未知时延系统的全局优化辅助变量辨识

对于未知时延系统,借助分离性原理,推导出迭代的可分离的非线性最小二乘（SNLS）辨识方法。为了降低收敛于局部最小的可能性,消除强观测噪声所引起的参数估计的偏差,利用全局优化理论,引进辅助变量,推导了全局优化的辅助变量（GOIV）辨识方法。仿真试验验证了算法的有效性。     

一类非线性系统的神经网络自适应控制

针对一类单输入单输出不确定非仿射型非线性系统,基于多层神经网络提出了一种直接自适应控制方法。该设计方法首先应用多层神经网络自适应模拟逼近逆解中的未知部分,然后应用逆设计和自适应反演设计出虚拟控制量,最后应用反馈线性化设计方法和神经网络设计了直接自适应控制律。并利用Lyapunov稳定性定理推导了神经网络的参数调节律,保证了闭环系统的所有信号均最终一致有界。     

超机动飞行的非线性反推自适应控制

为解决对象参数未知时的超机动飞行控制问题,设计了一种非线性反推自适应控制器。针对超机动飞行的非线性模型,适当选取Lyapunov函数和中间虚拟控制信号,同时通过自适应控制律的设计来调节未知参数并得到了最终的控制信号。仿真结果表明,即使模型参数未知,所设计的控制律也能在过失速机动条件下控制飞机跟踪指令飞行,同时保证了闭环系统的稳定性。     

基于预设性能的四旋翼无人机编队安全控制

针对四旋翼无人机编队系统存在模型不确定性、未知外部干扰与内部碰撞等问题,提出一种基于预设性能的安全控制方法。首先使用预设性能函数结合误差转换方法,将防止内部碰撞的不等式约束问题转换为无约束问题。同时针对模型中的不确定项,使用神经网络进行逼近;针对神经网络逼近误差与未知外部干扰组成的复合干扰,使用非线性干扰观测器进行估计,并分别设计位置与姿态子系统控制器,避免了编队内四旋翼无人机的碰撞。然后借助Lyapunov方法证明了闭环系统所有信号的收敛性。最后通过数值仿真验证了所提控制方法的有效性。     

采用工作模态识别法进行模态分析

对于一些大型工作结构 ,有时很难测得输入信号 ,只能单独利用实测响应数据进行工作模态识别。本文针对工程实际中的这一情况 ,首先利用响应间互相关函数同脉冲响应函数在表达形式上的相似性 ,推导出了多参考点时域工作模态复指数法 ,继而又从响应间的互相关函数入手 ,推导出了多参考点频域工作模态识别法。最后采用一飞机模型对这两种方法进行了试验验证 ,并将所得结果做了对比分析 ,结果表明 ,两种多参考点方法都能较有效地单独从实测响应数据提取结构的模态参数 ,且频域工作模态识别法比时域工作模态复指数法识别精度更高。     

Nonlinear robust observer design for strapdown INS in-flight alignment

A nonlinear observer is proposed for a strapdown inertial navigation system (SDINS) in-flight alignment problem using an H/sub /spl infin// filter Riccati equation and a freedom parameter. The proposed observer improves the filtering stability, convergence, and performance. The characteristics of the observer are analyzed using a Lyapunov function. Simulation results demonstrate a significant reduction in alignment errors by employing the proposed nonlinear observer. The observer is developed in general such that it can be applied to estimating nonlinear systems other than the SDINS in-flight alignment.     

Simultaneous state and actuator fault estimation for satellite attitude control systems

In this paper, a new nonlinear augmented observer is proposed and applied to satellite attitude control systems. The observer can estimate system state and actuator fault simultaneously. It can enhance the performances of rapidly-varying faults estimation. Only original system matrices are adopted in the parameter design. The considered faults can be unbounded, and the proposed augmented observer can estimate a large class of faults. Systems without disturbances and the fault whose finite times derivatives are zero piecewise are initially considered, followed by a discussion of a general situation where the system is subject to disturbances and the finite times derivatives of the faults are not null but bounded. For the considered nonlinear system, convergence conditions of the observer are provided and the stability analysis is performed using Lyapunov direct method. Then a feasible algorithm is explored to compute the observer parameters using linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed approach is illustrated by considering an example of a closed-loop satellite attitude control system. The simulation results show satisfactory perfor-mance in estimating states and actuator faults. It also shows that multiple faults can be estimated successfully.     

