Vulnerability analysis for airport networks based on fuzzy soft sets: From the structural and functional perspective

Recently,much attention has been paid to the reliability and vulnerability of critical infrastructure.In air traffic systems,the vulnerability analysis for airport networks can be used to guide air traffic administrations in their prioritization of the maintenance and repair of airports,as well as to avoid unnecessary disturbances in the planning of flight schedules.In this paper,the evaluation methods of airport importance and network efficiency are established.Firstly,the evaluation indices of airport importance are proposed from both the topological and functional perspectives.The topological characteristics come from the structure of airport network and the functional features stem from the traffic flow distribution taking place inside the network.Secondly,an integrated evaluation method based on fuzzy soft set theory is proposed to identify the key airports,which can fuse together importance indices over different time intervals.Thirdly,an airport network efficiency method is established for the purpose of assessing the accuracy of the evaluation method.Finally,empirical studies using real traffic data of US and China’s airport networks show that the evaluation method proposed in this paper is the most accurate.The vulnerability of US and China’s airport networks is compared.The similarities and differences between airport geography distribution and airport importance distribution are discussed here and the dynamics of airport importance is studied as well.     

Epistemic uncertainty quantification in flutter analysis using evidence theory

Aimed at evaluating the structural stability and flutter risk of the system, this paper manages to quantify epistemic uncertainty in flutter analysis using evidence theory, including both parametric uncertainty and method selection uncertainty, on the basis of information from limited experimental data of uncertain parameters. Two uncertain variables of the actuator coupling system with unknown probability distributions, that is bending and torsional stiffness, which are both described with multiple intervals and the basic belief assignment(BBA) extricated from the modal test of actuator coupling systems, are taken into account. Considering the difference in dealing with experimental data by different persons and the reliability of various information sources, a new combination rule of evidence––the generalized lower triangular matrices method is formed to acquire the combined BBA. Finally the parametric uncertainty and the epistemic uncertainty of flutter analysis method selection are considered in the same system to realize quantification. A typical rudder of missile is selected to examine the present method, and the dangerous range of velocity as well as relevant belief and plausibility functions is obtained. The results suggest that the present method is effective in obtaining the lower and upper bounds of flutter probability and assessing flutter risk of structures with limited experimental data of uncertain parameters and the belief of different methods.     

A generalized rough set-based information filling technique for failure analysis of thruster experimental data

Interval-valued data and incomplete data are two key problems for failure analysis of thruster experimental data and have been basically solved by the proposed methods in this paper. Firstly, information data acquired from the simulation and evaluation system formed as intervalvalued information system （IIS） is classified by the interval similarity relation. Then, as an improvement of the classical rough set, a new kind of generalized information entropy called ＂H＇-information entropy＂ is suggested for the measurement of uncertainty and the classification ability of IIS. There is an innovative information filling technique using the properties of H＇-information entropy to replace missing data by some smaller estimation intervals. Finally, an improved method of failure analysis synthesized by the above achievements is presented to classify the thruster experimental data, complete the information, and extract the failure rules. The feasibility and advantage of this method is testified by an actual application of failure analysis, whose performance is evaluated by the quantification of E-condition entropy.     

Testability evaluation using prior information of multiple sources

Testability plays an important role in improving the readiness and decreasing the lifecycle cost of equipment. Testability demonstration and evaluation is of significance in measuring such testability indexes as fault detection rate（FDR） and fault isolation rate（FIR）, which is useful to the producer in mastering the testability level and improving the testability design, and helpful to the consumer in making purchase decisions. Aiming at the problems with a small sample of testability demonstration test data（TDTD） such as low evaluation confidence and inaccurate result, a testability evaluation method is proposed based on the prior information of multiple sources and Bayes theory. Firstly, the types of prior information are analyzed. The maximum entropy method is applied to the prior information with the mean and interval estimate forms on the testability index to obtain the parameters of prior probability density function（PDF）, and the empirical Bayesian method is used to get the parameters for the prior information with a success-fail form. Then, a parametrical data consistency check method is used to check the compatibility between all the sources of prior information and TDTD. For the prior information to pass the check, the prior credibility is calculated. A mixed prior distribution is formed based on the prior PDFs and the corresponding credibility. The Bayesian posterior distribution model is acquired with the mixed prior distribution and TDTD, based on which the point and interval estimates are calculated.Finally, examples of a flying control system are used to verify the proposed method. The results show that the proposed method is feasible and effective.     

