基于FPGA硬件实现的谐波检测方法

针对现有系统对谐波检测实时性差和精度低的问题,介绍一种基于傅立叶变换和FPGA硬件实现的谐波检测方法.分析了谐波检测中影响测量精度的关键因素,采用数字锁相环来同步被测信号,以减小由非同步采样所产生的误差.基-4FFT 处理器的硬件设计采用全并行的乘法运算单元结构和并行的存储分配方法,最大限度地提高谐波检测的速度.数字锁相环和基-4 FFT 算法用VHDL语言设计实现,并用MAX plus Ⅱ软件进行仿真,仿真结果表明,所设计的数字锁相环可以很好地跟踪被测信号,在180ms时,误差仅为0.01Hz,很好地消除了非同步采样所引起的测量误差;采用所设计的基-4FFT运算器对给定的谐波数据进行运算,得到的谐波幅值和相位误差小于0.05%,运算时间仅为8μs.     

新型锁相环在频率跟踪技术中的研究

在比较电力系统频率跟踪技术中软硬件同步优缺点的基础上,提出了一种基于FPGA的全数字锁相环(ADPLL)电路实现电力系统频率跟踪的技术;将FPGA技术运用于同步跟踪技术中,解决了软硬同步方法中的各个不足之处;全数字锁相环电路采用VHDL语言和FPGA设计,仿真波形和实验结果表明,该电路能够很好地跟踪电网频率的实时变化,相位误差仅为0.1%,频率测量误差仅为0.06%,实现了同频率同相位的锁定;速度快、精度高;对电网的谐波计算有较大的实际意义.     

高动态条件下BPSK信号载波的同步算法

在诸如火箭、导弹等飞行器的数据传输中,不可避免遇到多普勒频移的影响,多普勒效应将导致收发信号之间频率发生偏移,高动态将产生很大的多普勒频移.并且还伴随不同的加速度,这都会影响载波的同步,通过对锁相环载波同步机理的分析,提出在全数字科斯塔斯环上、改变环路带宽法进行快速、高精度载波跟踪同步,在全数字环中,变带宽法具有结构简单,容易实现的特点,设计了全数字锁相环,进行了Matlab仿真,仿真结果说明该算法是可行的,能够适应高动态大频偏环境下,载波的快速、高精度跟踪.     

全数字锁相环实现的自适应低通滤波电路

提出了一种新的基于全数字锁相环的自适应低通滤波系统的结构和实现方法。输入信号经整形后产生方波信号,方波信号经FPGA实现的全数字锁相环锁相同步倍频后,再将同步倍频信号输入到开关电容滤波器MAX295的时钟输入端,通过该时钟信号来控制滤波器的截止频率,从而实现滤波器频率的自动跟踪。介绍了系统设计原理,详细分析了FPGA实现全数字锁相环和锁相倍频的设计方法。通过实验验证了该系统的可行性和有效性,能够实现1 kHz至50 kHz的频率自跟踪倍频和滤波。     

自适应数字带阻滤波器的设计及应用

本文采用自适应跟踪数字带阻滤波器自动跟踪被测信号中干扰信号的频率，并利用该频率设计相应的数字带阻滤波器去除被测信号中的干扰信号。试验表明，该方法具有设计简单、应用方便、实时性强等特点。     

北斗B1信号捕获跟踪算法的软件仿真研究

针对北斗B1频率的I支路信号,设计并实现了北斗软件接收机的基带处理部分;阐述了北斗B1频点信号的扩频体制和产生过程,并行码相位搜索捕获策略以及鉴相辅助跟踪环路,并设计了二阶数字环路滤波器;同时采用Matlab软件,仿真北斗中频数字信号,编码实现捕获跟踪算法,并分别通过对仿真信号和真实卫星信号的捕获跟踪,验证捕获跟踪算法的可行性,并提出锁频环辅助锁相环算法的改进思路;为进一步开展北斗软件接收机相关技术研究打下了基础。     

基于FPGA的自动变模控制感应加热电源全数字锁相环研究

针对感应加热电源频率跟踪设计中传统锁相环电路设计复杂、跟踪速度慢、锁相频带窄、单独模块设计修改繁琐等问题,提出一种基于FPGA的自动变模控制感应加热电源全数字锁相环,即拓展锁相环中心频率频带和采用变模控制实现快速频率跟踪.应用SOC技术完成系统设计,并进行典型频带的计算机仿真.仿真结果证实了该设计具有宽范围的锁相能力及快速精确的频率跟踪性能,满足感应加热电源对负载频率变化的快速跟踪要求.     

