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.     

Measuring reliability under epistemic uncertainty:Review on non-probabilistic reliability metrics

In this paper, a systematic review of non-probabilistic reliability metrics is conducted to assist the selection of appropriate reliability metrics to model the influence of epistemic uncertainty. Five frequently used non-probabilistic reliability metrics are critically reviewed, i.e., evidence-theory-based reliability metrics, interval-analysis-based reliability metrics, fuzzy-interval-analysis-based reliability metrics, possibility-theory-based reliability metrics (posbist reliability) and uncertainty-theory-based reliability metrics (belief reliability). It is pointed out that a qualified reli-ability metric that is able to consider the effect of epistemic uncertainty needs to (1) compensate the conservatism in the estimations of the component-level reliability metrics caused by epistemic uncertainty, and (2) satisfy the duality axiom, otherwise it might lead to paradoxical and confusing results in engineering applications. The five commonly used non-probabilistic reliability metrics are compared in terms of these two properties, and the comparison can serve as a basis for the selection of the appropriate reliability metrics.     

Crashworthiness uncertainty analysis of typical civil aircraft based on Box–Behnken method

The crashworthiness is an important design factor of civil aircraft related with the safety of occupant during impact accident. It is a highly nonlinear transient dynamic problem and may be greatly influenced by the uncertainty factors. Crashworthiness uncertainty analysis is conducted to investigate the effects of initial conditions, structural dimensions and material properties. Simplified finite element model is built based on the geometrical model and basic physics phenomenon. Box–Behnken sampling and response surface methods are adopted to obtain gradient information.Results show that the proposed methods are effective for crashworthiness uncertainty analysis.Yield stress, frame thickness, impact velocity and angle have great influence on the failure behavior,and yield stress and frame thickness dominate the uncertainty of internal energy. Failure strain and tangent modulus have the smallest influence on the initial peak acceleration, and gradients of mean acceleration increase because the appearance of material plastic deformation and element failure.     

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.     

Adaptive path planning for unmanned aerial vehicles based on bi-level programming and variable planning time interval

This paper presents an adaptive path planner for unmanned aerial vehicles (UAVs) to adapt a real-time path search procedure to variations and fluctuations of UAVs’ relevant performances, with respect to sensory capability, maneuverability, and flight velocity limit. On the basis of a novel adaptability-involved problem statement, bi-level programming (BLP) and variable planning step techniques are introduced to model the necessary path planning components and then an adaptive path planner is developed for the purpose of adaptation and optimization. Additionally, both probabilistic-risk-based obstacle avoidance and performance limits are described as path search constraints to guarantee path safety and navigability. A discrete-search-based path planning solution, embedded with four optimization strategies, is especially designed for the planner to efficiently generate optimal flight paths in complex operational spaces, within which different surface-to-air missiles (SAMs) are deployed. Simulation results in challenging and stochastic scenarios firstly demonstrate the effectiveness and efficiency of the proposed planner, and then verify its great adaptability and relative stability when planning optimal paths for a UAV with changing or fluctuating performances.     

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.     

A new method of single celestial-body sun positioning based on theory of mechanisms

Considering defects of current single celestial-body positioning methods such as discon-tinuity and long period, a new sun positioning algorithm is herein put forward. Instead of tradi-tional astronomical spherical trigonometry and celestial coordinate system, the proposed new positioning algorithm is built by theory of mechanisms. Based on previously derived solar vector equations (from a C1R2P2 series mechanism), a further global positioning method is developed by inverse kinematics. The longitude and latitude coordinates expressed by Greenwich mean time (GMT) and solar vector in local coordinate system are formulated. Meanwhile, elimination method of multiple solutions, errors of longitude and latitude calculation are given. In addition, this algo-rithm has been integrated successfully into a mobile phone application to visualize sun positioning process. Results of theoretical verification and smart phone’s test demonstrate the validity of pre-sented coordinate’s expressions. Precision is shown as equivalent to current works and is acceptable to civil aviation requirement. This new method solves long-period problem in sun sight running fix-ing and improves applicability of sun positioning. Its methodology can inspire development of new sun positioning device. It would be more applicable to be combined with inertial navigation systems for overcoming discontinuity of celestial navigation systems and accumulative errors of inertial nav-igation systems.     

