Identification of reduced-order model for an aeroelastic system from flutter test data

Recently, flutter active control using linear parameter varying (LPV) framework has attracted a lot of attention. LPV control synthesis usually generates controllers that are at least of the same order as the aeroelastic models. Therefore, the reduced-order model is required by syn-thesis for avoidance of large computation cost and high-order controller. This paper proposes a new procedure for generation of accurate reduced-order linear time-invariant (LTI) models by using sys-tem identification from flutter testing data. The proposed approach is in two steps. The well-known poly-reference least squares complex frequency (p-LSCF) algorithm is firstly employed for modal parameter identification from frequency response measurement. After parameter identification, the dominant physical modes are determined by clear stabilization diagrams and clustering tech-nique. In the second step, with prior knowledge of physical poles, the improved frequency-domain maximum likelihood (ML) estimator is presented for building accurate reduced-order model. Before ML estimation, an improved subspace identification considering the poles constraint is also proposed for initializing the iterative procedure. Finally, the performance of the proposed procedure is validated by real flight flutter test data.     

基于LMI的鲁棒滤波在无人机飞控系统中的应用

针对无人机在实际飞行过程中存在外界干扰以及传感器量测噪声的问题,应用线性矩阵不等式理论对无人机飞控系统进行了降阶鲁棒滤波器设计.讨论了适用于连续系统的降阶鲁棒滤波算法以及滤波器存在的条件.最后,进行了无人机纵向高度保持阶段的数字仿真,给出迎角与俯仰角速度的仿真曲线,仿真结果验证了该算法的合理性和有效性.     

An optimal reduced-order stochastic observer-estimator

An optimal reduced-order observer-estimator (filter) is developed which can provide a full-dimensional vector of state estimates for systems where the dimension of the measurement vector is smaller than that of the state vector and none of the measurements are noise free. The reduced-order filter consists of two subfilters each of which provides a subset of the optimal estimate. A two-step L-K transformation is employed to minimize the estimate error variance of each subfilter. The optimal reduced-order filter developed is computationally efficient     

用于微小型GNC系统的电气单元集成一体化及信息快速处理技术

微小型导航、制导与控制（MGNC）集成一体化电气单元需要采集和处理的数据量较多,且算法复杂,本文采用流水线与高速串行总线技术,实现了集成一体化电气单元电路的多路、实时、同步采样。并对GNC软件中组合导航算法的Kalman滤波器进行了降维处理,车载导航试验表明该设计方法可有效提高组合导航软件的实时性与智能性,为最终提高GNC软件运行速度和效率创造了条件。     

Reduced-order H/sub /spl infin// and L/sub 2/-L/sub /spl infin// filtering via linear matrix inequalities

Necessary and sufficient conditions are derived for the existence of a solution to the continuous-time and discrete-time reduced-order H/sub /spl infin// and L/sub 2/-L/sub /spl infin// filtering problems. These conditions are expressed in terms of linear matrix inequalities (LMIs) and a coupling nonconvex matrix rank constraint. Convex LMI problems are obtained for the full-order and the zeroth-order filtering. An explicit parametrization of all reduced-order filters that correspond to a feasible solution is derived in terms of a contractive matrix, and iterative algorithms are proposed to solve the reduced-order filtering problems using alternating projections.     

基于μ理论的飞机俯仰姿态控制

针对飞机飞行条件变化引起的模型不确定性问题,基于μ控制理论设计鲁棒的俯仰姿态控制系统.首先,根据干扰抑制原理将俯仰姿态控制系统设计转化为μ综合的一般框架,合理地选择加权函数确定广义被控对象,通过引入虚拟的不确定块将鲁棒性能问题转化为广义系统的鲁棒稳定性问题.然后,利用D-K迭代算法求解得到14阶的μ控制器,基于平衡截断...     

Control of a large space structure using MMAE/MMAC techniques

The application of moving-bank multiple model adaptive estimation and control (MMAE/MMAC) algorithms to an actual spade structure (Space Integrated Controls Experiment (SPICE)) being examined at Phillips Laboratory at Kirtland AFB, NM, is presented. The structure consists of a large platform and a smaller platform connected by three legs in a tripod fashion. Kalman filtering and LQG (linear system, quadratic cost, Gaussian noise) control techniques are utilized as the primary design tools for the components of the MMAE/MMAC. Implementing a bank of filters or controllers increases the robustness of the algorithms when uncertainties exist in the system model, whereas the moving bank is utilized to reduce the computational load. Several reduced-order models are developed from the truth model using modal analysis and modal cost analysis. The MMAE/MMAC design with a substantially reduced-order filter model provides an excellent method to estimate a wide range of parameter variations and to quell oscillations in the structure.     

