直接斜率波前复原算法的控制效果分析

建立自适应光学系统功率谱抑制函数的概念，分析了采用直接斜率波前复原算法的自适应当光学系统的控制效果，理论分析与６１单元自适应光学系统上的实验结果表明，直接斜率波前复原算法将导致控制效果下降。     

稀布阵综合脉冲孔径雷达旁瓣对消性能分析

定量分析了阵列孔径、干扰信号带宽、通道幅相误差以及Ａ／Ｄ变换器的量化噪声对大型稀布圆形阵列天线干扰对消效果的影响，介绍了稀布阵综合脉冲孔径雷达（ＳＩＡＲ）采用抽头延迟线以提高干扰对消性能的方法，并给出了数值计算与计算机模拟结果。     

智能同步广播激励器及其标频

使用智能同步广播激励器,并采用CCTV传输的1MHz标频信号,就有可能实现自适应相位跟踪同步广播。这将大大节省中波段的频率资源。     

Robust adaptive control of robotic manipulators without the regressor matrix

A new adaptive controller is presented here for rigid-body robotic manipulators. It is stable and robust with respect to a class of external disturbances. The robustness of the adaptive controller is established without the ‘slow-varying’ assumption and the computationally demanding regressor matrix. The control law consists of a non-adaptive PD control part and an adaptive control part. It uses two adaptive matrices to compensate two uniformly bounded coefficient matrices derived from the original dynamics. A α σ|q?|-modified adaptive law is designed to adjust the adaptive matrices. A Lyapunov-type stability analysis indicates that the closed-loop system is uniformly ultimately bounded. The tracking error and compensation error will eventually converge into a closed region, which can be made arbitrarily small by adjusting the controller parameters. Simulation results are included to demonstrate the performance of the proposed controller.     

Mesh Simplification Based on Super-Face and Genetic Algorithm in Reverse Engineering

Mesh simplification is one of the most important links in the context of reverse engineering. It is also an important consideration in computer graphics. This paper presents a novel and original method of triangular mesh reduction. A new concept of super-face is defined. In order to construct a super-face, a way to calculate the scattered point curvature is discussed. The growth of a seed point and the combination of different regions are also necessary for the construction of a super-face. When the hole left by the deletion of super-face is retriangulated a genetic algorithm is used that has been modified for our specific problem. Then the different weights to balance the optimisation of the new triangular mesh can be adjusted.     

强噪声背景下确定性谐波信号的模糊滤波

文章提出了一种在强背景噪声环境下对被淹没的谐波信号进行模糊滤波，从而恢复微弱目标信号的方法。在MATLAB环境下，先利用相干平均法，除去被测信号中的随机白噪声，对于有色噪声运用自适应神经模糊推理系统（ANFIS）的方法，对被测信号进行模糊滤波，在较低信噪比下，能较好的恢复出原始微弱信号。     

Robot control and parameter estimation with only joint position measurements

Most adaptive control schemes for rigid robots assume velocities measurements to be available. Although it is possible to measure velocities by using tachometers, this increases costs and the signals delivered may be contaminated with noise. Since the use of encoders allows to read joint position pretty accurately, it is desirable to estimate joint velocities through an observer. This paper presents an adaptive scheme designed in conjunction with a linear observer. Boundedness of the estimated parameters and uniform ultimate boundedness for the tracking and observation errors are guaranteed. Experimental results are included to support the developed theory.     

Steady-state weights solution to affine projection algorithm

A new expression of the weights update equation for the affine projection algorithm (APA) is proposed that improves the convergence rate of an adaptive filter,particularly for highly colored input sign...     

Adaptive control of permanent magnet synchronous machines with disturbance estimation

In this paper,an adaptive control scheme is introduced for permanent magnet synchronous machines (PMSMs)as an alternative to classical control techniques.The adaptive control strategy capitalizes on the machine’s inverse dynamics to achieve accurate tracking by using an observer to approximate disturbance in the form of friction and load torque.The controller’s output is then fed to a space vector pulse width modulation(SVPWM)algorithm to produce duty cycles for the inverter.The control scheme is validated through a set of simulations on an experimentally validated PMSM model.Results for different situations highlight its high speed tracking accuracy and high performance in compensating for friction and load disturbances of various magnitudes.     

Environmental Perception with Spatial Regularization Correlation Filter for Visual Tracking

With the introduction of correlation filtering (CF), the performance of visual object tracking is significantly improved. Circular shifts collecting samples is a key component of the CF tracker, and it also causes negative boundary effects. Most trackers add spatial regularization to alleviate boundary effects well. However, these trackers ignore the effect of environmental changes on tracking performance, and the filter discriminates poorly in the background interference. Here, to break these limitations, we propose a new correlation filter model, namely Environmental Perception with Spatial Regularization Correlation Filter for Visual Tracking. Specifically, we use the Average Peak to Correlation Energy (APCE) and the response value error between the two frames together to perceive environmental changes, which adjusts the learning rate to make the template more adaptable to environmental changes. To enhance the discriminatory capability of the filter, we use real background information as negative samples to train the filter model. In addition, the introduction of the regular term destroys the closed solution of CF, and this problem can be effectively solved by the use of the alternating direction method of multipliers (ADMM). Extensive experimental evaluations on three large tracking benchmarks are performed, which demonstrate the good performance of the proposed method over some of the state-of-the-art trackers.