自适应机翼翼型变形的研究现状及关键技术

自适应机翼具有巨大的应用潜力,是未来飞机设计的必然趋势,已经得到了广泛的关注。分别从自适应变弯度前缘、自适应变弯度后缘以及变厚度机翼三个方面阐述了其变形原理,并对使用的蒙皮、驱动方式、研究方法等进行了归纳总结,指出了未来的发展趋势,提出了自适应机翼亟需解决的关键技术,包括兼具大变形和高承载功能的柔性蒙皮的设计、自适应驱动系统设计、协同控制系统的设计、分布式传感器网络,可为自适应机翼结构的设计与实现途径提供一定的技术参考。     

三维Euler方程非结构自适应网格投影和光顺技术研究

研究了三维Euler方程非结构自适应网格的投影和光顺技术.以ONERA M6机翼为计算模型,非结构网格为计算网格,守恒变量的范数为自适应加密准则,对采用一般自适应计算策略得到的网格和数值结果进行了分析,并发展了一种考虑网格投影和光顺的自适应计算策略.数值试验结果表明:通过对自适应所生成网格的投影与光顺,实现了自适应计算过程中的几何保真性,获得了相对光滑的压力分布曲线.     

航空发动机非理想解耦自适应控制

本文对航空发动机的双变量控制方法进行了研究, 提出了一种非理想解耦自适应控制方法, 各子系统之间部分残余的相互耦合和非线性影响就通过自适应律本身的鲁棒性来解决。仿真结果表明该控制系统实现了解耦控制, 对发动机模型参数在大范围内的变化均有良好的控制效果。      

Deployable space structure control using adaptive predictive controller with notch filter

The present study addresses the adaptive predictive controller with adaptive notch filter for the tip position control of a deployable space structure model. An adaptive notch filter is designed to estimate multiple bending mode frequencies of the deployable manipulator and to minimize the effect of bending vibration. The results show that the adaptive predictive controller with adaptive notch filter is quite effective controlling the tip position of a deployable space structure under poor modeling information.     

永磁同步电机的自适应云模型控制研究

针对PID或其改进的算法鲁棒性偏低问题,提出了永磁同步电机(PMSM)的自适应云模型控制算法研究。在分析了自适应云模型结构后设计了PMSM自适应云模型控制器。搭建了基于自适应云模型控制算法的PMSM试验平台,试验结果表明提出的PMSM的自适应云模型控制算法精度高、性能稳定。     

基于多模型切换的鲁棒自适应控制器

系统参数发生跳变时,为了解决多变量系统暂态响应变差的问题,提出一种基于多模型切换的鲁棒自适应控制器。该控制器由多个鲁棒自适应控制器组成,鲁棒自适应控制器保证系统存在未建模动态时能够使自适应系统稳定运行,引入的多模型策略保证系统参数跳变时具有良好的暂态性能。仿真结果表明,所提出的多模型鲁棒自适应控制器能够加快系统的响应速度,提高系统的暂态性能。     

铣削过程在线辨识与极点配置自适应控制

 研究了铣削加工过程的建模、参数在线辨识及自适应控制问题,为铣削过程建立了二阶离散传递函数模型,提出了一种修正的带遗忘因子递推最小二乘参数辨识算法,从而解决了普通递推最小二乘辨识算法中由于递推计算协方差矩阵衰退或膨胀引起辨识结果失真的问题,采用极点配置设计原理,为铣削过程推导了自适应控制的控制律。仿真和实验表明,修正的最小二乘辨识算法和极点配置自适应控制律是正确和可靠的,自适应控制器可获得所需的响应性能。     

基于自适应代理模型的气动优化方法

气动优化设计中,为了减少优化系统的计算周期,提高搜索效率,引入结构简单、计算量较小的代理模型,而运用有效的插值和选样方法(自适应选样)可以大大减少建立代理模型的时间。因此本文提出了一种基于自适应代理模型的气动优化方法。首先对自适应代理模型进行研究,建立了 Kriging 自适应代理模型和支持向量回归自适应代理模型,这两种自适应代理模型在相同样本点情况下比一般代理模型拥有更高的预测能力,然后将这其应用到翼型优化设计中,取得了良好的优化效果,从而表明这两种自适应代理模型不仅简单实用,而且明显提高了气动分析的计算效率。     

