质量矩导弹的神经网络及自适应非线性控制

本文对质量矩控制导弹的动力学方程简化和控制系统的设计进行了研究。详细阐述了所提出的控制方法，介绍了径向基单隐层神经网络进行误差补偿的算法原理，用Lyapunov理论证明了所采用方法的稳定性。在给出了质量矩导弹的六自由度动力学方程和简化后的方程后，用所提出的方法设计控制系统。通过仿真分析，得出了本文所提出的方法具有较好的误差补偿能力的结论。     

超弹性N形杆纯弯曲力矩理论建模和试验验证

为了使N形杆在空间结构中顺利展开,对其缠绕过程中的力学特性进行了分析.基于协变基向量法建立了纯弯曲条件下各向同性单片带簧在缠绕时应变能理论模型,并采用最小势能原理推导了弯矩的理论模型,然后通过拟合曲率推导了N形杆缠绕时的理论模型.研制了4根N形杆样件,并搭建了试验平台,使用数显式推拉力计分别对杆件在缠绕过程的拉力进行了...     

基于相空间重构的网络流量RBF神经网络预测

应用混沌理论,分析了网络流量,用单变量的网络流量时闯序列重构与网络动力系统等距同构的相空间,进而计算了实际网络的关维数和Lyapunov指数,并证实了网络流量存在混沌特性;据此建立了基于径向基函数（RBF）神经网络的模型,并对实际网络数据流进行了预测。仿真结果表明,相对于其他前馈神经网络预测,基于混沌理论的RBF神经网络预测方法学习速度快,预测精度高。     

民用飞机冲压空气涡轮系统适航工程技术研究

冲压空气涡轮系统是一种飞机应急能源,其在紧急情况下为飞机提供应急液压源和/或应急电源,对飞机应对紧急情况至关重要。参照AP-21-AA-2011-03-R4中关于航空器生命周期审定过程划分及合格审定活动,结合某型民用飞机冲压空气涡轮系统研制过程,从识别审定基础开始,将适航条款转化成需求,落实到产品设计中,明确条款的符合性方法和验证思路,并给出民用飞机冲压空气涡轮系统适航工程技术的工作流程和方法。此套工作流程已通过某型民用飞机冲压空气涡轮系统的研制进行了初步验证,可为国内民用飞机机载系统的研制及取证过程提供参考。     

浅析验证性改装

验证性改装通过对在役飞机进行改装来论证改装设计符合审定基础，是一种符合性方法。本文简要介绍了验证性改装的性质以及与批准改装的区别，以及航空公司对于验证性改装的认识误区和对快速处理偏差的建议。     

基于局部三角变换的OFDM系统

正交频分复用(OFDM)调制技术由于具有良好的抗多径干扰能力和高效的频谱利用率,在许多数字传输系统中被广泛应用,成为当今卫星通信研究的热点。本文提出了基于局部三角变换（LTT）的OFDM系统模型,该系统带外频率谱密度下降快,并能保持相邻的OFDM符号的正交性。给出了用离散余弦变换（DCT）实现的快速算法及复杂度,并考查了最优基的选取。仿真和分析结果表明：该系统误码率比基于快速傅里叶变换（FFT）的系统更小,能更好地适应高速传输带来的大多普勒频移,更有效地利用带宽,为接收端对高速数据的解调提供很好的保证。     

Numerical analysis and optimization of boundary layer suction on airfoils

Numerical approach of hybrid laminar flow control(HLFC) is investigated for the suction hole with a width between 0.5 mm and 7 mm. The accuracy of Menter and Langtry’s transition model applied for simulating the flow with boundary layer suction is validated. The experiment data are compared with the computational results. The solutions show that this transition model can predict the transition position with suction control accurately. A well designed laminar airfoil is selected in the present research. For suction control with a single hole, the physical mechanism of suction control, including the impact of suction coefficient and the width and position of the suction hole on control results, is analyzed. The single hole simulation results indicate that it is favorable for transition delay and drag reduction to increase the suction coefficient and set the hole position closer to the trailing edge properly. The modified radial basis function(RBF) neural network and the modified differential evolution algorithm are used to optimize the design for suction control with three holes. The design variables are suction coefficient, hole width, hole position and hole spacing. The optimization target is to obtain the minimum drag coefficient. After optimization,the transition delay can be up to 17% and the aerodynamic drag coefficient can decrease by 12.1%.     

Practical compensation for nonlinear dynamic thrust measurement system

The real dynamic thrust measurement system usually tends to be nonlinear due to the complex characteristics of the rig, pipes connection, etc. For a real dynamic measuring system,the nonlinearity must be eliminated by some adequate methods. In this paper, a nonlinear model of dynamic thrust measurement system is established by using radial basis function neural network(RBF-NN), where a novel multi-step force generator is designed to stimulate the nonlinearity of the system, and a practical compensation method for the measurement system using left inverse model is proposed. Left inverse model can be considered as a perfect dynamic compensation of the dynamic thrust measurement system, and in practice, it can be approximated by RBF-NN based on least mean square(LMS) algorithms. Different weights are set for producing the multi-step force, which is the ideal input signal of the nonlinear dynamic thrust measurement system. The validity of the compensation method depends on the engine’s performance and the tolerance error0.5%, which is commonly demanded in engineering. Results from simulations and experiments show that the practical compensation using left inverse model based on RBF-NN in dynamic thrust measuring system can yield high tracking accuracy than the conventional methods.     

基于径向基函数与混合背景网格的动态网格变形方法

发展了一种基于径向基函数(RBF)插值和混合背景网格映射的动态网格变形方法。混合背景网格由运动物面附近的各向异性网格和偏离运动物面的各向同性网格组成。物面变形或运动后,包含在各向异性背景网格中的所有物面网格点的位移由指定的物面运动规律得到,而各向同性背景网格点的位移通过径向基函数插值获得。然后变形后的计算网格利用计算网格与混合背景网格之间固定的映射关系代数插值得到。各向同性网格距离物面一定的距离,消除了物面保形对径向基函数插值的要求,从而可以减少径向基函数基点的数量,以提高插值的效率和可靠性。最后,通过二维和三维算例对该方法的变形网格质量、参数影响、网格拓扑依赖性、复杂外形变形能力及网格变形效率进行了测试。测试结果表明,该方法能够高效生成大变形下高质量的变形网格。     

基于RBF带学习能力高精度非线性FDD设计

在轨航天器故障检测与诊断问题需要面对模型的非线性,而且要求尽量提高其检测的精度,为此设计了基于径向基函数（RBF）神经网络的动量轮非线性故障检测与诊断（FDD）方案。首先应用RBF补偿建模误差,提高检测精度,并选择李雅普诺夫函数证明其收敛性;然后应用非线性观测器来产生故障残差,给出了阈值以及故障检测的时间;应用RBF网络对故障信号进行重构,并据此设计了带学习能力的FDD策略。再次建立了详细的动量轮模型,通过不同条件下的仿真研究分别验证残差的阈值特性、时间特性以及RBF的重构能力,仿真结果表明了算法的有效性。