一种卡尔曼滤波器的永磁同步电机无速度传感器

针对滑模观测器的永磁同步电机参数误差容易造成估算误差和反电动势中存在高频纹波分量的缺点,使用低通滤波器不能有效消除高频纹波,提出在滑模观测器前端引入卡尔曼滤波器来消除高频纹波,使得永磁同步电机的控制系统具有更好的稳态效果和动态响应。依据设计仿真搭建MATLAB平台,对提出新方法进行验证。试验结果表明增加卡尔曼滤波环节后的滑模观测器不仅鲁棒性强,而且在一定程度上有效抑制了抖振,在系统快速性及稳态性能上都有较好的效果。     

Luenberger观测器在永磁同步电机无传感器控制中的应用研究

在永磁同步电机(PMSM)矢量控制中,根据Luenberger观测器原理,提出了一种基于Luenberger观测器的PMSM转子速度和位置的估算方法,有效解决了PMSM由于机械传感器安装带来的一些弊端。利用MATLAB/Simulink工具搭建控制系统仿真模型并进行仿真验证,仿真结果表明控制系统具有良好的控制性能。最后,在以STM32F103ZET6为控制核心的硬件系统上进行算法的实现,试验结果表明基于Luenberger观测器的PMSM控制系统具有较高的控制精度且稳定性较好。     

基于扩张状态观测器的动态逆过失速机动飞行控制

针对飞机过失速机动飞行控制问题,提出了一种将动态逆与扩张状态观测器相结合进行扰动估计补偿的新思路。根据时标分离原则将飞机状态分为快变量和慢变量,并分别设计了两个回路的动态逆控制器。在快慢回路分别引入扩张状态观测器对系统的不确定部分进行估计补偿,抵消不确定部分对系统动态特性的影响。最后对控制律进行了过失速机动仿真。结果表明,在存在较大参数摄动情况下,设计的控制律能控制飞机跟踪控制指令,表现出良好的稳定性和鲁棒性。     

运动单站干涉仪相位差直接定位方法

针对传统干涉仪测向定位在低信噪比(SNR)下性能降低、多频段系统复杂等缺点,本文直接利用运动单站干涉仪模糊相位差(PD)实现对地面静止辐射源定位.为解决该定位问题,结合干涉仪相位差的几何特性,提出了一种多角度距离参数化高斯和滤波(MB-RP-GMF)定位解算方法,利用相位差误差检测获得多个初始方位角,通过距离参数化得到一组滤波初始值,采用扩展卡尔曼滤波(EKF)进行定位计算.仿真结果表明,该定位方法在低信噪比下优于仅测向(BO)定位,且仅采用一组干涉仪便可对多个频段辐射源进行定位.     

AHP方法在系(部)工作评价中的应用

本文给出了系(部)工作评价的AHP模型，并对模型进行求解，说明了该模型的有效性。     

基于主动失谐优化的叶轮瞬态加减速振动抑制

提出了一种基于主动失谐优化的叶轮瞬态加减速振动抑制方法.首先建立了瞬态加减速激励下的叶轮降阶模型,获得了表征失谐对瞬态振幅影响的失谐放大因子.然后基于降阶模型,采用蒙特卡洛仿真快速计算了一系列瞬态激励下失谐放大因子的概率密度分布,结果表明:失谐放大因子在大多数瞬态激励下受到随机小失谐的影响大于在稳态激励下受到的影响,且...     

Disturbance observer based model predictive control for accurate atmospheric entry of spacecraft

Facing the complex aerodynamic environment of Mars atmosphere, a composite atmospheric entry trajectory tracking strategy is investigated in this paper. External disturbances, initial states uncertainties and aerodynamic parameters uncertainties are the main problems. The composite strategy is designed to solve these problems and improve the accuracy of Mars atmospheric entry. This strategy includes a model predictive control for optimized trajectory tracking performance, as well as a disturbance observer based feedforward compensation for external disturbances and uncertainties attenuation. 500-run Monte Carlo simulations show that the proposed composite control scheme achieves more precise Mars atmospheric entry (3.8?km parachute deployment point distribution error) than the baseline control scheme (8.4?km) and integral control scheme (5.8?km).     

关于“用好的作风选人，选作风好的人”的逻辑梳理

“用好的作风选人，选作风好的人”必须确定相关的概念，必须进行科学的判断，必须进行正确的推理。本文试图从逻辑角度对这一选人用人原则进行梳理。     

Backstepping sliding-mode control of stratospheric airships using disturbance-observer

In the presence of unknown disturbances and model parameter uncertainties, this paper develop a nonlinear backstepping sliding-mode controller (BSMC) for trajectory tracking control of a stratospheric airship using a disturbance-observer (DO). Compared with the conventional sliding mode surface (SMS) constructed by a linear combination of the errors, the new SMS manifold is selected as the last back-step error to improve independence of the adjustment of the controller gains. Furthermore, a nonlinear disturbance-observer is designed to process unknown disturbance inputs and improve the BSMC performances. The closed-loop system of trajectory tracking control plant is proved to be globally asymptotically stable by using Lyapunov theory. By comparing with traditional backstepping control and SMC design, the results obtained demonstrate the capacity of the airship to execute a realistic trajectory tracking mission, even in the presence of unknown disturbances, and aerodynamic coefficient uncertainties.     

Stall flutter prediction based on multi-layer GRU neural network

The modeling of dynamic stall aerodynamics is essential to stall flutter, due to the flow separation in a large-amplitude pitching oscillation process. A newly neural network based Reduced Order Model (ROM) framework for predicting the aerodynamic forces of an airfoil undergoing large-amplitude pitching oscillation at various velocities is presented in this work. First, the dynamic stall aerodynamics is calculated by solving RANS equations and the transitional SST-γ model. Afterwards, the stall flutter bifurcation behavior is calculated by the above CFD solver coupled with structural dynamic equation. The critical flutter speed and limit-cycle oscillation amplitudes are consistent with those obtained by experiments. A newly multi-layer Gated Recurrent Unit (GRU) neural network based ROM is constructed to accelerate the calculation of aerodynamic forces. The training and validation process are carried out upon the unsteady aerodynamic data obtained by the proposed CFD method. The well-trained ROM is then coupled with the structure equation at a specific velocity, the Limit-Cycle Oscillation (LCO) of stall flutter under this flow condition is predicted precisely and more quickly. In order to predict both the critical flutter velocity and LCO amplitudes after bifurcation at different velocities, a new ROM with GRU neural network considering the variation of flow velocities is developed. The stall flutter results predicted by ROM agree well with the CFD ones at different velocities. Finally, a brief sensitivity analysis of two structural parameters of ROM is carried out. It infers the potential of the presented modeling method to depict the nonlinearity of dynamic stall and stall flutter phenomenon.