A possibilistic clustering approach to novel fault detection and isolation

In this paper, a new approach for fault detection and isolation that is based on the possibilistic clustering algorithm is proposed. Fault detection and isolation (FDI) is shown here to be a pattern classification problem, which can be solved using clustering and classification techniques. A possibilistic clustering based approach is proposed here to address some of the shortcomings of the fuzzy c-means (FCM) algorithm. The probabilistic constraint imposed on the membership value in the FCM algorithm is relaxed in the possibilistic clustering algorithm. Because of this relaxation, the possibilistic approach is shown in this paper to give more consistent results in the context of the FDI tasks. The possibilistic clustering approach has also been used to detect novel fault scenarios, for which the data was not available while training. Fault signatures that change as a function of the fault intensities are represented as fault lines, which have been shown to be useful to classify faults that can manifest with different intensities. The proposed approach has been validated here through simulations involving a benchmark quadruple tank process and also through experimental case studies on the same setup. For large scale systems, it is proposed to use the possibilistic clustering based approach in the lower dimensional approximations generated by algorithms such as PCA. Towards this end, finally, we also demonstrate the key merits of the algorithm for plant wide monitoring study using a simulation of the benchmark Tennessee Eastman problem.     

Differential geometry based active fault tolerant control for aircraft

This work shows how to use a differential geometry tool to design a novel nonlinear active fault tolerant flight control system for aircraft. The proposed control scheme consists of two main subsystems: a controller, which is designed for the nominal plant, and a fault detection and diagnosis module, which provides fault estimation. A further feedback loop exploits the fault estimation to accommodate faults affecting the system. The estimate convergence and the stability of the active fault tolerant flight controller are theoretically proved. Finally, high fidelity simulations show the effectiveness of the scheme.     

外商直接投资类型转变的实证分析

论文在文献评述的基础上利用1992—2008年日本、美国等10个主要经济体对华直接投资数据,实证检验了外商直接投资(FDI)类型与中国市场规模、要素成本、投资环境之间的关系。结果表明:FDI在中国既具有垂直型FDI的特征,同时又具有水平型FDI的特征,但水平型特征更为突出。随着中国经济的迅速发展和市场规模的扩大,进入中国的FDI正由垂直型向水平型转变。在实证分析的基础上,针对当前的FDI类型转变提出了相关政策建议。     

FDI对物流业技术溢出效应的实证研究——以河南省为例

首先利用Malmquist指数方法测算物流业全要素生产率(TFP),并将其分解成技术进步指数与技术效率指数;然后利用脉冲响应函数和格兰杰检验分别动态模拟FDI对技术进步的影响程度,以及FDI与技术进步的因果关系.结果表明:FDI对物流业生产率的溢出机制主要是通过对技术进步的提升表征出来的;物流业FDI对技术进步的影响,其格兰杰检验不通过,说明外商直接投资在物流业的技术溢出效应不显著.     

省域FDI区域差异及其影响因素比较分析

以FDI为切入点,分析省域之间的差异及其影响因素,平衡FDI地域流向,促进经济协调发展。本文主要通过定量分析2005-2014年近十年来,安徽省和江苏省各地级市FDI的变化情况。结果表明:安徽省外商直接投资引起的区域差异,无论是相对差异还是绝对差异都比较大;而江苏省近十年来外商直接投资对区域差异影响整体较小。安徽省与江苏省仍有小的差距,宏观层面体现在区域的不平衡发展上,有待进一步改善。     

基于联立方程模型的 FDI、产业结构与碳排放互动关系研究

通过中国30个省区1997—2012年能源消费数据,依据电（热）碳分摊原则测算出各省区的碳排放量,运用面板单位根和面板协整理论,建立了包含经济增长、碳排放以及外商直接投资在内的联立方程来分析区域 FDI 与二氧化碳排放的关系。结果表明：联立方程中每个模型的协整关系是成立的,区域 FDI 对区域碳排放的直接弹性是－0．001,间接弹性是0．146,区域产业结构对区域碳排放的直接弹性是0．032,间接弹性是1．882。研究进一步发现区域 FDI、区域经济增长、区域产业结构与区域能源强度都是促进区域碳排放的重要因素,并且区域 FDI 和区域碳排放量对区域经济增长呈现出双向的因果关系。     