Fuzzy robust nonlinear control approach for electro-hydraulic flight motion simulator

A fuzzy robust nonlinear controller for hydraulic rotary actuators in flight motion simulators is proposed. Compared with other three-order models of hydraulic rotary actuators, the proposed controller based on first-order nonlinear model is more easily applied in practice, whose control law is relatively simple. It not only does not need high-order derivative of desired command,but also does not require the feedback signals of velocity, acceleration and jerk of hydraulic rotary actuators. Another advantage is that it does not rely on any information of friction, inertia force and external disturbing force/torque, which are always difficult to resolve in flight motion simulators. Due to the special composite vane seals of rectangular cross-section and goalpost shape used in hydraulic rotary actuators, the leakage model is more complicated than that of traditional linear hydraulic cylinders. Adaptive multi-input single-output(MISO) fuzzy compensators are introduced to estimate nonlinear uncertain functions about leakage and bulk modulus. Meanwhile, the decomposition of the uncertainties is used to reduce the total number of fuzzy rules. Different from other adaptive fuzzy compensators, a discontinuous projection mapping is employed to guarantee the estimation process to be bounded. Furthermore, with a sufficient number of fuzzy rules, the controller theoretically can guarantee asymptotic tracking performance in the presence of the above uncertainties, which is very important for high-accuracy tracking control of flight motion simulators.Comparative experimental results demonstrate the effectiveness of the proposed algorithm, which can guarantee transient performance and better final accurate tracking in the presence of uncertain nonlinearities and parametric uncertainties.     

Airworthiness Compliance Verification Method Based on Simulation of Complex System

A study is conducted on a new airworthiness compliance verification method based on pilot-aircraft-environment complex system simulation. Verification scenarios are established by "block diagram" method based on airworthiness criteria. A pilotaircraft-environment complex model is set up and a virtual flight testing method based on connection of MATLAB/Simulink and Flightgear is proposed. Special researches are conducted on the modeling of pilot manipulation stochastic parameters and manipulation in critical situation. Unfavorable flight factors of certain scenario are analyzed, and reliability modeling of important system is researched. A distribution function of small probability event and the theory on risk probability measurement are studied. Nonlinear function is used to depict the relationship between the cumulative probability and the extremum of the critical parameter. A synthetic evaluation model is set up, modified genetic algorithm (MGA) is applied to ascertaining the distribution parameter in the model, and a more reasonable result is obtained. A clause about vehicle control functions (VCFs) verification in MIL-HDBK-516B is selected as an example to validate the practicability of the method.     

An improved α-cut approach to transforming fuzzy membership function into basic belief assignment

In practical applications, pieces of evidence originated from different sources might be modeled by different uncertainty theories. To implement the evidence combination under the Dempster–Shafer evidence theory(DST) framework, transformations from the other type of uncertainty representation into the basic belief assignment are needed. a-Cut is an important approach to transforming a fuzzy membership function into a basic belief assignment, which provides a bridge between the fuzzy set theory and the DST. Some drawbacks of the traditional a-cut approach caused by its normalization step are pointed out in this paper. An improved a-cut approach is proposed, which can counteract the drawbacks of the traditional a-cut approach and has good properties. Illustrative examples, experiments and related analyses are provided to show the rationality of the improved a-cut approach.     

Validation of Flight Control Law Based on LFT and Structured Singular Value

The main goal of flight clearance is to use the structured singular value (μ) analysis of the flight control system when some pa-rameters in the system vary in a certain range. As the μ-analysis can only be done on a linear fractional transformation (LFT) model, the first step of flight clearance is to generate the LFT model of the flight control system. In this paper, based on the introduction of basic theory of LFT and μ-analysis, an X-fighter is chosen as an example to utilize the proposed methods. In order to realize the flight clear-ance process automatically, a novel software package based on MATLAB programming language is developed. The results of simulation experiments validate the feasibility and effectiveness of the novel methods proposed in this paper.     

Attitude tracking control for variable structure near space vehicles based on switched nonlinear systems

An adaptive robust attitude tracking control law based on switched nonlinear systems is presented for a variable structure near space vehicle (VSNSV) in the presence of uncertainties and disturbances. The adaptive fuzzy systems are employed for approximating unknown functions in the flight dynamic model and their parameters are updated online. To improve the flight robust performance, robust controllers with adaptive gains are designed to compensate for the approximation errors and thus they have less design conservation. Moreover, a systematic procedure is developed for the synthesis of adaptive fuzzy dynamic surface control (DSC) approach. According to the common Lyapunov function theory, it is proved that all signals of the closed-loop system are uniformly ultimately bounded by the continuous controller. The simulation results demonstrate the effectiveness and robustness of the proposed control scheme.     

