改进神经网络在模拟电路故障诊断中的应用

研究模拟电路故障诊断准确性问题.电路故障与引起故障因素之间呈高度非线性,传统故障识别方法无法识别其非线性特点,导致传统故障方法的诊断精度低.为了提高电路故障诊断的精度,提出一种遗传算法优化BP神经算法的模拟电路故障诊断方法.首先对故障电路样本进行特征提取和归-化处理,然后采用遗传算法对BP神经网络参数进行优化,最后利用最优参数BP神经网络对电路故障样本进行训练和建模,获得电路故障诊断结果.在MATLAB平台上对模拟电路故障进行仿真测试,仿真结果表明,与传统模拟电路故障诊断方法相比,提高了模拟电路故障诊断精度,缩短了故障诊断时间,在模拟电路故障中有着广泛的应用前景.     

基于SIMULINK的非线性优化PID控制

提出了利用MATLAB优化控制工具箱与优化函数相结合对非线性系统PID控制器进行优化设计的方法,同时建立了基于MATLAB/SIMULINK的非线性系统仿真图.通过仿真试验,验证了该参数优化设计方法不仅方便快捷,而且使系统具有较好的控制精度和稳定性,可使系统的性能有所提高.     

基于研华数据采集卡PCI-1710-B的倒立摆控制系统研究

倒立摆控制系统是一个典型的高阶次、不稳定、多变量、非线性和强藕合控制系统.本文研究对象是基于研华公司数据采集卡PCI-1710-B的倒立摆控制系统.通过对一级倒立摆系统控制原理分析、数学建模分析、状态反馈设计、MATLAB仿真,然后在搭建的实验平台上用LQR方法编程实现对其最优控制.MATLAB仿真结果良好,软件部分采用VB开发,实现了对系统的‘倒立'控制和相关实时参数的显示.     

小功率开关磁阻风力发电系统模拟装置研发

分析开关磁阻电机风力发电工作原理,推导其非线性数学模型,在MATLAB仿真平台上建立基于PWM斩波和APC复合控制的开关磁阻发电系统仿真模型,进行相关仿真实验,为硬件电路设计的参数选择提供帮助。以DSP为控制核心,设计开关磁阻风力发电系统功率主电路与控制电路,实现小功率风力发电。实验和性能测试验证了设计方案的可行性与有效性。     

新颖交流开关变换器的建模和仿真分析

开关电源是一个非线性系统,它的分析与设计一直是一个难题。本文对在开关电源方面应用较多的状态空间平均法进行了数学推导,结合MATLAB软件对新颖交流升降压变换器（Buck-Boost）建立了电路模型、数学模型和电路分析法模型,并进行了仿真对比,定量的讨论了状态空间平均法的适用条件,说明状态空间平均法的本质,并用其分析了开关频率对于输出电压纹波的影响。     

基于dSPACE开关磁阻电机控制器开发方法

本文提出了一种基于dSPACE半实物仿真环境下,开关磁阻电机控制器的开发方法.通过dSPACE系统与实际驱动电路相结合,建立了开关磁阻电机控制器的开发平台,能够方便有效地实现多种开关磁阻电机控制算法.该平台的硬件部分由dSPACE系统的硬件部分结合电机的驱动电路,驱动电路根据不同的电机开发需求设计.开发平台的软件部分包括模块化建模工具MATLAB/Simulink,与综合实验和测试软件ControlDesk.通过开发平台的建立,归纳出一套开关磁阻电机控制器的开发方法.该方法在MATLAB/Simulink下建立的仿真模型通过ControlDesk在线修调参数,同时自动生成控制代码.与传统方法相比,该方法能显著的缩短控制器的开发周期,降低开发成本.     

非线性仿射控制系统的高阶滑模控制

研究非线性仿射系统的高阶滑模控制问题.通过适当的输入及非线性状态变换将系 统分解为一个关于切换变量及其高阶导数的低阶线性子系统和一个关于滑模的低阶非线性子 系统,进而给出了其高阶滑模控制器的设计方法.最后,对两轮驱动的非完整移动机器人进行 了数值仿真,结果表明高阶滑模控制在抖振减弱方面确实具有一定的作用.     

基于MATLAB的非线性电路的数值模拟

混沌是非线性系统中的常见现象.本文提出了一个变形蔡氏电路,介绍了一个新的非线性电阻,讨论了此变形蔡氏电路的工作原理.由kirchoff's laws得到变形蔡氏电路的电路方程,建立了数学模型,分析了产生混沌现象的原因,采用了蔡氏电路的仿真算法--龙格库塔法,并使用MATLAB编写程序对其进行了数值模拟.本文设定了非线性电阻的伏安特性,通过调节电路参量观察到了混沌现象,双蜗旋混沌吸引子.     

