使用MCU内置序列发生器控制的交流信号采样

针对一款隔离开关控制器交流信号采样的需求,在分析使用MCU内置的采样序列控制器实现多通道交流信号同时采样可行性的基础上,提出了完整的软同步交流信号采样技术的解决方案,设计了交流信号输入调理电路和相应的信号采集软件,使用LM3S9D92内置的ADC系统实现了三相四线交流线路PQIU电气参数的采样,有效提升了控制器产品的性价比。测试结果表明,所设计的交流信号采样部分的精度满足技术规范书的要求。     

一种可调延时超窄脉冲触发序列产生技术

为了实现高频信号在欠采样条件下的波形重构,递进延时超窄触发信号的产生成为顺序等效采样技术用于触发取样系统进行高频信号采样的关键。为此,设计了一种可编程延时触发序列产生及调理电路,在FPGA数字电路的控制下,通过计数器与延时模块产生可调延时触发序列,利用阶跃恢复二极管特性对产生的触发序列进行调理,产生一种延时步进可调、边沿极窄的脉冲信号。通过对该电路进行测试,结果表明,输出脉冲信号步进范围0～-2.4 ns可调,分辨率可达1 ps,且边沿跳变时间可以达到120 ps内,幅度可达到8 V左右。该延迟脉冲和调理电路可应用于通信、雷达等信号探测设备中,对于高频信号的获取与分析具有重要意义。     

配电变压器监控系统中的交流采样算法

交流采样是按一定规律对被测信号的瞬时值进行采样，再用一定的数值算法求得被测量的值。实践证明，采用交流采样方法进行数据采集，通过算法运算后获得的电压、电流、有功功率、功率因数等电力参数有较好的精确度和稳定性。     

交流同步采样在断路器测控装置中的应用

真空断路器遥测装置中最重要的测量参数中最重要的是三相交流电参数,当电网频率波动时,必须采用交流同步采样技术才能保证采样计算精度,同步检测和FFT算法成为其核心技术,文章提出了如何使用硬件同步和软件同步相结合,以提高三相同步交流采样的精度和可靠性。     

基于STM32单片机的微电网模拟系统设计

本系统主要由主控电路和三相逆变电路模块组成。采用DC直流电源供电,STM32单片机输出一个模拟量,控制EG8030输出SPWM波,经三相对称整流桥输出三相交流到三相对称Y型负载。采用电流互感器和电压互感器进行电流、电压采样,反馈到单片机形成闭环控制,采集到的数据可实时液晶显示。逆变器1和逆变器2并联到母线,实现共同向负载输出功率,负载可调整。     

一种改进的i_p-i_q无功电流检测方法研究

为了保证电力系统安全稳定运行,需要对电网无功电流进行补偿,因效果取决于无功电流检测的精确性和实时性,在三相电网电压不对称时,传统ip-iq检测法提取的无功电流存在相位差和延时问题,影响了无功补偿的效果。为提高检测精度,提出一种改进的ip-iq无功电流检测方法。改进方法通过对三相电源电压、电流的检测,并将信号延迟算法与幅值积分器相结合,提取被测电压、电流的正序基波分量,再经过简单的坐标变换即可得到无功电流。既避免了三相电网不对称时相位差的检测,又消除了低通滤波器产生的延时问题。采用MATLAB仿真软件进行了建模仿真。仿真结果表明,改进的ip-iq无功电流检测方法明显提高了检测精度和实时性。     

一种矿用相控开关短路电流过零点预测算法

现有短路电流过零点预测算法存在计算复杂、误差大等问题。针对煤矿供电系统三相短路故障,提出了一种矿用相控开关短路电流过零点预测算法。该算法利用三相短路故障发生后1个基波周期内短路电流采样数据,通过累加和的方法计算短路电流的直流分量,可减小计算量、消除谐波干扰;将采样数据与直流分量相减,得到短路电流的交流分量;利用交流分量周期性的特点,可预测1个基波周期后任意采样时刻的交流分量;将1个基波周期后任意采样时刻的直流分量与交流分量相加,即可重构出任意采样时刻的短路电流,从而预测短路电流过零点。仿真和实验结果验证了该算法的准确性。     

