基于集成温度传感器的硅微陀螺仪数字化温度补偿研究

提出了一种基于集成温度传感器的硅微陀螺仪数字化温度补偿方法。首先,介绍了集成温度传感器的硅微陀螺仪基本结构原理,分析了硅微陀螺仪动力学方程以及温度变化对硅微陀螺仪谐振频率、品质因数、标度因数和零偏的影响。然后,设计了基于FPGA的硅微陀螺仪数字化补偿电路。最后,经过温度特性实验得到标度因数和零偏随温度变化曲线,建立了温度补偿模型,提出分段温度补偿方法。经过温度补偿后,标度因数和零偏的温度系数分别由316.66×10-6/℃和366.22°/(h·℃)减小为69.67×10-6/℃和115.25°/(h·℃),证明了补偿方法的正确性和可行性。     

物联网技术在科研量化管理平台中的应用及探索

科研管理的现代化及高效化是社会发展的趋势,将物联网技术集成到科研管理平台中,能达到高效、科学、高效的效果。完善当前科研管理系统的功能,使得平台除基本的管理功能外,同时具备量化积分功能及论文共享机制等功能,为考核、评价及后续工作提供参考数据,适应当前形势下的复杂需求。     

一种基于灰色系统理论的控制系统参数辨识算法的仿真研究

灰色预测补偿是一种对灰色系统进行白化的算法,该算法需要的信息少、计算量小。它可以克服常规PID控制存在超调的缺点。根据灰色PID控制算法,对系统不确定部分建立灰色模型,进行灰色预测补偿。通过仿真研究,该算法具有较强的鲁棒性,可以提高控制质量,减小控制系统的误差。     

基于广义预测控制的船舶编队

针对多船舶之间的编队合作问题,对船舶的编队控制进行研究。利用广义预测控制方法在船舶运行中对理想路径曲线进行预测,得出船舶的运动控制策略;通过运用领导-跟随者编队方法,在Cartesian坐标系下建立船舶编队控制模型,基于这种模型建立一系列船舶航迹约束,得到船队跟随者成员的控制策略。同时在船舶运行过程中,加入风浪的扰动,进行模拟仿真,得到船队的运行轨迹。     

Stability analysis and controller synthesis for discrete uncertain singular fuzzy systems with distinct difference matrices in the rules

This paper mainly studies an extended discrete singular fuzzy model incorporating the multiple difference matrices in the rules and discusses its stability and design issues. By embracing additional algebraic constraint, traditional discrete Takagi-Sugeno (T-S) fuzzy model can be extended to a generalised discrete singular Takagi-Sugeno (GDST-S) model with individual difference matrices E_i in the locally singular models, where it can describe a larger class of physical or non-linear systems. Based on the linear matrix inequality (LMI) approach, we focus on deriving some explicit stability and design criteria expressed by the LMIs for the regarded system. Thus, the stability verification and controller synthesis can be performed by the current LMI tools. Finally, some illustrative examples are given to illustrate the effectiveness and validity of the proposed approach.     

3D soft-tissue tracking using spatial-color joint probability distribution and thin-plate spline model

Visual tracking techniques based on stereo endoscope are developed to measure tissue motion in robot-assisted minimally invasive surgery. However, accurate 3D tracking of tissue surfaces remains challenging due to complicated deformation, poor imaging conditions, specular reflections and other dynamic effects during surgery. This study employs a robust and efficient 3D tracking scheme with two independent recursive processes, namely kernel-based inter-frame motion estimation and model-based intra-frame 3D matching. In the first process, target region is represented in joint spatial-color space for robust estimation. By defining a probabilistic similarity measure, a mean-shift-based iterative algorithm is derived for location of the target region in a new image. In the second process, the thin-plate spline model is used to fit the 3D shape of tissue surfaces around the target region. An iterative algorithm based on an efficient second-order minimization technique is derived to compute optimal model parameters. The two processes can be computed in parallel. Their outputs are combined to recover 3D information about the target region. The performance of the proposed method is validated using phantom heart videos and in vivo videos acquired by the daVinci^®${\mathrm{daVinci}}^{\circledR }$ surgical robotic platform and a synthesized data set with known ground truth.     

受端电网区域无功自动控制调控策略研究

要确保受端电压的稳定性,就要保证有足够的无功补偿。静态无功补偿可以有效降低网损,并提供稳定的无功功率。但在电网系统变得越来越复杂的情况下,静态无功补偿已经很难满足需求,这时,动态无功补偿作为一种更为有效的无功补偿方式应运而生了。     

基于单片机的功率因数补偿控制器硬件的研究

为了减小电网中感性负载造成的电量损耗,在分析了现有功率因数补偿控制器的补偿效果后,设计了一种通过单片机控制四组电容器组,自动控制投切进行补偿的功率因数补偿控制器。     

Frequency analysis and compensation of valve stiction in cascade control loops

Valve stiction is often a common problem in control loops and stiction induced oscillation is the main cause of poor performance in control systems. Cascade control is extensively applied in process industry as an effective strategy to restrain disturbances and compensate process nonlinearities. In recent years many studies have been performed on the detection and quantification of valve stiction in single feedback control loops. However, there is a lack in developing a mechanism which can analyze stiction induced oscillation in cascade control loops. This work focuses on the frequency analysis of stiction induced oscillations in cascade control loops and proposes a mechanism of oscillation compensation through outer and inner controller tuning. The effect of oscillation compensation by changing control strategies is also discussed. The theoretical analysis is evaluated through simulation examples and a pilot-scale flow-level cascade control experiment.     

A robust two degree-of-freedom controller for systems with both model and measurement uncertainty

This paper presents a design method for robust two degree-of-freedom (DOF) controllers that optimize the control performance with respect to both model uncertainty and signal measurement uncertainty. In many situations, non-causal feedforward is a welcome control addition when closed loop feedback bandwidth limitations exist due to plant dynamics such as: delays, non-minimum phase zeros, poorly placed zeros and poles (Xie, Alleyne, Greer, and Deneault (2013); Xie (2013), etc. However, feedforward control is sensitive to both model uncertainty and signal measurement uncertainty. The latter is particularly true when the feedforward is responding to pre-measured disturbance signals. The combined sensitivity will deteriorate the feedforward controller performance if care is not taken in design. In this paper a two DOF design is introduced which optimizes the performance based on a given estimate of uncertainties. The controller design uses H_∞ tools to balance the controlled system bandwidth with increased sensitivity to signal measurement uncertainties. A successful case study on an experimental header height control system for a combine harvester is shown as an example of the approach.