交互作用的双自适应模型估计器

 通过对目标的不确定机动分析和对不确定机动的模式分类(非机动、临界机动、弱机动、强机动),建立了一种新的目标状态自适应估计器——交互作用的双自适应模型估计器。它通过具有机动识别特性的二阶自适应模型和具有机动水平特性的三阶自适应模型,以及它们之间交互作用自适应组合方式的结合,达到了跟踪估计目标各种运动的“全面”自适应能力。应用新估计器对目标的5种基本运动进行了Monto-carlo仿真。仿真表明,它具有所期望的良好性能。     

A Unified Approach to Model-Reference Adaptive Systems Part I: Theory

A unified approach to model-reference adaptive control systems is presented. A linearized error equation for each adaptive system is derived about some operating point and converted into the standard form for plotting root loci. The contribution made here is to convert the selection of an adaptive technique and the choosing of adaptive coefficients for some desired system performance from a "mystical art" to standard control techniquess.     

采用FPGA实现基于LMS算法的自适应均衡器的设计研究

近年来,自适应均衡技术在无线通信系统中的应用日益广泛,利用自适应均衡技术在多径环境中可以有效地提高数字接收机的性能。本文阐述了在用MATLAB软件仿真的基础上使用FPGA芯片设计自适应均衡器的一种方法;简要介绍了此设计中采用的各个主要功能模块,后者应用到相应的硬件平台上,取得了一定的设计效果。     

Design and Application of an Adaptive Tracking Filter Control System

The design of an adaptive tracking filter control system and its application to large flexible booster vehicles is described. The problem of elastic vehicle stability is considered along with its solution by conventional and adaptive techniques. The improvement in vehicle stability, which may be achieved with the adaptive tracking filter technique as compared to conventional techniques, is shown. The control system evolved uses two adaptive tracking filters to phase stabilize the first and second bending modes, in addition to conventional compensation techniques. The application of this adaptive technique to a vehicle in which the modal frequencies are in close proximity (<2.5 percent separation) is discussed. The mechanization of the adaptive control system involves the selection of design techniques and components that are electrically and physically compatible with the intended airborne application. The development of a suitable frequency tracking technique and tracking filter is described, in addition to the electronic and mechanical design of the adaptive control system prototype.     

自适应控制在飞机控制中的应用

 1979年,在自适应控制的应用研讨会上,Stein~[1],Kreisselmeier~[2]和Rynaski~[3]等分别发表了有关自适应控制在飞机控制中应用的文章。本文将通过对这些论文的综述,对自适应飞机控制的应用现状,所面临的问题,可能的应用方向和前景,建立一个较明确的认识。     

研发阶段涡扇发动机模型自适应方法

为了实现研发阶段涡扇发动机整机试验数据的快速评估和模型自适应,提出一种发动机模型自适应方法。该方法以整机试验数据为输入,结合气动热力过程约束方程和发动机整机匹配约束条件,重构出各部件的性能参数。文中提出了按照高压涡轮导向器喉部流通能力确定核心机流量的方法,并以载荷系数为媒介实现叶轮机械部件参数修正计算,完成了小涵道比涡扇发动机的自适应建模计算。计算结果表明,17个测量参数与计算结果完全一致,该方法完成单个状态点自适应计算的平均时间约为1.44ms,主要部件特性的修正系数在0.95～1.05。采用该方法计算的部件特性参数自适应修正系数可为发动机性能调试和故障诊断提供依据。     