Digital Control of High Performance Aircraft Using Adaptive Estimation Techniques

Since the early 1960's, a rapid advance in signal processing, including filtering and estimation techniques, has been evident. In contrast, applied feedback control, particularly for aircraft, is currently based on technology available prior to 1960, i. e., primarily either constant gain feedback or at most a standard gain-scheduling. In this paper, an adaptive signal processing algorithm is joined with gain-scheduling to produce an effective scheme for controlling the dynamics of high performance aircraft. A technique is presented for a reduced-order model (the longitudinal dynamics) of a high performance short-takeoff-and-landing (STOL) aircraft. The actual controller views the nonlinear behavior of the aircraft as being equivalent to a randomly switching sequence of linear models taken from a preliminary piecewise-linear fit of the system nonlinearities. The adaptive nature of the estimator is necessary to select the proper sequence of linear models along the flight trajectory. From the analysis of the reduced-order model the nonlinear behavior has been found to be well approximated by assuming an effective switching of the linear models at random times, the durations of which reflect the motion of the aircraft in response to pilot commands.     

Decentralized reduced-order filters

Continuous and discrete methods of designing simple reduced-order local filters within a large-scale network are suggested. The filters are designed to estimate only the local variables of interest and not the entire state vector. The method has the advantage that one need not know the mathematical models of the subsystems generating the interconnection variables. The order of the filter can be small enough so that there is no computational burden associated with the filter. The disadvantage of the method is that performance is lost by using a reduced-order filter instead of a full-order filter. An example that demonstrates one application in the aerospace industry is presented     

基于增量学习的非定常气动力参数化降阶模型

气动降阶模型（ROM）是预测非定常气动力的有效工具,具有高精度和低计算成本的优点,近年来许多研究证实了该方法的有效性。但是关于飞行参数变化时,ROM的鲁棒性还需要进一步提高。为了提高ROM对不同飞行参数下的气动力预测能力,提出了基于最小二乘支持向量回归（LS-SVR）和增量学习算法的参数化降阶模型。LS-SVR是一种具有良好泛化能力的回归方法,基于LS-SVR的增量学习算法的主要贡献是在增加新样本集时,不需要重新学习整个数据集。为说明该方法的有效性,基于两自由度NACA64A010翼型构建参数化非定常气动力降阶模型。为了训练气动力输入和相应输出之间的关系,将马赫数和迎角作为附加的模型输入。仿真结果表明,该降阶模型能够准确描述气动力和气动弹性系统在不同飞行参数下的动态特性。     

基于CFD降阶模型的阵风减缓主动控制研究

飞行器飞行时会受到大气紊流的影响,降低飞行品质。阵风减缓控制是改善飞行器飞行性能的关键技术。现有的阵风响应分析多以离散阵风为研究对象,对更加真实描述大气紊流的连续型阵风时域分析关注较少。采用成形滤波器方法将频域形式给出的大气紊流信号转换为时域信号。在跨声速区域内,利用系统辨识技术,基于计算流体力学(CFD)方法建立阵风激励下的气动载荷状态空间降阶模型(ROM)。为方便控制器设计,借助平衡模态法进行模型的进一步降阶。使用模型预测控制(MPC)算法通过控制操纵面偏转实现阵风减缓主动控制。以AGARD445.6标模作为仿真算例,验证基于ROM设计的阵风减缓控制律的有效性。仿真结果表明,在跨声速飞行状态下,模型预测控制器能够在满足操纵面偏转范围的约束下,对连续阵风激励下的翼根弯矩输出进行有效抑制。     

适用于气动弹性的小波非定常气动力降阶方法

发展非定常气动力模型降阶技术旨在缩减计算耗费并且使得计算流体力学信息能够应用于气动伺服弹性以及设计优化当中。采用小波方法建立基于Volterra级数的非定常气动力降阶模型。在模型识别过程中,激励是光滑连续的且以零阶保持方式进行离散,采样频率选择二的整数幂次。近似的一阶Volterra核基于Haar尺度函数族展开,鉴于Volterra核在系统响应中的衰减特性,可在合适的有限时长截断一阶核。为了获得一阶核的各项展开系数,需要求解由输入/输出数据组成的超定方程,其中涉及到奇异值分解算法。为了验证小波方法的有效性,算例选取了二维的NACA64a010翼型。数值仿真结果表明该方法能够比较准确地预测结构小扰动引起的非定常气动力响应且能描述一定的非线性现象。     

Square root parallel Kalman filtering using reduced-order localfilters

The basic parallel Kalman filtering algorithms derived by H.R. Hashemipour et al. (IEEE Trans. Autom. Control. vol.33, p.88-94, 1988) are summarized and generalized to the case of reduced-order local filters. Measurement-update and time-update equations are provided for four implementations: the conventional covariance filter, the conventional information filter, the square-foot covariance filter, and the square-foot information filter. A special feature of the suggested architecture is the ability to accommodate parallel local filters that have a smaller state dimension than the global filter. The estimates and covariance or information matrices (or their square roots) from these reduced-order filters are collated at a central filter at each step to generate the full-size, globally optimal estimates and their associated error covariance or information matrices (or their square roots). Aspects of computational complexity and the ensuing tradeoff with communication are discussed     