基于满意博弈论的复杂低空飞行冲突解脱方法

复杂低空空域环境下多飞行器冲突解脱方法可以有效地提供冲突解脱策略,实时规划飞行器四维航迹,避免飞行器之间发生危险接近事故或者碰撞,从而保障空域运行安全。然而,随着飞行器数目的不断增长,冲突解脱面临"维数灾难",导致问题具有高维度、强耦合等难点。因此,传统的优化方案难以得到令人满意的方案。为了提高冲突解脱效率,保障运行安全,基于满意博弈论方法,考虑低空飞行器运动特点,构建冲突解脱模型,设计冲突解脱方法。飞行器主要采用改变航向角的策略。通过基于条件概率的方法来建立"社会关系",即当前飞机所做的决策对其他飞机产生的影响。每个飞行器在决策时,都会受到优先级比自己高的决策者的影响。基于满意博弈论的冲突解脱方法不仅可以有效地解决当前飞行器的冲突问题,而且兼顾探测范围内的其他飞行器,避免当前解脱策略导致与其他飞行器冲突,实现整体最优化。最后,通过在极端典型飞行冲突场景中实验验证表明,基于满意博弈论的冲突解脱方法可以实时高效实现大规模飞行器的冲突解脱,保障飞行安全且控制经济成本。     

基于贝叶斯理论的低循环疲劳寿命模型不确定性量化

为量化低循环疲劳寿命模型中的不确定性因素,利用贝叶斯理论,采用经典的模型校准形式确立了寿命模型的不确定性量化形式,并结合正态性检验对误差项进行验证;应用马尔可夫链-蒙特卡罗(MCMC)算法获得了模型参数后验分布的抽样样本,在小子样试验数据条件下确定了低循环疲劳寿命的95%不确定性区间,较好地覆盖了寿命的分散性;对参数样本进行了相关性分析,并将异方差回归概率模型与贝叶斯概率模型进行了比较。最后,利用Morris全局灵敏度分析方法获得了Manson-Coffin模型参数的全局灵敏度指标;同时,验证了在模型参数对先验信息敏感,或者说在先验信息影响极大的情况下,采用无信息先验处理方法的合理性。     

Uncertain multiobjective redundancy allocation problem of repairable systems based on artificial bee colony algorithm

Based on the uncertainty theory, this paper is devoted to the redundancy allocation problem in repairable parallel-series systems with uncertain factors, where the failure rate, repair rate and other relative coefficients involved are considered as uncertain variables. The availability of the system and the corresponding designing cost are considered as two optimization objectives. A crisp multiobjective optimization formulation is presented on the basis of uncertainty theory to solve this resultant problem. For solving this problem efficiently, a new multiobjective artificial bee colony algorithm is proposed to search the Pareto efficient set, which introduces rank value and crowding distance in the greedy selection strategy, applies fast non-dominated sort procedure in the exploitation search and inserts tournament selection in the onlooker bee phase. It shows that the proposed algorithm outperforms NSGA-II greatly and can solve multiobjective redundancy allocation problem efficiently. Finally, a numerical example is provided to illustrate this approach.     

基于总能量理论的着舰飞行/推力控制系统

为提高舰载飞机在低动压着舰条件下飞行操纵性能和实现飞行航迹/速度之间的解耦,首先设计了阻尼器,使飞机的短周期阻尼达到了一级飞行品质的要求;然后,基于总能量控制理论设计了着舰飞行/推力综合控制系统。该控制系统使航迹角的响应带宽为1.21 rad/s。仿真结果表明,该系统能够在保持速度恒定的条件下实现航迹角的快速响应,而且对气动参数摄动具有较强的鲁棒性。     

基于CR理论的大柔性机翼几何非线性结构建模

大柔性机翼在气动载荷的作用下,将产生显著的弹性变形,常规线弹性理论的小变形假设不再成立,需要采用能够考虑几何非线性效应的结构模型进行求解。基于CR(Co-Rotational)共旋转有限元理论,把几何非线性大变形分解为刚体的旋转和平移及局部坐标系下的弹性变形,建立了适用于大柔性机翼几何非线性变形描述的结构模型。以大柔性悬臂梁为例,采用载荷增量法,研究了集中弯矩作用下的非线性变形特征,对静力学方法进行了验证,并讨论了耦合加载几何非线性变形特征;以类"太阳神"太阳能布局无人机(UAV)为例,研究了其几何非线性大变形特性。     

A novel LAAS pseudo-range error over-bound method based on improved pseudo-range error distribution model

The high level of safety demand of civil aviation requests local area augmentation system (LAAS) extremely high navigation integrity performance. A new LAAS pseudo-range error overbound method is proposed in this paper to improve the integrity of LAAS. Firstly, a more practical pseudo-range error distribution model is established. Then, by calculating the relationship between the statistical uncertainty of the model parameter and the integrity risk, a new method is proposed to calculate the pseudo-range error over-bound model. This method can effectively reduce the inflation factor and the resulting conservativeness of the over-bound model. Comparative experiments show that the method proposed in this paper performs better and satisfies the requirements of real applications.