基于模糊理论的遮阳罩结构可靠性评估

本文探讨了基于模糊理论的结构可靠性评估。运用模糊可靠度理论对遮阳罩可靠度进行了评估和设计,在保证系统结构可靠度的同时,有效的降低了结构的质量,实现了预期的结构优化。     

模糊控制算法分析及改进

基于E.H.Mamdai等人的模糊控制算法,本文讨论了模糊控制器参数的选择及对系统输出性能的影响。与已有的方法不同,本文注重物理概念的分析,并研究了模糊控制器参数的自调整问题。这是因为基本模糊控制器参数的选择难以同时兼顾控制系统的动静态性能,一般只好采取折衷的方法。为了改善控制系统性能,一种实用的方法是在线调整模糊控制器的参数。文中提出了一种分段式自调参方案,仿真结果表明该方案优于已有的自调参方案。为了达到有效的调参目的,本文给出了模糊控制器参数初始配置的一种关系,并通过仿真,验证了该关系是确切的。最后,基于模糊控制算法的特点,探讨了一种新的模糊控制算法的构思,作为今后进一步研究的问题。     

一种模糊Modular神经网络模型及其应用

将神经网络模糊系统与模糊C均值聚法相结合，对模糊Modular神经网络进行研究，提出了该模糊神经网络模型的多输出结构及其学习算法，据此开发了模糊神经网络诊断系统，并将其用于某电源分系统的诊断分析，运行的结果表明，该网络模型优于一般神经网络。     

可靠性模糊优化设计方法

本文论述了可靠性模糊优化设计方法，它是可靠性化设计、模糊优化设计的深化。可靠性模糊优化设计既考虑随机因素对产品的影响，又考虑了模糊因素对产品的影响，优化结果往往比普通优化设计、可靠设计、模糊优化设计要好。可靠性优化设计是一种值得推广的优化设计方法。     

一种卫星导航模拟器置信度评估方案及应用

置信度评估能够为卫星导航模拟器的研制与改进提供依据。提出了一种基于对数最小二乘的模糊层次分析法和相似度法相结合的置信度评估方案。该方案利用基于对数最小二乘的模糊层次分析法将卫星导航模拟器系统分解为若干子系统或模型,并利用相似度法计算各个子系统或模型的置信度,同时使用模糊层次分析法计算各子系统或模型的权重向量,而后再逐级综合得到模拟器系统的总置信度。该方案能够将复杂系统逐层细化,且求解的子系统或模型的权重向量与置信度较为客观真实,具有重要的工程参考价值。     

漂浮基空间机械臂姿态、关节协调运动的模糊小波神经网络控制

讨论了本体姿态受控、位置不受控制的漂浮基空间机械臂系统协调运动的动力学控制问题. 根据系统位置几何关系、动量守恒关系和第二类拉格朗日方程, 建立漂浮基空间机械臂系统的动力学方程. 在此基础上, 针对系统参数未知的情况, 设计了一种采用小波基函数作为模糊隶属度函数的模糊神经网络控制器, 以控制空间机械臂的本体姿态和机械臂两关节铰协调地完成各自在关节空间的期望运动. 其特点是不要求系统动力学方程关于惯性参数呈线性函数关系, 甚至不需要知道系统参数;而且网络权值是采用反向传播算法根据误差进行在线学习, 使模糊神经网络获得更强的自学习和自适应能力, 同时也节省了离线学习的时间. 系统数值仿真的结果证实上述控制方案是行之有效的.      

空间交会对接的智能控制

探讨了交会对接过程自动寻的阶段的智能控制策略及绕飞和最后逼近阶段的模糊控制问题,并针对实际条件给出了仿真结果,证明介绍的控制策略是可行的。     

Review of hybrid electric powered aircraft,its conceptual design and energy management methodologies

The paper overviews the state-of-art of aircraft powered by hybrid electric propulsion systems. The research status of the design and energy management of hybrid aircraft and hybrid propulsion systems are further reviewed. The first contribution of the review is to demonstrate that, in the context of relatively underdeveloped electrical storage technologies, the study of mid-scale hybrid aircraft can contribute the most to both theoretical and practical knowledge. Meanwhile, the profits and potential drawbacks of applying hybrid propulsion to mid-scale hybrid airplanes have not been thoroughly illustrated. Secondly, as summed in the overview of design methodologies, the multi-objective optimization transcends the single-objective one. The potential of the hybrid propulsion system can be thoroughly evaluated in only one optimization run, if several objectives optimized simultaneously. Yet there are few researches covering the conceptual design of hybrid aircraft using multi-objective optimization. The review of the most popular energy management strategies discloses the third research gap—current methodologies favoured in hybrid ground vehicles do not consider the aircraft safety. Additionally, both non-causal and causal energy management are needed for performing a complicated flight mission with several sub-tasks.     

A combined technique of Kalman filter,artificial neural network and fuzzy logic for gas turbines and signal fault isolation

The target of this paper is the performance-based diagnostics of a gas turbine for the automated early detection of components malfunctions. The paper proposes a new combination of multiple methodologies for the performance-based diagnostics of single and multiple failures on a two-spool engine. The aim of this technique is to combine the strength of each methodology and provide a high success rate for single and multiple failures with the presence of measurement malfunctions. A combination of KF (Kalman Filter), ANN (Artificial Neural Network) and FL (Fuzzy Logic) is used in this research in order to improve the success rate, to increase the flexibility and the number of failures detected and to combine the strength of multiple methods to have a more robust solution. The Kalman filter has in his strength the measurement noise treatment, the artificial neural network the simulation and prediction of reference and deteriorated performance profile and the fuzzy logic the categorization flexibility, which is used to quantify and classify the failures. In the area of GT (Gas Turbine) diagnostics, the multiple failures in combination with measurement issues and the utilization of multiple methods for a 2-spool industrial gas turbine engine has not been investigated extensively.This paper reports the key contribution of each component of the methodology and brief the results in the quantification and classification success rate. The methodology is tested for constant deterioration and increasing noise and for random deterioration. For the random deterioration and nominal noise of 0.4%, in particular, the quantification success rate is above 92.0%, while the classification success rate is above 95.1%. Moreover, the speed of the data processing (1.7 s/sample) proves the suitability of this methodology for online diagnostics.     

基于DSP的飞机全电刹车模糊神经网络控制系统

介绍了一种基于DSP的飞机全电刹车模糊神经网络控制系统 ,此系统以电作动器取代液压机构。由于不使用液压机构使得系统更加安全 ,同时刹车效率也有所提高。仿真及试验结果显示该系统具有良好的性能 ,达到了设计要求。