基于时间反转和降阶Keystone的SAR-GMTI快速聚焦方法

对合成孔径雷达（SAR）地面运动目标聚焦技术进行了研究。针对现有运动目标聚焦方法存在的问题,提出了一种基于时间反转和降阶Keystone的SAR地面运动目标检测（SAR-GMTI）快速聚焦方法。首先,根据目标的机动特性建立了3阶距离模型;其次,针对目标多普勒中心模糊引起的多普勒谱分裂现象,结合所提时间反转处理（TRP）和降阶Keystone变换处理估计出运动目标2阶参数。此后,构造2阶相位补偿函数补偿运动目标的2阶距离徙动和多普勒徙动,从而完成运动目标的聚焦。同时,所提方法没有任何参数搜索过程,降低了计算复杂度。最后,仿真实验验证了所提算法的正确性和有效性。     

基于内模控制的多输入多输出高阶振动系统

常规的比例-积分-微分(PID)控制器一般用于单输入单输出系统。对于具有多个输入和多个输出且相互之间具有较强耦合作用的高阶多变量系统,PID控制器的设计常难以实现。针对高阶柔性结构振动控制问题,提出如下PID控制策略：首先在某一频段内对频响函数进行拟合降阶,建立过程模型,然后采用内模控制方法和麦克劳林展开式设计多输入多输出振动系统PID控制器。以4层刚架进行建模仿真计算,结果表明,通过本文方法设计的PID控制器,可以在避免未控模态影响的前提下,使外部干扰得到有效抑制,得到比较理想的控制效果。     

改进型LQR方法在飞机控制律设计中的应用

阐述了线性二次型状态反馈（LQR）理论在飞行控制系统设计中的优势。针对现代飞机飞行控制系统非线性、多回路和强耦合的特点，典型的介绍了纵向飞行控制系统的设计过程。选择反馈信号以及升降舵等变量作为输出量．使传统LQR最优控制中对加权阵Q和R的选择变为对降维的加权阵Q的选择,并通过真实飞行速度进行动态调参，最后，通过仿真验证了该方法的正碜性和实用性。     

Digital Controllers for VTOL Aircraft

Using linear-optimal estimation and control techniques, digitaladaptive daptive control laws have been designed for a tandem-rocopteror heliopter which is equipped for fully automatic flight in terminal area operations. Two distinct discrete-time control laws are designed to interface with velocity-command and attitude-command guidance logic, and each incorporates proportional-integral compensation for nonzero-set-point regulation, as well as reduced-order Kalman filters for sensor blending and noise rejection. Adaptation to flight condition is achieved with a novel gain-scheduling method based on correlation and regression analysis. The linear-optimal design approach is found to be a valuable tool in the development of practical multivariable control laws for vehicles which evidence significant coupling and insufficient natural stability.     

Switched adaptive active disturbance rejection control of variable structure near space vehicles based on adaptive dynamic programming

Based on the switched nonlinear system, a switched adaptive Active Disturbance Rejection Control(ADRC) law is proposed for the Variable Structure Near Space Vehicle(VSNSV) with unknown uncertainties and external disturbances. The reduced-order Extended State Observers(ESOs) are constructed for the attitude angle system and the angular rate system to estimate the total disturbance in real time. With the extended state introduced to counteract the effects of uncertainties and disturbances, a systematic procedure is presented for the synthesis of the switched adaptive ADRC strategy. Rigorous proof shows that the estimation errors of the reduced-order ESOs would converge to a small neighborhood of zero in finite time, and that the output of the closedloop system can track a given signal stably for a class of switching signals with average dwell time via the proposed approach. The variable gain control strategy based on Adaptive Dynamic Programming(ADP) with the actor-critic structure is also designed to improve the dynamic performance of the system. Simulation results verify the effectiveness and advantage of the proposed control scheme.     

合成射流激励器流场PIV实验及模态分析

为了获得合成射流激励器流场细节特性,优化合成射流流动控制系统,对于静止流场中的合成射流激励器,通过位移传感器、热线风速仪和时间分辨粒子图像测速(TR-PIV)系统,对激励器时间响应和特定工况下的流场特性进行研究,并针对TR-PIV得到的流场快照运用本征正交分解(POD)和动力学模态分解(DMD)进行模态分析.通过自定义...     

DESIGNING REDUCED-ORDER CONTROLLERS OF MIXED SENSITIVITY PROBLEM FOR FLIGHT CONTROL SYSTEMS

Based on linear matrix inequalities (LMI), the design method of reduced-order controllers of mixed sensitivity problem is studied for flight control systems. It is shown that there exists a controller with order not greater than the difference between the generalized plant order and the number of independent control variables, if the mixed sensitivity problem is solvable for strict regular flight control plants. The proof is constructive, and an approach to design such a controller can be obtained in terms of a pair of feasible solution to the well-known 3 LMI. Finally, an example of mixed sensitivity problem for a flight control system is given to demonstrate practice of the approach.