基于CPLD的高精度全数字锁相环

针对由电力系统工频信号频率波动导致的不能同步采样从而影响电参量测量精度的问题,提出以74HC297为核心设计高精度的全数字锁相环(ADPLL)电路,实现精密跟踪锁定待测信号频率和相位,并在CPLD中实现.本文推导ADPLL在频率跳变时的锁定时间表达式,分析影响锁定速度和精度的相关因素.给出实验波形和数据,实验结果表明,该ADPLL的锁定精度至少达到0.000 2 Hz以上.     

卫星定位接收机高精度伪码跟踪的设计与实现

在卫星定位接收机中,伪码跟踪的精度直接影响定位精度。介绍了延迟锁相环及其数学模型。在对比分析等量采样和非等量采样条件下延迟锁相环跟踪精度的基础上,提出了采用非等量采样延迟锁相环的伪码跟踪数字实现方案。该方案复杂度低,易于实现。实验结果表明该方案对码速率为10.23 MHz的伪码跟踪精度可达1 ns,实现了伪码的精确同步。该设计已应用于卫星定位接收机的研制开发中。     

一种自动控制中正弦信号同步采集与处理的方法

介绍一种用于微型计算机控制的正弦信号同步采集和处理的方法，这种方法采用锁相环技术实现采样控制信号与测试信号的频率完全相同，从而克服了用软件设定采样时间间隔而造成的由于被测信号频率波动所引起的误差，同时，采用ＦＦＴ方法，可实现对被测信号的快速处理及谐波分析。     

Robustness of temporal logic specifications for continuous-time signals

In this paper, we consider the robust interpretation of Metric Temporal Logic (MTL) formulas over signals that take values in metric spaces. For such signals, which are generated by systems whose states are equipped with non-trivial metrics, for example continuous or hybrid, robustness is not only natural, but also a critical measure of system performance. Thus, we propose multi-valued semantics for MTL formulas, which capture not only the usual Boolean satisfiability of the formula, but also topological information regarding the distance, ε$\epsilon$, from unsatisfiability. We prove that any other signal that remains ε$\epsilon$-close to the initial one also satisfies the same MTL specification under the usual Boolean semantics. Finally, our framework is applied to the problem of testing formulas of two fragments of MTL, namely Metric Interval Temporal Logic (MITL) and closed Metric Temporal Logic (clMTL), over continuous-time signals using only discrete-time analysis. The motivating idea behind our approach is that if the continuous-time signal fulfills certain conditions and the discrete-time signal robustly satisfies the temporal logic specification, then the corresponding continuous-time signal should also satisfy the same temporal logic specification.     

Probabilistic logic programming on the web

We present the web application ‘cplint on SWI‐Prolog for SHaring that allows the user to write (SWISH)' Probabilistic Logic Programs and submit the computation of the probability of queries with a web browser. The application is based on SWISH, a web framework for Logic Programming. SWISH is based on various features and packages of SWI‐Prolog, in particular, its web server and its Pengine library, that allow to create remote Prolog engines and to pose queries to them. In order to develop the web application, we started from the PITA system, which is included in cplint , a suite of programs for reasoning over Logic Programs with Annotated Disjunctions, by porting PITA to SWI‐Prolog. Moreover, we modified the PITA library so that it can be executed in a multi‐threading environment. Developing ‘cplint on SWISH’ also required modification of the JavaScript SWISH code that creates and queries Pengines. ‘cplint on SWISH’ includes a number of examples that cover a wide range of domains and provide interesting applications of Probabilistic Logic Programming. By providing a web interface to cplint , we allow users to experiment with Probabilistic Logic Programming without the need to install a system, a procedure that is often complex, error prone, and limited mainly to the Linux platform. In this way, we aim to reach out to a wider audience and popularize Probabilistic Logic Programming. Copyright © 2015 John Wiley & Sons, Ltd.     

Application of probability to enhance the performance of fuzzy based mobile robot navigation

This paper presents a new path planning algorithm based on Probability and Fuzzy Logic (PFL) as a duality technique to enhance the performance of Fuzzy Logic alone. Fuzzy Logic interacts with the grading of obstacles existed in the path and probability lies over the decision to move the mobile robot. The fuzzy grading correspondence with the probabilistic decision is the primary function of moving the mobile robot towards the goal and the secondary is path planning which lies over the probability distribution function. The distance–speed combination rule is developed for effective navigation. The single and multiple mobile robot systems have been tested successfully in a dense environment in presence of obstacles (static and dynamic) and moving goal. The obtained results are optimal when compared to other navigational approaches in sense of navigational path length and time in the static and dynamic environment.     