Uncertainty analysis and design optimization of hybrid rocket motor powered vehicle for suborbital flight

In this paper, we propose an uncertainty analysis and design optimization method and its applications on a hybrid rocket motor(HRM) powered vehicle. The multidisciplinary design model of the rocket system is established and the design uncertainties are quantified. The sensitivity analysis of the uncertainties shows that the uncertainty generated from the error of fuel regression rate model has the most significant effect on the system performances. Then the differences between deterministic design optimization(DDO) and uncertainty-based design optimization(UDO) are discussed. Two newly formed uncertainty analysis methods, including the Kriging-based Monte Carlo simulation(KMCS) and Kriging-based Taylor series approximation(KTSA), are carried out using a global approximation Kriging modeling method. Based on the system design model and the results of design uncertainty analysis, the design optimization of an HRM powered vehicle for suborbital flight is implemented using three design optimization methods: DDO, KMCS and KTSA. The comparisons indicate that the two UDO methods can enhance the design reliability and robustness. The researches and methods proposed in this paper can provide a better way for the general design of HRM powered vehicles.In this paper,we propose an uncertainty analysis and design optimization method and its applications on a hybrid rocket motor(HRM)powered vehicle.The multidisciplinary design model of the rocket system is established and the design uncertainties are quantified.The sensitivity analysis of the uncertainties shows that the uncertainty generated from the error of fuel regression rate model has the most significant effect on the system performances.Then the differences between deterministic design optimization(DDO)and uncertainty-based design optimization(UDO)are discussed.Two newly formed uncertainty analysis methods,including the Kriging-based Monte Carlo simulation(KMCS)and Kriging-based Taylor series approximation(KTSA),are carried out using a global approximation Kriging modeling method.Based on the system design model and the results of design uncertainty analysis,the design optimization of an HRM powered vehicle for suborbital flight is implemented using three design optimization methods:DDO,KMCS and KTSA.The comparisons indicate that the two UDO methods can enhance the design reliability and robustness.The researches and methods proposed in this paper can provide a better way for the general design of HRM powered vehicles.     

机载武器作战使用可靠性综合验证

为减少机载武器可靠性验证试验样本量和降低验证试验风险,通过对机载武器作战使用可靠性验证的工程需求、试验方案、统计模型、验证方法等进行研究,提出了一种利用研制试验数据和定型飞行试验数据的作战使用可靠性综合验证方法。针对机载武器的特点,根据变动统计理论,考虑性能验证与可靠性验证的要求,综合利用研制试验数据和定型飞行试验数据,给出作战使用可靠性综合验证方案,进而制定设计定型飞行试验方案。实例表明,在不改变生产方风险和使用方风险的情况下,该方法可有效地验证机载武器挂飞可靠性和自主飞行可靠性指标,显著地减少定型飞行试验样本量,大幅节约研制成本,并缩短研制周期。     

基于模糊贝叶斯的导弹武器系统可靠性和可用性分析

综合考虑了装备、保障系统、管理和人员、保障方案等要素,提出了一种基于模糊贝叶斯的导弹武器系统可靠性和可用性分析方法,将先验信息和样本数据有效融合,采用模糊随机变量来处理数据的不确定。通过算例分析,验证了模型的有效性。结论表明,该方法所得的评估结果符合装备的实际情况。     

Real-time decision aiding: aircraft guidance for wind shearavoidance

Modern estimation theory and artificial intelligence technology are applied to the Wind Shear Safety Advisor, a conceptual airborne advisory system to help flight crews avoid or survive encounter with hazardous low-altitude wind shear. Numerical and symbolic processes of the system fuse diverse, time-varying data from ground-based and airborne measurements. Simulated wind-shear-encounter scenarios illustrate the need to consider a variety of factors for optimal decision reliability. The wind-shear-encounter simulations show the potential of the Wind Shear Safety Advisor for effectively integrating the available information, highlighting the benefits of the computational techniques employed     

无人机动态飞行参数处理及应用策略

飞行参数处理能够有效地评价无人机在飞行过程中的行为,将其与故障注入技术相集成能够合成测试无人机系统可靠性的完整技术。文中结合无人机的特点提出了一种面向飞行参数时序数据流的飞行参数处理方案,利用飞行参数处理技术实时判读无人机的行为,监测机载设备故障在无人机系统中的传播过程。首先在分析无人机飞行参数数据特征的基础上,着重研究了飞行参数实时数据采集和数据处理方法;然后构造了一个实际的飞行参数处理系统UAVFDD_01,并分析了动态飞行参数处理过程。系统可靠性测试试验结果表明设计的系统能够满足无人机可靠性测试的要求。     