基于传输线模型的动态电路建模与仿真分析

针对利用数值分析法求解高阶电路时难于列写系统状态空间方程,且计算复杂烦琐的问题,阐述了一种不需要列写状态空间方程,并且能够直接从动态电路元件得到电路计算模型的建模法(传输线模型(TLM)建模法),同时对一个含耦合元件的动态电路进行了建模和仿真,与常用的其它两种常用的数值分析法进行了比较分析.仿真结果表明.方法简单实用,物理概念清晰,能有效对各种动态电路特别足高阶电路进行求解,并且具有无条件的数值稳定性.     

面向方框图仿真的模型建立与仿真计算

在对高阶系统及非线性系统进行仿真时，需要求解高阶微分方程与非线性微分方程。当中的变量耦合问题较难处理，面向方框图仿真方法可以较好地解决这个问题，仿真计算简单，界面直观，对控制系统的设计起较好的辅助作用。主要介绍面向方框图的仿真模型的建立方法，讨论线性及非线性微分方程的方框图模型，并简单介绍面向方框图的仿真计算和误差分析。     

Modelling and simulation of the multi-scroll chaotic attractors using bond graph technique

This paper presents modelling and simulation of multi-scroll chaotic attractors by using a new simple and more general bond graph model. For this purpose, the multi-segment non-linear resistor in Chua’s circuit is modelled by using piecewise linearization with control inequalities. The proposed model consists of active/passive circuit elements, voltage-controlled current source (VCCS) and ideal switches. The advantage of modelling multi-segment non-linear resistor by using control inequalities yields minimum number of the switches and sources. Proposed model is simple and more general and, especially, could be used in various kinds of non-linear circuit in the chaos studies. Generally, two different non-linear resistor models are used in the literature to obtain odd and even numbers of the scrolls. In this study, one model is developed for both multi-scroll chaotic attractors. In this paper, bond graph simulation of Chua’s circuit is realized by using proposed model. The BONDAS program that developed in Matlab is used for the simulations, and satisfactory results are obtained.     

A GMDH neural network-based approach to passive robust fault detection using a constraint satisfaction backward test

This paper proposes a new passive robust fault detection scheme using non-linear models that include parameter uncertainty. The non-linear model considered here is described by a group method of data handling (GMDH) neural network. The problem of passive robust fault detection using models including parameter uncertainty has been mainly addressed by checking if the measured behaviour is inside the region of possible behaviours based on the so-called forward test since it bounds the direct image of an interval function. The main contribution of this paper is to propose a new backward test, based on the inverse image of an interval function, that allows checking if there exists a parameter in the uncertain parameter set that is consistent with the measured system behaviour. This test is implemented using interval constraint satisfaction algorithms which can perform efficiently in deciding if the measured system state is consistent with the GMDH model and its associated uncertainty. Finally, this approach is tested on the servoactuator being a FDI benchmark in the European Project DAMADICS.     

An efficient and reliable model to simulate microscopic mechanical friction in the Frenkel–Kontorova–Tomlinson model

The Frenkel–Kontorova–Tomlinson model is composed of a large number of non-linear, coupled differential equations that reproduce the friction occurring in mechanical systems in which the atomic smooth surfaces of two bodies slide against each other. The problem is very interesting since the possible solutions, which are very sensitive to the parameters of the system, range from simple stable harmonic solutions (in which the spectrum of the movement of individual atoms contains one frequency) to chaotic solutions (where the spectrum contains a series of incommensurable frequencies), passing through intermediate solutions formed by a spectrum of commensurable finite frequencies. The design of the model both for the static and dynamic problem, which follows the network method rules, is explained in detail and the model is run on standard electrical circuit simulation software to provide, in its own graphic ambient, the average total friction force, the Fast Fourier Transforms of atom displacement and the phase diagrams. The influence of the main parameters of the system (interaction force amplitude and stiffness between surface atoms and substrate) on the type of pattern of the solution is studied for a practical range of these parameters.     