静补型无创食管曲张静脉测压仪的设计

为了克服穿刺测压的弊端,基于无创性测压原理,提出了一种新型无创食管曲张静脉压力测定仪;在气路中采用压力平衡室,在电路中采用DSP芯片作为采样和控制核心,在信号采样通道中使用一系列软硬件抗干扰技术;该系统运行稳定,测压过程中可有效排除心跳、呼吸等外界干扰;实验表明,该仪器能够比较精确地测定食管曲张静脉压,可应用于临床预测曲张静脉的出血。     

交流采样中的一种频率跟踪测量方法

论述了交流采样中的一种频率测量方法，可实时测量供电线路电网频率，通过跟踪电网频率的变化，以确保供电线路工频波动时，交流采样也能正确跟踪信号频率，确定交流采样的时间间隔，从而保证在每个信号周波内能够均匀地采样预定的Ｎ个测量点，保证测量的精度。     

基于FPGA实现的高速等效采集系统

基于FPGA设计一个高速等效采集系统,采样速率高达1 GHz.通过对被测信号的周期进行测量,动态配置锁相环,使采样时钟的周期刚好比被测信号的周期大1ns,从而完成对被测信号的等效采样.系统采用Quartus Ⅱ软件进行系统模块设计,使用NIOS IDE Ⅱ软件完成软件代码的实现.该系统在以Cyclone Ⅲ FPGA芯...     

Stochastic bounded consensus tracking of second-order multi-agent systems with measurement noises based on sampled-data with general sampling delay

This paper investigates the stochastic bounded consensus tracking problems of second-order multi-agent systems, where the control input of an agent can only use the information measured at the sampling instants from its neighbours or the virtual leader with a time-varying reference state, the measurements are corrupted by random noises and the signal sampling process induces the general sampling delay. First, the stochastic bounded consensus tracking protocol based on sampled-data with the general sampling delay is presented by using the delay decomposition technique. Second, the augmented matrix method, the probability limit theory and some other techniques are employed to derive the necessary and sufficient conditions guaranteeing the mean square bounded consensus tracking. The theoretical results show that the convergence of the proposed protocol simultaneously depends on the constant feedback gains, the network topology, the sampled period and the sampling delay, and that the static consensus tracking error depends on not only the above-mentioned factors, but also the noise intensity and the upper bound of the velocity and the acceleration of the virtual leader. The obtained results cover no sampling delay and the small sampling delay as two special cases. Simulations are provided to demonstrate the effectiveness of the theoretical results.     

Stochastic bounded consensus tracking of second-order multi-agent systems with measurement noises based on sampled-data with small sampling delay

This paper is devoted to the stochastic bounded consensus tracking problems of second-order multi-agent systems, where the control input of each agent can only use the information measured at the sampling instants from its neighbors or the virtual leader with a time-varying reference state, the measurements are corrupted by random noises, and the signal sampling process induces the small sampling delay. The augmented matrix method, the probability limit theory and some other techniques are employed to derive the necessary and sufficient conditions guaranteeing the mean square bounded consensus tracking. We show that the convergence of the proposed protocol simultaneously depends on the constant feedback gains, the network topology, the sampled period and the sampling delay, and that the static consensus tracking error depends on not only the above mentioned factors, but also the noise intensity and the upper bound of the velocity and the acceleration of the virtual leader. The obtained results cover no sampling delay as its one special case. Simulations are provided to demonstrate the effectiveness of the theoretical results.     

Evaluate time delay from sensor's data by trend similarity search

Time delay estimation is a general issue in both signal processing and process control fields. Neither offline step impulse response-based methods nor least squares methods in control field estimate time delay directly from the real running data. Although the methods for signal processing directly evaluate the delay from signals, such as correlation calculation, coherence analysis and least mean square methods, they are mainly suitable for two signals only different at a time delay part and an attenuation factor. In this article, an estimation method is proposed which is directly based on the real running input and output data of a control plant. The input and output signals of a plant show raw monotony from each other in many cases. According to this feature, we estimate the delay by comparing the trend of two signals. Furthermore, it is extended to an adaptive method for estimating piecewise time-varying delay by sliding window and forgetting factor. The experiments on real plant show the good performances of our methods. The simulation experiments demonstrate that our basic method performs better than CCF or coherence analysis for the nonlinear plant and the adaptive one performs better than least mean square methods for the signals with transfer function except time delay.     

