航空发动机神经网络自学习PID控制

将神经网络与传统的PID控制相结合,构成神经网络自学习PID控制,用神经网络在线整定PID控制器的比例、积分及微分三个参数,使被控对象跟踪理想参考模型的输出。该系统具有自学习能力,能适用于非线性、时变的被控对象。将神经网络自学习PID控制方法用于航空发动机全包线控制以及蜕化发动机的控制,进行了数字仿真,验证了该方法的有效性。     

Forecasting space weather: Can new econometric methods improve accuracy?

Space weather forecasts are currently used in areas ranging from navigation and communication to electric power system operations. The relevant forecast horizons can range from as little as 24 h to several days. This paper analyzes the predictability of two major space weather measures using new time series methods, many of them derived from econometrics. The data sets are the A_p geomagnetic index and the solar radio flux at 10.7 cm. The methods tested include nonlinear regressions, neural networks, frequency domain algorithms, GARCH models (which utilize the residual variance), state transition models, and models that combine elements of several techniques. While combined models are complex, they can be programmed using modern statistical software. The data frequency is daily, and forecasting experiments are run over horizons ranging from 1 to 7 days. Two major conclusions stand out. First, the frequency domain method forecasts the A_p index more accurately than any time domain model, including both regressions and neural networks. This finding is very robust, and holds for all forecast horizons. Combining the frequency domain method with other techniques yields a further small improvement in accuracy. Second, the neural network forecasts the solar flux more accurately than any other method, although at short horizons (2 days or less) the regression and net yield similar results. The neural net does best when it includes measures of the long-term component in the data.     

贝叶斯网络在飞控系统可靠性评估中的应用

把一种基于贝叶斯网络的故障树分析法应用于飞控系统俯仰控制功能的可靠性评估中,突破传统故障树分析法的局限性——各部件独立、状态为二值,不但可以计算系统的可靠性指标,而且可以定量给出某个事件或某几个事件在系统可靠性中所占的地位,找出系统的薄弱环节。     

基于贯序正则极端学习机的时间序列预测及其应用

为实现对液压泵特征参数的在线预测,提出一种贯序正则极端学习机(SRELM),并研究了基于SRELM的预测方法.SRELM根据结构风险最小化原理实现网络训练,其网络权值可随新样本的逐次加入而递推求解,具有泛化能力强与训练速度快的优点,因此适于特征参数的在线预测.基于SRELM的预测方法利用特征参数训练SRELM模型,以逐...     

New Neural Network Response Surface Methods for Reliability Analysis

This article presents two new kinds of artificial neural network (ANN) response surface methods (RSMs): the ANN RSM based on early stopping technique (ANNRSM-1), and the ANN RSM based on regularization theory (ANNRSM-2). The following improvements are made to the conventional ANN RSM (ANNRSM-0): 1) by monitoring the validation error during the training process, ANNRSM-1 determines the early stopping point and the training stopping point, and the weight vector at the early stopping point, which corresponds to the ANN model with the optimal generalization, is finally returned as the training result; 2) according to the regularization theory, ANNRSM-2 modifies the conventional training performance function by adding to it the sum of squares of the network weights, so the network weights are forced to have smaller values while the training error decreases. Tests show that the performance of ANN RSM becomes much better due to the above-mentioned improvements: first, ANNRSM-1 and ANNRSM-2 approximate to the limit state function (LSF) more accurately than ANNRSM-0; second, the estimated failure probabilities given by ANNRSM-1 and ANNRSM-2 have smaller errors than that obtained by ANNRSM-0; third, compared with ANNRSM-0, ANNRSM-1 and ANNRSM-2 require much fewer data samples to achieve stable failure probability results.     

Cooperative Routing for Maximizing Network Performance of Wireless Networks

To greatly increase spectral efficiency and improve network performance in wireless networks,a novel cooperative routing algorithm,namely maximum throughput cooperative routing(MTCR) algorithm,is proposed.According to cooperative link model,throughput analysis is presented to evaluate performance improvement in the process of exploiting cooperative commu-nication from physical layer to higher layer.Taking the throughput improvement as performance metric,a cooperative relay se-lection scheme is developed.Finally,based on the route constructed by adaptive forwarding cluster routing(AFCR) algorithm,each node on the route selects the optimum cooperative node from all the potential cooperative nodes to construct the coopera-tive link with maximum throughput so that cooperative route with maximum network throughput from source to destination can be set up.Simulation results show that compared with the noncooperative routing algorithm and minimum power selection de-code-and-forward(MPSDF) routing algorithm,the proposed algorithm can obviously improve network throughput in the pres-ence of low transmission power,large number of nodes and high spectral efficiency.     

网络安全体系分析

阐明了网络安全体系是一个保证网络安全的体系结构,涉及到法律、技术、管理等方面;从 TCP/IP 协议体系角度对网络安全存在的问题入手分析,并对目前采用的安全策略及安全技术进行了剖析。     

基于业务持续性的航空公司机务维修安全评估

为降低航空公司的事故率,提出基于业务持续性的航空公司机务维修安全评估方法。从人件、硬件、环境、应急救援和软件5个方面来建立风险评估体系,根据风险评估体系建立贝叶斯网络模型,利用能够反映航空公司安全维修状况的历史定量数据作为训练参数。在建立起评估模型的基础上,对航空公司的机务维修进行安全评估和敏感性分析。实验证明,方法能预测风险发展趋势,有效地降低事故发生率,为航空公司的安全运行提供科学依据。     

基于粗糙集-神经网络的机载设备故障诊断方法研究

提出了一种基于粗糙集-神经网络的故障诊断方法。将粗糙集理论同神经网络结合起来可以用于机载设备的故障诊断。采用粗糙集理论对原始故障诊断样本进行处理,并根据条件属性对决策属性的正域的大小来选择条件属性,提取出对诊断故障贡献最大的最小故障特征集,从而确定神经网络的拓扑结构;通过训练神经网络建立故障特征与故障之间的映射关系,实现故障的诊断。通过A320飞机燃油系统的故障诊断仿真实例,表明这种故障诊断方法的有效性。     

一种移动卫星网络最小费用切换算法(英文)

For mobile satellite networks, an appropriate handover scheme should be devised to shorten handover delay with optimized application of network resources. By introducing the handover cost model of service, this article proposes a rerouting triggering scheme for path optimization after handover and a new minimum cost handover algorithm for mobile satellite networks. This algorithm ensures the quality of service （QoS） parameters, such as delay, during the handover and minimizes the handover costs. Simulation indicates that this algorithm is superior to other current algorithms in guaranteeing the QoS and decreasing handover costs.