超低空空投航迹倾角自适应跟踪控制

针对超低空空投下滑阶段考虑执行器输入死区、不确定性大气扰动以及模型存在未知非线性等因素干扰轨迹精确跟踪等问题,提出了一种自适应神经网络动态面跟踪控制方法.建立了含执行器输入死区的超低空空投载机纵向非线性模型,采用神经网络逼近模型中未知非线性函数,引入非线性鲁棒补偿项消除了执行器死区建模误差和外界扰动.应用Lyapunov稳定性理论证明了闭环系统所有信号均是有界收敛的.仿真验证表明,所提方法既保证了轨迹跟踪的精确性,又具有强鲁棒性.     

基于递推傅里叶变换的飞行器参数在线辨识方法

在线辨识在现代飞行控制系统设计中扮演越来越重要的角色,飞行器模型的在线更新使得人们可以采用更智能的控制方法。基于计算精度和速度的考虑,在线辨识方法通常以递推方式进行,主要分为时域和频域两大类方法。在建立飞行器系统模型结构的基础上,利用频域递推傅里叶变换及最小二乘方法,实现对气动及控制偏导数的在线辨识。针对某飞机纵向通道的在线辨识仿真验证该方法有效,且计算速度和收敛速度快,辨识结果与参数真实值之间的一致性好,方法对传感器噪声有较强的适应性。最后,分析比较了各种典型激励信号对辨识结果的影响,为进行实际在线辨识试验提供了参考依据。     

基于非线性压缩变换的纤维增强复合薄板非线性阻尼的时域测试方法

提出了基于非线性压缩变换的纤维增强复合薄板非线性阻尼的时域测试方法。基于非线性压缩变换构造了理论分析信号,并推导获得了复合结构系统非线性阻尼的表达式,明确了从时域测试角度获取非线性阻尼参数的理论原理。编写了Matlab算法,并用数值算例证明了该算法的正确性。总结并概括出一套合理、规范的测试流程,并对TC500碳纤维/树脂基复合薄板进行了实际测试。实践证明,利用所提出的方法可以有效获得复合薄板在不同衰减时刻对应的阻尼参数,该方法可以用来定量评价不同振动幅值及频率下复合结构的非线性阻尼特性。      

基于未知输入观测器的非线性动态系统故障估计

针对一类受扰非线性动态系统的执行器故障估计问题,提出一种未知输入观测器来实现故障估计。首先,通过坐标变换将原系统转化为合适的形式;其次,采用线性矩阵不等式与Lyapunov泛函分别设计H_∞输出反馈控制器和未知输入观测器,在此基础上实现对系统中执行器故障的渐近估计;最后,通过机械臂系统仿真分析并验证了所提方法的有效性。与已有方法相比,所提方法不要求故障可导,也不要求故障或干扰上界已知,因此易于在工程实际中实现对非线性系统执行器故障的估计。     

Nonlinear Adaptive Slewing Motion Control of Spacecraft Truss Driven by Synchronous V-gimbaled CMG Precession

The slewing motion control of a truss arm driven by a V-gimbaled control-moment-gyro (CMG) is a nonlinear control problem. The V-gimbaled CMG consists of a pair of gyros that must precess synchronously. The moment of inertia of the system, the angular momentum of the gyros and the external disturbances are not exactly known. With the help of feedback linearization and recursive Lyapunov design method, an adaptive nonlinear controller is designed to deal with the unknown items. Performance of the proposed controller is verified by simulation.     

一种时域稳定参数预报与最优估计兼容的参数辨识法

 本文导出一种基于时域稳定的参数预报与最优估计兼容的状态估计和参数辨识算法。这种算法将系统辨识分为三步:1.以辨识系统预报误差渐近稳定为准则的参数预报;2.以预报参数为条件的状态估计;3.对参数和状态的后验修正。即一般分割辨识算法（GPIA）与模型参考辨识算法（MRIA）相结合的兼容辨识算法。本文将这一算法用于飞行器气动系数和控制导数的辨识,并与GPIA算法所得结果相比较。     

对我国以往常用前起落架载荷谱存在问题的探索

 通过对轰六前起落架主、辅减摆器使用载荷谱的实测、疲劳试验实施方法和试验结果的介绍与分析,初步探索了我国以往常用前起落架载荷谱中存在的问题以及疲劳试验结果与前起落架外场实际破坏不符的原因。并对今后编制前起落架载荷谱和确定前起落架疲劳试验加载方法提出了改进意见。     

