Moreover, the fault detectability condition is rigorously investigated, characterizing the class of sensor faults in each subsystem that is detectable by the proposed distributed FDI method. Additionally, the stability and learning capability of the distributed adaptive fault isolation estimators is established. A simulation example of interconnected inverted pendulums mounted on carts is used to illustrate the effectiveness of the distributed FDI method.     

Cascade filter structure for sensor/actuator fault detection and isolation of satellite attitude control system

This paper presents a new scheme for fault detection and isolation in a satellite system. The purpose of this paper is to develop detection, isolation and identification algorithms based on a cascade filter for both total and partial faults in a satellite attitude control system (ACS). The cascade filter consists of a decentralized Kalman filter (DKF) and a bank of interacting multiple model (IMM) filters. The cascade filter is utilized for detection and diagnosis of anticipated sensor and actuator faults in a satellite ACS. Other fault detection and isolation (FDI) schemes are compared with the proposed FDI scheme. The FDI procedure using a cascade filter was developed in three stages. In the first stage, two local filters and a master filter detect sensor faults. In the second stage, the FDI scheme checks sensor residuals to isolate sensor faults, and 11 Extended Kalman filters with actuator fault models detect wherever actuator faults occur. In the third stage of the FDI scheme, four filters identify the fault type, which is either a total or partial fault. An important feature of the proposed FDI scheme is that it can decrease fault isolation time and accomplish not only fault detection and isolation but also fault type identification using a scalar penalty in the conditional density function.     

The merits of exergy-based fault detection in petrochemical processes

The complexity and multi-domain nature of petrochemical (PC) plants make the application of conventional model-based fault detection and isolation (FDI) techniques a challenging endeavour. Although hybrid FDI schemes aim to address this shortfall, many are simply a combination of data-driven techniques that exclude physical system information. In this work, a hybrid approach to FDI of a PC process is proposed that is based on an exergy-data abstraction. Data from an actual system is abstracted to system exergy, based on physical knowledge of the system and then used as a diagnostic metric for the FDI scheme. In this paper, it is shown why energy-based approaches are lacking when considering petrochemical processes. After presenting a novel method for the real-time, automatic calculation of chemical exergy in Aspen HySys^® the applicability of exergy-based fault detection is investigated. Application of the exergy-based fault detection scheme shows a marked improvement over the energy-based approach with perfect detectability and isolability of the considered process faults. The exergy-based fault detection technique shows merit in comparison to the energy-based detection scheme. Additionally, and more importantly, exergy-based characterisation allows the use of more sophisticated model-based fault detection schemes to petrochemical processes.