重庆市外国直接投资与出口贸易结构关系研究

重庆市自直辖以来,进出口贸易总额呈加速上升的趋势。伴随着重庆市对外贸易规模的高速增长,外商直接投资也逐年递增。因此,研究FDI的变动对重庆市出口贸易结构的影响,具有一定的现实意义。本文主要通过回顾FDI与对外贸易相关理论,结合重庆市利用FDI与出口贸易结构的现状,利用1990-2012年度重庆的FDI 及对外贸易数据,通过构建模型,运用单位根检验、协整检验及误差修成模型对FDI与重庆市出口贸易结构关系进行了实证分析。结果表明,FDI对出口贸易总额和出口贸易结构的优化影响是显著的,提出了相关的政策建议。     

Full-order observer-based actuator fault detection and reduced-order observer-based fault reconstruction for a class of uncertain nonlinear systems

This paper considers observer-based actuator fault detection and reconstruction problems for uncertain nonlinear systems. Based on a kind of full-order observer which is robust to disturbances but sensitive to actuator faults, a single detection observer is constructed to produce a residual which can be used to alarm the occurrence of the actuator faults when at least one actuator fault occurs indeed. The full-order observer is adaptive one because an adaptation law which can adjust the Lipschitz constant of Lipschitz term is introduced. For this reason, the Lipschitz constant can be unknown in our design. After this, a kind of reduced-order observer is developed by choosing a special observer gain matrix. Based on the reduced-order observer, we provide a kind of unknown information estimating method which can be used to not only reconstruct the actuator faults but also estimate the disturbances of the system. In simulation, a real model of the seventh-order aircraft is used to illustrate the effectiveness of the proposed methods.     

Robust actuator fault isolation and management in constrained uncertain parabolic PDE systems

This paper presents a methodology for the design of an integrated robust fault detection and isolation (FDI) and fault-tolerant control (FTC) architecture for distributed parameter systems modeled by nonlinear parabolic Partial Differential Equations (PDEs) with time-varying uncertain variables, actuator constraints and faults. The design is based on an approximate finite-dimensional system that captures the dominant dynamics of the PDE system. Initially, an invertible coordinate transformation-obtained through judicious actuator placement-is used to transform the approximate system into a form where the evolution of each state is excited directly by only one actuator. For each state, a robustly stabilizing bounded feedback controller that achieves an arbitrary degree of asymptotic attenuation of the effect of uncertainty is then synthesized and its constrained stability region is explicitly characterized in terms of the constraints, the actuator locations and the size of the uncertainty. A key idea in the controller synthesis is to shape the fault-free closed-loop response of each state in a prescribed fashion that facilitates the derivation of (1) dedicated FDI residuals and thresholds for each actuator, and (2) an explicit characterization of the state-space regions where FDI can be performed under uncertainty and constraints. A switching law is then derived to orchestrate actuator reconfiguration in a way that preserves robust closed-loop stability following FDI. Precise FDI rules and control reconfiguration criteria that account for model reduction errors are derived for the implementation of the FDI-FTC structure on the distributed parameter system. Finally, the results are demonstrated using a tubular reactor example.     

Nonlinear aircraft sensor fault reconstruction in the presence of disturbances validated by real flight data

This paper proposes an approach for Inertial Measurement Unit sensor fault reconstruction by exploiting a ground speed-based kinematic model of the aircraft flying in a rotating earth reference system. Two strategies for the validation of sensor fault reconstruction are presented: closed-loop validation and open-loop validation. Both strategies use the same kinematic model and a newly-developed Adaptive Two-Stage Extended Kalman Filter to estimate the states and faults of the aircraft. Simulation results demonstrate the effectiveness of the proposed approach compared to an approach using an airspeed-based kinematic model. Furthermore, the major contribution is that the proposed approach is validated using real flight test data including the presence of external disturbances such as turbulence. Three flight scenarios are selected to test the performance of the proposed approach. It is shown that the proposed approach is robust to model uncertainties, unmodeled dynamics and disturbances such as time-varying wind and turbulence. Therefore, the proposed approach can be incorporated into aircraft Fault Detection and Isolation systems to enhance the performance of the aircraft.