A new structural reliability index based on uncertainty theory

The classical probabilistic reliability theory and fuzzy reliability theory cannot directly measure the uncertainty of structural reliability with uncertain variables,i.e.,subjective random and fuzzy variables.In order to simultaneously satisfy the duality of randomness and subadditivity of fuzziness in the reliability problem,a new quantification method for the reliability of structures is presented based on uncertainty theory,and an uncertainty-theory-based perspective of classical Cornell reliability index is explored.In this paper,by introducing the uncertainty theory,we adopt the uncertain measure to quantify the reliability of structures for the subjective probability or fuzzy variables,instead of probabilistic and possibilistic measures.We utilize uncertain variables to uniformly represent the subjective random and fuzzy parameters,based on which we derive solutions to analyze the uncertainty reliability of structures with uncertainty distributions.Moreover,we propose the Cornell uncertainty reliability index based on the uncertain expected value and variance.Experimental results on three numerical applications demonstrate the validity of the proposed method.     

模糊随机可靠性综合方法在涡轮盘可靠性分析中的应用

提出了模糊随机可靠性分析的近似解析和数字模拟综合方法,基于模糊变量的等价随机化变换,可以方便地得到模糊随机失效概率的计算公式,并建立了模糊随机可靠性分析的一次二阶矩法。定义了同时考虑基本变量和状态都含有模糊随机双重不确定性的可靠度指标,探讨了多个模式情况下模糊随机可靠性分析方法。所提出的方法被用于发动机涡轮盘的应力、应变和低周疲劳寿命模糊随机可靠性分析,证明了该方法是可行的。     

基于动态贝叶斯网络和模糊灰度理论的飞行训练评估

针对战斗机飞行训练中的评估问题,提出了一种基于动态贝叶斯网络和模糊灰度理论的评估方法。首先,分析了训练过程中典型飞行参数与机动动作的因果关系,根据专家经验与先验知识构建基于动态贝叶斯网络的机动动作识别模型,推理得到战斗机机动动作识别结果。然后,建立战斗机飞行训练评估指标体系,根据战斗机机动识别结果选择飞行训练评估指标,并采用综合赋权法确定了指标权重。最后,建立灰度模糊评估矩阵,结合飞行训练过程中各评估指标的飞行数据得到评估结果。实验结果表明该评估方法能够根据飞行过程中的参数信息进行机动动作识别及飞行训练评估,提高了飞行训练评估的效率。     

基于滑窗检测的机载设备故障诊断仿真系统

根据机载设备故障诊断的需求,结合飞机性能监控系统的结构框架和机载设备的特点,提出基于快速存取记录器（QAR）记录的飞行数据和滑窗检测原理的机载设备故障诊断算法,并实现相应的机栽设备故障诊断仿真系统。在简述QAR数据译码与数据选择方法的基础上,论述了滑窗检测的原理并对其性能进行分析：设计实现了基于QAR的机载设备故障诊断仿真系统并给出仿真结果。结果表明,该系统可以有效诊断存在的故障,并能大大降低虚警概率,对保障飞行安全具有重要意义。     

机载多传感器信息融合试飞技术研究

在简要论述机载多传感器信息融合基本原理和不同传感器工作特性的基础上,提出了机载多传感器信息融合的试飞思路、试飞设计原则以及最终试飞结果的评价方法,并在实际的飞行试验中得到了应用。试飞结果表明:利用试飞方法能够充分验证机载多传感器信息融合系统的功能、性能,而且对于同类航空电子系统多传感器信息融合的飞行验证具有借鉴意义。     

Gray bootstrap method for estimating frequency-varying random vibration signals with small samples

During environment testing, the estimation of random vibration signals （RVS） is an important technique for the airborne platform safety and reliability. However, the available meth- ods including extreme value envelope method （EVEM）, statistical tolerances method （STM） and improved statistical tolerance method （ISTM） require large samples and typical probability distri- bution. Moreover, the frequency-varying characteristic of RVS is usually not taken into account. Gray bootstrap method （GBM） is proposed to solve the problem of estimating frequency-varying RVS with small samples. Firstly, the estimated indexes are obtained including the estimated inter- val, the estimated uncertainty, the estimated value, the estimated error and estimated reliability. In addition, GBM is applied to estimating the single flight testing of certain aircraft. At last, in order to evaluate the estimated performance, GBM is compared with bootstrap method （BM） and gray method （GM） in testing analysis. The result shows that GBM has superiority for estimating dynamic signals with small samples and estimated reliability is proved to be 100% at the given confidence level.