Robust state estimation for uncertain linear systems with deterministic input signals

In this paper, we investigate state estimations of a dynamical system in which not only process and measurement noise, but also parameter uncertainties and deterministic input signals are involved. The sensitivity penalization based robust state estimation is extended to uncertain linear systems with deterministic input signals and parametric uncertainties which may nonlinearly affect a state-space plant model. The form of the derived robust estimator is similar to that of the well-known Kalman filter with a comparable computational complexity. Under a few weak assumptions, it is proved that though the derived state estimator is biased, the bound of estimation errors is finite and the covariance matrix of estimation errors is bounded. Numerical simulations show that the obtained robust filter has relatively nice estimation performances.     

一种新的InSAR基线估计方法

针对InSAR技术中基线估计误差对DEM精度的影响,从传统的基线估计方法入手,提出了一种新的估计基线参数的方法,并用仿真实验做了论证.结果表明,该方法比以往传统的方法得到的基线参数的精度更高,运算速度更快,应用范围更加广泛.     

一种自适应视频图像超分辨率重构算法*

依据图像局部二阶统计量能够反映图像区域变化的特性,以参考帧的局部方差为参数建立凸集投影算子和区域修复阈值的条件,提出了一种自适应选取运动估计误差阈值和图像修复误差阈值的视频图像超分辨率重构方法.实验结果表明,与传统方法相比,该算法重构图像的主观质量得到了明显增强,提高了峰值信噪比.     

Fault diagnosis based on high-gain observer with an update law for a class of nonlinear systems

In this paper, by using the well-known high-gain observer design, an update law for the gain and an adaptive estimation of parameters, a new method of fault diagnosis for a class of nonlinear systems is presented. Without resort to any transformation for the parameters, the estimation errors of the states and the parameters are guaranteed to be globally exponentially convergent by a persistent excitation condition. Compared to the existing results, it can be applied to nonlinear systems with nonlinear terms admitting an incremental rate depending on the measured output. A case study further verifies the validity of the proposed research.     

A practical robust nonlinear controller for maglev levitation system

In order to explore the precise dynamic response of the maglev train and verify the validity of proposed controller, a maglev guideway-electromagnet-air spring-cabin coupled model is developed in the first step. Based on the coupled model, the stresses of the modules are analyzed, and it is pointed out that the inherent nonlinearity, the inner coupling, misalignments between the sensors and actuators, and external disturbances are the main issues that should be considered for the maglev engineering. Furthermore, a feedback linearization controller based on the mathematical model of a maglev module is derived, in which the nonlinearity, coupling and misalignments are taken into account. Then, to attenuate the effect of external disturbances, a disturbance observer is proposed and the dynamics of the estimation error is analyzed using the input-to-state stability theory. It shows that the error is negligible under a low-frequency disturbance. However, at the high-frequency range, the error is unacceptable and the disturbances can not be compensated in time, which lead to over designed fluctuations of levitation gap, even a clash between the upper surface of electromagnet and lower surface of guideway. To solve this problem, a novel nonlinear acceleration feedback is put forward to enhancing the attenuation ability of fast varying disturbances. Finally, numerical comparisons show that the proposed controller outperforms the traditional feedback linearization controller and maintains good robustness under disturbances.     

双选择瑞利信道MIMO-OFDM存在信道估计误差分析

双选择性(时域多变性和频域选择性)瑞利信道多入多出-正交频分复用(MIMO-OFDM)系统中,信道估计误差客观存在.为了研究双选择性瑞利信道中信道估计误差对MIMO-OFDM系统的影响,使用迫零检测和对Wishart分布的近似处理,从理论上推导出了存在信道估计误差时双选择不相关瑞利信道和双选择指数相关瑞利信道中MIMO-OFDM系统信干噪比(SINR)的概率分布.根据系统SINR概率分布,推导出了存在信道估计误差时系统的平均差错率和中断概率.仿真结果表明了理论分析的正确性.     

使用遗传算法的自适应Kalman滤波器

基于Magill的Kalman撼波器池结构，设计了使用遗传算法的自适应Kalman滤波器，给出了离线和在线两种实现方案．离线方案以辨识滤波参数为主要目的，进而可以对状态进行较准确的事后估计；在线方案以实时地对状态进行估计为目的．对滤波参数寻优使用具有良好性能的浮点数编码遗传算法，该算法与二进制编码遗传算法相比收敛速度更快、搜索全局最优的能力更强．仿真结果验证了所提出的自适应Kalman滤波器的有效性．     

全双工大规模MIMO网络中最优天线分配

在全双工大规模MIMO网络中,为了降低自干扰,提升频谱效率,提出了一种最优天线分配算法。该算法在基站采用迫零线性信号处理和存在信道估计误差的前提下,首先推导出系统和速率的紧下界。通过分析该下界,以系统和速率最大化为优化目标,得到最优的收发天线比。理论分析和仿真结果表明:1）收发天线比与上行导频信号发射功率成正比,与下行导频信号发射功率成反比;2）当天线数目无穷大时,最优天线比趋近于1。     

和式的Stolz估计法

本文应用Ｓｔｏｌｚ定理，给出了和式的一种估计方法，作为例子，对（Ｐ＞０）的估计进行了较为细致的讨论．