基于模糊观测器的不确定非线性系统故障检测方法

给出了一种不确定非线性系统的基于模糊观测器的故障诊断方法。用T-S模型描述不确定非线性系统,从而得到一种新的模糊观测器,并给出了其稳定性约束条件LMI。将模糊观测器和实际系统的输出之差作为残差可对不确定非线性系统进行故障检测。最后给出了一个控制系统感应电机的故障诊断应用实例。     

航天器壳体压力自动加载系统的研究

航天器壳体的压力加载实验对于航天器的安全飞行具有十分重要的意义。研究并建立了航天器壳体水压自动加载系统的数学模型,针对该系统的高度非线性以及高低压特性显著不同的特点,利用误差及误差导数构造了一种变比例因子的模糊PD控制器。采用一种新型的遗传算法对控制器系统参数进行寻优。针对模糊控制器控制规则表与量化比例因子的不同特点,分别采用两种不同的编码方法,进而采用两种不同的遗传操作算子与遗传操作概率。通过MATLAB与C 语言接口编程实现对系统的仿真设计。实验表明该方法取得了良好的压力加载效果。     

进化算法在系统可靠性多目标优化中的应用

为解决复杂系统可靠性设计的多目标优化问题，采用NSGA-Ⅱ进化算法，在一次性获得大量均匀分布的非劣解后，根据定义的满意度函数对每个非劣解进行模糊评价。运用群体排序、小生境、比较操作和精英保留等关键技术，将整个非劣解集分为若干个具有不同性能特征的类，决策者可根据各自的偏好从中选择最终的满意解。分析结果表明，进化算法具有较高的优化效率。     

基于模糊逻辑的GPS/DR组合导航系统地图匹配算法

利用地图匹配技术能够使用高精度的电子地图位置信息改善 GPS/ DR组合导航系统的定位精度。提出一种基于模糊数学方法和统计概率准则的地图匹配算法 ,在融合定位传感器数据和路段位置信息的基础上 ,通过模糊逻辑评判完成最佳匹配路段的挑选 ,并对匹配修正结果的可信度作出评价。仿真试验的结果证明该算法的有效性。     

竞争学习模糊神经网络及在导弹故障诊断中的应用

尽管基于解析冗余的故障诊断方法有许多突出的优点而越来越多地得到的研究和应用，但它依赖于系统的模型，当系统存在非线性或不确定性时，存在难以建模的困难，模糊神经网络可以通过学习建立系统的模型，且模型参数有明确的物理意义，初始参数易于选择，成为解决这一问题的优选途径，作者通过把模糊神经网络的学习转化为竞争聚类和线性优化问题，基于竞争聚类和最小二乘原理，提出了一种模糊神经网络学习算法，并在某伺服机构上进行     

Aircraft robust multidisciplinary design optimization methodology based on fuzzy preference function

This paper presents a Fuzzy Preference Function-based Robust Multidisciplinary Design Optimization (FPF-RMDO) methodology. This method is an effective approach to multidisciplinary systems, which can be used to designer experiences during the design optimization process by fuzzy preference functions. In this study, two optimizations are done for Predator MQ-1 Unmanned Aerial Vehicle (UAV): (A) deterministic optimization and (B) robust optimization. In both problems, minimization of takeoff weight and drag is considered as objective functions, which have been optimized using Non-dominated Sorting Genetic Algorithm (NSGA). In the robust design optimization, cruise altitude and velocity are considered as uncertainties that are modeled by the Monte Carlo Simulation (MCS) method. Aerodynamics, stability and control, mass properties, performance, and center of gravity are used for multidisciplinary analysis. Robust design optimization results show 46% and 42% robustness improvement for takeoff weight and cruise drag relative to optimal design respectively.     

Prediction of aerodynamic characteristics of an aircraft model with and without winglet using fuzzy logic technique

This paper describes the potentials of an aircraft model without and with winglet attached with NACA wing No. 65-3-218. Based on the longitudinal aerodynamic characteristics analyzing for the aircraft model tested in low subsonic wind tunnel, the lift coefficient (CL) and drag coefficient (CD) were investigated respectively. Wind tunnel test results were obtained for CL and CD versus the angle of attack α for three Reynolds numbers Re (1.7×¹⁰⁵, 2.1×¹⁰⁵, and 2.5×¹⁰⁵) and three configurations (configuration 1: without winglet, configuration 2: winglet at 0° and configuration 3: winglet at 60°). Compared with conventional technique, fuzzy logic technique is more efficient for the representation, manipulation and utilization. Therefore, the primary purpose of this work was to investigate the relationship between lift coefficients and drag coefficients with free-stream velocities and angle of attacks, and to illustrate how fuzzy expert system (FES) might play an important role in prediction of aerodynamic characteristics of an aircraft model with the addition of winglet. In this paper, an FES model was developed to predict the lift and drag coefficients of the aircraft model with winglet at 60°. The mean relative error of measured and predicted values (from FES model) were 6.52% for lift coefficient and 4.74% for drag coefficient. For all parameters, the relative error of predicted values was found to be less than the acceptable limits (10%). The goodness of fit of prediction (from FES model) values were found as 0.94 for lift coefficient and 0.98 for drag coefficient which were close to 1.0 as expected.     

基于聚类模糊系统的动态数据野值剔除方法

针对影响遥测参数处理和分析的野值问题,提出了基于聚类法实时设计模糊系统实现动态数据野值辨识和剔除的新方法。该方法能够自适应跟踪不同变化特性的遥测参数,基于聚类法实现模糊系统的动态建模并获得预测值与观测值的残差序列,再按照狄克松准则实现野值的快速剔除。对实测数据的仿真实验表明：该方法能够显著降低动态建模的复杂度,快速跟踪信号变化,方法可行且有效。     

飞控系统故障检测的参数模糊自适应调节

提出通过模型参数的模糊比例积分自适应调节，以校正基于模型的飞控系统故障检测中的系统数学模型偏差。针对模型中误差差较大的迎角导数值，将俯仰角加速度的测量值与教学模型估计值之差作为比例积分调节的反馈量，动态实时校正数学模型参数。     

自由飞行空间机器人基座位姿调整的模糊PD控制

由于自由飞行空间机器人处于微重力的环境,因此其在目标获取的过程中必然会出现因机械臂运动和环境影响而导致基座的复杂运动.本文设计了自由飞行空间机器人位姿调整的模糊PD算法,根据接收到的实时位置信息,空间机器人可以自主地调整基座的姿态和位置来校正位姿误差,保证目标的稳定捕获.利用开发的实验平台与传统的on/off式控制器进行了实验对比,验证了此方法在稳定性、控制精度和燃料消耗上都有较好的表现.