基于延时互相关的正弦信号频率估计方法

为提高非整周期采样信号的频率估计精度,提出一种基于延时互相关的正弦信号频率估计方法。首先,截取一段采样信号及其等长度延时信号;其次,对2段信号做互相关运算,并构建不包含误差项的误差校正信号;然后,对误差校正信号进行频率粗估计,并生成参考信号;最后,根据柯西-施瓦兹不等式构造误差函数,通过最小化误差函数得到频率精估计值。仿真实验结果表明：该方法能有效降低非整周期采样的影响,提高频率估计精度,其估计精度优于同等条件下基于自相关的频率估计方法,使得频率估计值的均方误差更接近克拉美罗下限。     

Modelling and control of Zigbee-based wireless networked control system with both network-induced delay and packet dropout

A new stochastic switched linear model is established to describe the Zigbee-based wireless networked control system (WNCS) with both network-induced delay and packet dropout. The network-induced delay can be less or longer than one sampling period. A sufficient condition is presented for the exponentially mean square stability of the closed-loop WNCS, and corresponding state feedback controller is designed by using the augmenting technique and multi-Lyapunov approach. Then, combined with carrier sense multiple access with collision avoidance (CSMA-CA) algorithm, a method is given to choose proper parameter values. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method.     

基于FBD法的STATCOM的研究

针对三相四线制配电网的无功、谐波检测的实时性和零线电流抑制问题,采用了双DSP控制的三相四桥臂statcom解决方案。系统的无功和谐波检测方式采用了FBD法,可减轻DSP计算量;系统的控制方式采用了双DSP控制,一片DSP主要负责信号数据采集,另一片DSP主要负责指令电流的运算,可以大大提高系统的运行速度,保证了statcom补偿的实时性。本文介绍了三相四桥臂statcom的检测和控制方式,并对系统的硬件构成和软件主程序流程作了阐述。仿真和实验结果验证了此方法的可行性。     

基于单片机的纸张计数显示装置设计

本系统是由 A T 89C 51单片机作为核心控制,采用自制电容式传感器和单片机计数电路、显示电路组成。 直流稳压电源为单片机提供 5V 工作电压,将纸张放在电容式传感器两个极板之间,使电容传感器的介电常数发生变 化,检测电路通过两条屏蔽线与电容传感器两极板连接,采集到变化的脉冲信号,经过振荡电路产生具有稳定周期的方 波信号,方波进入单片机进行编译计数,最终数码管短时间内显示纸张的数量,系统控制方便,操作简单,可用于中小规模纸张计数。     

基于延时预测的模型状态反馈网络控制方法

网络延时的存在不仅会使控制系统的动、静态性能变差,还可能会破坏系统的稳定性,造成既有控制方法的失效。针对带有随机延时的网络控制系统,提出了一种基于网络延时实时预测和系统状态逼近的控制方法。首先,建立无延时的理想控制系统模型作为标准控制系统模型;其次,应用基于隐马尔可夫模型(HMMs)的延时预测算法预测网络延时,该方法能够实时自适应学习,以适应网络负载情况的变化,得到更符合实际情况的延时预测值;最后,根据网络延时的预测值、实际网络控制系统与标准控制系统模型的状态之差,来调整控制信号,从而使实际网络控制系统的状态与标准控制系统模型接近、甚至相等,达到期望的控制效果。数字仿真结果表明,这一方法是可行的,能够获得更加快速的动态性能和稳定的静态性能。     

舰艇运动姿态实时预测方法研究

针对某艇载发射装置稳定控制系统中舰艇姿态数据因采样和传输产生的延迟问题,建立组合Kal-man滤波隔点预测算法的数学模型,并采用算法流程调整法、衰减记忆法和平方根法对预测算法进行改进优化,实现对舰艇横纵摇运动姿态精确实时的预测.通过Matlab软件对优化前后的预测算法进行仿真验证.实验结果表明,改进优化后的组合Kalman滤波隔点预测算法满足舰艇上发射装置稳定控制系统姿态实时预测的需求.     

基于双边闭环函数的网络化采样控制系统稳定性分析EI北大核心CSCD

考虑数据通信时延不确定环境下网络化采样控制系统的稳定性问题.首先基于输入时滞方法,建立包含采样周期信息的网络化采样控制系统的数学模型,在此基础上,采用双边闭环函数方法和自由矩阵积分不等式技术,得到网络传输时滞变化区间依赖稳定性新准则,并进一步讨论了网络化采样控制系统中网络时延与采样周期之间的关系.仿真结果表明减小采周期可以增强网络控制系统对网络通信时延的鲁棒性.