A unified SVM framework for signal estimation

This paper presents a review in the form of a unified framework for tackling estimation problems in Digital Signal Processing (DSP) using Support Vector Machines (SVMs). The paper formalizes our developments in the area of DSP with SVM principles. The use of SVMs for DSP is already mature, and has gained popularity in recent years due to its advantages over other methods: SVMs are flexible non-linear methods that are intrinsically regularized and work well in low-sample-sized and high-dimensional problems. SVMs can be designed to take into account different noise sources in the formulation and to fuse heterogeneous information sources. Nevertheless, the use of SVMs in estimation problems has been traditionally limited to its mere use as a black-box model. Noting such limitations in the literature, we take advantage of several properties of Mercerʼs kernels and functional analysis to develop a family of SVM methods for estimation in DSP. Three types of signal model equations are analyzed. First, when a specific time-signal structure is assumed to model the underlying system that generated the data, the linear signal model (so-called Primal Signal Model formulation) is first stated and analyzed. Then, non-linear versions of the signal structure can be readily developed by following two different approaches. On the one hand, the signal model equation is written in Reproducing Kernel Hilbert Spaces (RKHS) using the well-known RKHS Signal Model formulation, and Mercerʼs kernels are readily used in SVM non-linear algorithms. On the other hand, in the alternative and not so common Dual Signal Model formulation, a signal expansion is made by using an auxiliary signal model equation given by a non-linear regression of each time instant in the observed time series. These building blocks can be used to generate different novel SVM-based methods for problems of signal estimation, and we deal with several of the most important ones in DSP. We illustrate the usefulness of this methodology by defining SVM algorithms for linear and non-linear system identification, spectral analysis, non-uniform interpolation, sparse deconvolution, and array processing. The performance of the developed SVM methods is compared to standard approaches in all these settings. The experimental results illustrate the generality, simplicity, and capabilities of the proposed SVM framework for DSP.     

Partial exponential stability of semi-state systems

The general class of non-linear non-autonomous semi-state systems is considered from the viewpoint of stability of system motions. A theorem is proved giving necessary and sufficient conditions for partial exponential stability of arbitrary motion of these systems over finite or infinite time intervals.

The results are illustrated by the analysis of a non-linear electrical circuit.     

基于模糊PI控制的光伏直流变换器控制策略研究

以光伏发电系统模型为基础,把直流变换器中的Boost电路作为研究对象,先分别采用占空比恒定的定脉宽调制和占空比可调节的传统PI控制作为控制方法,利用MATLAB/Simulink仿真工具搭建光伏发电系统的主电路模型,进而分别根据不同的控制方法对Boost电路进行仿真分析。由仿真分析得到,定脉宽调制控制和传统PI控制的参数设置均无法适应实际工况的变化。基于此,提出一种模糊PI控制算法,通过对传统PI控制的参数设定进行实时调整,改善Boost电路的输出电压,使系统能更好地克服实际运行工况变化带来的不利影响。通过仿真分析可得,模糊PI控制的鲁棒性增强,并且能够降低系统的输出电压超调,缩短系统的稳定时间,提升系统的抗干扰能力。     

基于Maxim控制器的无刷电机控制系统的优化设计

分析了无刷电机控制中的非线性问题和解决方案;以MAX6650/MAX6651控制器为核心,设计了无刷直流电机控制系统,并对其电机转速控制及其电路做了详细的阐述;通过典型设计案例对控制系统进行了分析;对MAX6650/MAX6651控制器在电机控制应用中的可靠性做了概述。     

Equivalent post-buckling models for the flexural behaviour of steel connections

Analytical solutions for the evaluation of the behaviour of steel connections are presented which are able to reproduce their full non-linear behaviour. Because usual models for the analysis of steel connections consist of translational springs and rigid links whereby the springs exhibit a non-linear force–deformation response, usually taken as a bi-linear approximation, they require an incremental non-linear analysis. Using a substitute elastic post-buckling model where each bi-linear spring is replaced by two equivalent elastic springs in the context of a post-buckling stability analysis using an energy formulation, closed-form solutions are obtained for a connection loaded in bending. Application to a beam-to-column welded connection using the component (spring) characterisation of code regulations yields the same results in terms of moment resistance and initial stiffness, being additionally able to trace the full unstiffening response.     

An adaptive orthogonal search algorithm for model subset selection and non-linear system identification

A new adaptive orthogonal search (AOS) algorithm is proposed for model subset selection and non-linear system identification. Model structure detection is a key step in any system identification problem. This consists of selecting significant model terms from a redundant dictionary of candidate model terms, and determining the model complexity (model length or model size). The final objective is to produce a parsimonious model that can well capture the inherent dynamics of the underlying system. In the new AOS algorithm, a modified generalized cross-validation criterion, called the adjustable prediction error sum of squares (APRESS), is introduced and incorporated into a forward orthogonal search procedure. The main advantage of the new AOS algorithm is that the mechanism is simple and the implementation is direct and easy, and more importantly it can produce efficient model subsets for most non-linear identification problems.     

光反馈激光器非线性仿真研究

一些传统计算方法对非线性系统的分析存在着一些困难。针对光反馈半导体激光器收发系统微分方程组的特点,对非线性性质做出了数学上的分析,考虑到在光反馈半导体激光器收发系统中,其微分方程含有延迟因子,无法直接利用多节点上的值的加权和来近似计算斜率。基于龙格-库塔法提出了一种有效的数值仿真算法,并在matlab平台上对给定参数条件下的发射端与接收端的归一化光场以及同步误差进行了仿真,证明了接收端光场信号可以很快与发射端光场信号一致,仿真结果表明仿真算法能有效对系统进行仿真分析。