直升机垂直飞行鲁棒控制系统设计与仿真

应用基于Lyapunov直接法的非线性不确定系统鲁棒控制方法，为某型直升机垂直飞行模态设计了鲁棒控制律，该控制律能保证闭环系统具有全局稳定性。为验证所设计鲁棒控制律的有效性，对直机机垂直飞行的三 机动：设定点悬停、起飞着陆机和忽上忽下机动，分别进行了闭环系统仿真。仿真结果表明，所设计的控制律对系统参数的摄动具有很强的鲁棒性。     

Time-varying transfer function extraction of an unstable launch vehicle via closed-loop identification

The aerospace launch vehicle, developed today by manufacturers, is characterized by high nonlinearity, open loop instability and time-varying behaviors. The transfer functions of the vehicle can be extracted using well-known linearization methodology. This paper presents an alternative to obtain the transfer functions via closed-loop identification using six degrees of freedom nonlinear simulation software. The pitch program is taken into account as the external excitation. Control and stability of the process are performed using robust PID controller. The model structure with some unknown parameters is obtained after mathematical modeling, thus the case of our problem is a parameter identification one. Time-variant parameters are estimated by Kalman filter approach with the aid of ARX model structure.     

Identification of Rotating Assembly Inertial and Bearing Parameters

The problem of estimating the state of a turbopump rotating assembly and identifying unknown products of inertia and unknown bearing parameters is considered. A linearized, extended Kalman filtering approach has been used and found to be successful for both state estimation and parameter identification in an inherently nonlinear problem. The input data was simulated Bently test data which was obtained from a verified 12-dimensional state-space model and was compared with real Bently test data obtained from NASA. The results prove the feasibility of using this model and this type of test data to obtain the hidden parameters of a typical turbopump rotating assembly. This method should lead to improved performance by allowing improved balancing of the rotor and giving improved knowledge of the bearing reactions.     

Estimating the Doppler centroid of SAR data

After reviewing frequency-domain techniques for estimating the Doppler centroid of synthetic-aperture radar (SAR) data, the author describes a time-domain method and highlights its advantages. In particular, a nonlinear time-domain algorithm called the sign-Doppler estimator (SDE) is shown to have attractive properties. An evaluation based on an existing SEASAT processor is reported. The time-domain algorithms are shown to be extremely efficient with respect to requirements on calculations and memory, and hence they are well suited to real-time systems where the Doppler estimation is based on raw SAR data. For offline processors where the Doppler estimation is performed on processed data, which removes the problem of partial coverage of bright targets, the ΔE estimator and the CDE (correlation Doppler estimator) algorithm give similar performance. However, for nonhomogeneous scenes it is found that the nonlinear SDE algorithm, which estimates the Doppler-shift on the basis of data signs alone, gives superior performance     

Non-affine parameter dependent LPV model and LMI based adaptive control for turbofan engines

The precise control of turbofan engines thrust is an important guarantee for an aircraft to obtain good flight performance and a challenge due to complex nonlinear dynamics of engines and time-varying parameters. The main difficulties lie in the following two aspects. Firstly, it is hard to obtain an accurate kinetic model for the turbofan engine. Secondly, some model parameters often change in different flight conditions and states and even fluctuate sharply in some cases. These variable parameters bring huge challenge for the turbofan engine control. To solve the turbofan engine control problem, this paper presents a non-affine parameter-dependent Linear Parameter Varying(LPV) model-based adaptive control approach. In this approach, polynomial-based LPV modeling method is firstly employed to obtain the basis matrices, and then the Radial Basis Function Neural Networks(RBFNN) is introduced for the online estimation of the non-affine model parameters to improve the simulation performance. LPV model-based Linear Matrix Inequality(LMI) control method is applied to derive the control law. A robust control term is introduced to fix the estimation error of the nonlinear time-varying model parameters for better control performance. Finally, the Lyapunov stability analysis is performed to ensure the asymptotical convergence of the closed loop system. The simulation results show that the states of the engine can change smoothly and the thrust of the engine can accurately follow the desired trajectory, indicating that the proposed control approach is effective. The contribution of this work lies in the combination of linear system control and nonlinear system control methods to design an effective controller for the turbofan engine and to provide a new way for turbofan engine control research.