基于结构的多级逻辑优化

本文提出一个基于结构的多级逻辑优化算法ＭＬＯＢＬＳ，多级组合逻辑网络的优化通过分析名逻辑门的可替代函数，并用简单的替代函数作替代变换完成。算法ＭＬＯＢＬＳ具有良好的逻辑结构重构能力，能得到近似最优的多级逻辑结构。整个优化过程在多级逻辑结构上直接进行，其时／空复杂性较少依赖于多级逻辑结构的基本输入／输出数目。／     

Completeness and incompleteness for plausibility logic

Plausibility Logic was introduced by Daniel Lehmann. We show—among some other results—completeness of a subset of Plausibility Logic for Preferential Models, and incompleteness of full Plausibility Logic for smooth Preferential Models.     

逻辑分析仪数据处理软件无损压缩算法研究

在对信号进行分析处理时,经常使用逻辑分析仪设备对被测信号进行采集分析,采集数据将在上位机进行存储;如果直接存储,无疑将占用大量的存储空间,为了解决逻辑分析仪采集数据量大、数据直接存储占用空间大的问题,文章以AMC2511逻辑分析仪和码型发生器为硬件平台,详细研究了数据的各种无损压缩算法,并根据采集数据本身的特点,提出了RLE和LZW算法相结合的设计思路;通过对采集数据进行压缩试验,总结出该算法在获取大的压缩比的同时,缩短了压缩时间。     

Blind estimation of the PN sequence in lower SNR DS-SS signals with residual carrier

This paper presents a method of singular value decomposition (SVD) plus digital phase lock loop (DPLL) to solve the difficult problem of blind pseudo-noise (PN) sequence estimation in low signal to noise ratios (SNR) direct sequence spread spectrum (DS-SS, DS) signals with residual carrier. Of course, the method needs to know the parameters of DS signal, such as the period and code rate of PN sequence. Firstly, the received signal is sampled and divided into non-overlapping signal vectors according to a temporal window, whose duration is two periods of PN sequence. Then, an autocorrelation matrix is computed and accumulated by the signal vectors one by one. The PN sequence with residual carrier can be estimated by the principal eigenvector of this autocorrelation matrix. Furthermore, a DPLL is used to deal with the estimated PN sequence with residual carrier, it estimates and tracks the residual carrier, removes the residual carrier in the end. Theory analysis and computer simulation results show that this method can effectively realize the PN sequence estimation from the input DS signals with residual carrier in lower SNR.     

PD型模糊学习控制及其在可重复轨迹跟踪问题中的应用

针对可重复轨迹跟踪问题,提出了一种PD型模糊学习算法.该算法集成两种控 制:作为基础的PD型模糊逻辑算法和改善系统性能的学习算法.模糊学习控制在模糊控制 基础上引入迭代学习算法,使得模糊PD控制器可以精确地跟踪可重复轨迹以及消除周期性 扰动.本文在能量函数和泛函分析的基础上,通过严格的推导表明PD型模糊学习算法可达 到:1)系统跟踪误差一致收敛到零;2)学习控制序列几乎处处收敛到理想的控制信号.     

Limitations of restricted branching in clause learning

The techniques for making decisions, that is, branching, play a central role in complete methods for solving structured instances of constraint satisfaction problems (CSPs). In this work we consider branching heuristics in the context of propositional satisfiability (SAT), where CSPs are expressed as propositional formulas. In practice, there are cases when SAT solvers based on the Davis-Putnam-Logemann-Loveland procedure (DPLL) benefit from limiting the set of variables the solver is allowed to branch on to so called input variables which provide a strong unit propagation backdoor set to any SAT instance. Theoretically, however, restricting branching to input variables implies a super-polynomial increase in the length of the optimal proofs for DPLL (without clause learning), and thus input-restricted DPLL cannot polynomially simulate DPLL. In this paper we settle the case of DPLL with clause learning. Surprisingly, even with unlimited restarts, input-restricted clause learning DPLL cannot simulate DPLL (even without clause learning). The opposite also holds, and hence DPLL and input-restricted clause learning DPLL are polynomially incomparable. Additionally, we analyze the effect of input-restricted branching on clause learning solvers in practice with various structured real-world benchmarks. This is an extended version of a paper [27] presented at the 13th International Conference on Principles and Practice of Constraint Programming (CP 2007) in Providence, RI, USA. The first author gratefully acknowledges financial support from Helsinki Graduate School in Computer Science and Engineering, Academy of Finland (grants #211025 and #122399), Emil Aaltonen Foundation, Jenny and Antti Wihuri Foundation, Finnish Foundation for Technology Promotion TES, and Nokia Foundation. The second author gratefully acknowledges the financial support from Academy of Finland (grant #112016).