一种改进的自适应故障诊断设计方法及其在飞控系统中的应用

基于自适应故障诊断观测器提出一种新的自适应故障估计设计方法。针对传统自适应故障估计设计方法难以满足故障估计性能的要求以及存在严格的等式约束增加了观测器设计的难度等问题,提出新的自适应故障估计设计方法,该方法不仅能够显著地提升故障估计的性能,而且通过运用不等式变化有效地避免了严格的等式约束,基于Lyapunov稳定性理论以矩阵不等式的形式给出了误差动态系统稳定的新的充分条件。最后,对某型飞控系统的仿真实验验证了所提方法的有效性。     

Robust adaptive filtering method for SINS/SAR integrated navigation system

This paper presents a new robust adaptive filtering method for SINS/SAR (Strap-down Inertial Navigation System/Synthetic Aperture Radar) integrated navigation system. This method adopts the principle of robust estimation to adaptive filtering of observational data. A robust adaptive filter is developed to adaptively determine the covariance matrix of observation noise, and adaptively adjust the covariance matrix of system state noise according to the adaptive factor constructed based on predicted residuals. Experimental results and comparison analysis demonstrate that the proposed method cannot only effectively resist disturbances due to system state noise and observation noise, but it can also achieve higher accuracy than the adaptive Kalman filtering method.     

Partially Adaptive STAP using the FRACTA Algorithm

A partially adaptive space-time adaptive processor (STAP) utilizing the recently developed FRACTA algorithm is presented which significantly reduces the high computational complexity and large sample support requirements of fully adaptive STAP. Multi-window post-Doppler dimensionality reduction techniques are employed to transform the data prior to application of the FRACTA algorithm. The FRACTA algorithm is a reiterative censoring (RC) and detection algorithm which has been shown to provide excellent detection performance in nonhomogeneous interference environments. Two multi-window post-Doppler dimensionality reduction techniques are considered: PRI-staggered and adjacent-bin. The partially adaptive FRACTA algorithm is applied to the KASSPER I (Knowledge-Aided Sensor Signal Processing & Expert Reasoning) challenge datacube. The pulse repetition interval (PRI)-staggered approach with D=6 filters per Doppler bin is found to provide the best detection performance, outperforming the fully adaptive case while simultaneously reducing the runtime by a factor of ten. Using this implementation, partially adaptive FRACTA detects 197 out of 268 targets with one false alarm. The clairvoyant processor (the covariance matrix for each range cell is known) detects 198 targets with one false alarm. In addition, the partially adaptive FRACTA algorithm is shown to be resilient to jamming, and performs well for reduced sample support situations. When compared with partially adaptive STAP using traditional sliding window processing (SWP), the runtime of partially adaptive FRACTA is 14 times faster, and the detection performance is significantly increased (SWP detects 46 out of 268 targets with one false alarm).     

Dynamic Effects of Signal Normalizing on Adaptive Algorithms

A method is shown for suppressing the adaptive switching transient that arises in complex adaptive (LMS and stochastic approximation) algorithms due to signal normalization with controlled switched gains. The method involves rescaling of the adaptive weights with the normalizing gains just prior to the first adaptation with the new gains. In addition, an effective method of rescaling the adaptive gain factor based on the maximum eigenvalues of the respective covariance matrices is shown.     

Adaptive control based on a parametric affine model for tail-controlled missiles

An adaptive control against uncertainties in tail-controlled STT (skid-to-turn) missiles is presented. First, we derive an analytic uncertainty model from a parametric affine missile model developed by the authors. Based on this analytic model, an adaptive feedback linearizing control law accompanied by a sliding mode control law is proposed. We provide analyses of stability and output tracking performance of the overall adaptive missile system. The performance and validity of the proposed adaptive control scheme are demonstrated by simulation.     

一种新的变结构自适应控制方法及其应用研究

本文提出一种新的变结构自适应控制方法,并将其应用于航空发动机控制。这种方法只利用系统输入输出信号,与传统的自适应控制方法相比,具有收敛特性好,对对象的参数变化及未建模动态有很好的鲁棒性,同时其算法简单,易于实现。仿真表明该方法适用于航空发动机控制。