CPU与简单模型机设计实验中的关键问题分析

模型机设计实验是计算机组成原理实验中的一个综合性较强的实验,要求学生在掌握各部件单元电路的基础上,构建一台模型计算机。文章选用TD-CMA实验教学系统,针对采用微程序控制器设计的CPU与简单模型机设计实验,从连线排查、指令设计、微程序设计、指令控制、程序运行等方面分析该实验中的关键问题,并给出每个问题的解决方法。     

DJS200/10机磁带机控制器微程序设计

本文叙述当前外部设备控制器设计思想新的发展动向,即微程序编制技术在外部设备控制器中的应用;试图通过对DJS200—10机磁带控制器微程序设计的说明,阐明微程序编制技术在计算机外设控制器设计上的一般特点和优化原则。最后提出一种有一定通用性的外设控制器方案要点。     

计算机组成原理虚拟实验环境的设计及实现

根据实验教学的需要,结合计算机组成原理的特点,对计算机组成原理虚拟实验环境进行了研究.该实验环境基于清华大学计算机厂设计研制的Tec-xp实验箱,开发软件平台采用Microsoft Visual C++6.0语言和SQLServer2003数据库技术.该实验环境的搭建从系统的需求分析出发,采用面向对象的仿真方法进行建模,同时结合计算机系统的功能特性和计算机组成原理教学的特点,应用了离散事件系统仿真的基本理论和方法,使得虚拟环境的操作如同在真实的设备上一样.该虚拟实验环境的实施,给学生提供一个具有自主性的实验环境,具有良好的开放性、通用性和实用价值.     

微程序控制器扩展指令研究

在控制器中设计新指令是控制器教学中比较难的内容。为解决TEC-XP16教学机缺少乘法指令和除法指令的问题,基于TEC-XP16教学机,介绍微程序控制器的基本组成与工作原理,分析在微程序控制器中扩展指令的主要过程,提出一种微程序控制器中MUL乘法指令与DIV除法指令的设计方案;以扩展MUL乘法指令为例,详细介绍在TEC-XP16教学机微程序控制器中设计实现扩展指令的完整过程;以实验方式验证了所设计和实现的乘法指令与除法指令的功能。所提出的设计方法对微程序控制器部件的教学与实验有一定的指导作用。     

EDA技术在计算机硬件设计中的应用与研究

文章介绍应用EDA技术实现计算机CPU的设计和微程序控制器设计的技巧与方法,阐述了采用EDA设计的特点,并对设计中的重难点进行了解析。     

DJS-142计算机的微程序设计

本文概述了DJS-142计算机微程序控制器的设计方案。针对该机指令具有多组操作码和可变指令格式的特点,采用以微程序设计为主、以组合逻辑设计为辅的方案。用ROM器件实现微程序控制存储器。用PLA器件实现微地址编码器。由于充分利用PLA的可编程序寻址方式的特点、借助于适当地选择地址编码和计算机辅助设计手段进行逻辑压缩,使编址器所需的可编程序逻辑阵列(PLA)器件大为减少。因而整个设计显得比较规整、灵活和经济,且具有一定的可扩充性。     

面向系统能力培养的计算机硬件课程实验教学改革

针对计算机硬件课程实验教学中存在的问题,提出面向计算机系统能力培养,通过虚拟仿真技术将计算机硬件课程群(数字逻辑、计算机组成原理、计算机体系结构、微机接口)实验贯通起来的教学改革方案,阐述在proteus虚拟仿真软件中验证计算机组成部件、设计CPU、组装微型计算机系统的详细实验内容,同时提出一种"软硬一体化"的创新实验箱设计,令虚拟仿真软件中的CPU模型通过总线实时与实验箱硬件上的真实外设交互。     

TEC-XP16教学机浮点运算指令快速设计方法

为解决TEC-XP16教学机缺少浮点运算指令的问题,设计32 bit浮点加法、32 bit浮点减法、32 bit浮点乘法、32 bit浮点除法指令以及实现浮点运算的算法。为解决人工方式设计微程序和修改微程序控制器源程序效率低且容易出错等问题,提出一种能够由汇编语言程序自动生成微程序以及能够由微程序自动修改控制器ABEL语言源程序的方法。实验结果表明,所设计的32 bit浮点运算指令的功能是正确的,平均5 s之内就能根据汇编语言源程序自动生成微程序,平均2 s之内就能根据微程序等自动修改并生成控制器ABEL语言源程序。该方法也可推广到其他复杂指令的设计。     

微程序控制器的设计与实现

该文讨论了NCS处理器中微程序控制器的设计方法,介绍了微程序控制器的基本构成电路和工作特点;在设计中采用了诸如：多入口地址输入、内外码转换、封锁机制等提高控制器性能的方法,并确定了电路的工作时钟、数据通路和控制通路。最后指出成功的微程序控制器设计是设计高性能CPU的关键。     

一个微程序控制的模型机

本文着重介绍一台大型计算机的模型机中采用的微程序控制器。由于大型计算机的速度高、指令繁多、设备复杂,因此所采用的微程序控制器应能适应这些特点。本文所介绍的内容,就是提出一个解决大型机中所用微程序控制器的方案,以及一些具体的实现方法。这台模型机曾于1971年装銲出来,经过调试和稳定性考验,证明所用方案是稳定可靠的。     

基于MFA与PID控制器的串级控制系统的实验比较

通过实时控制试验,对比了MFA与常规PID分别作为外环控制器的串级控制系统以及单闭环MFA与常规PID控制器的抗干扰能力,试验表明,MFA的控制效果要比PID好,调整参数也比较简单.     

免疫最优PID控制器设计与应用

以基于欧氏距离和精英交叉的人工免疫算法(DKBAIA)为基础,提出了一种新的最优PID控制器的设计方法。这种方法的核心是以ITAE性能准则为目标函数,采用DKBAIA去调整和优化PID控制器参数,以获得最优的目标函数值,进而获得最优的PID控制器。所设计的这种控制器称为DKBAIA—PID控制器。将该控制器用于控制智能仿生人工腿的执行电机中,并进行计算机仿真实验,结果表明:这种基于免疫算法的最优PID控制器具有良好的动态和稳态性能。     

基于极点配置的二级倒立摆最优控制器设计

介绍了按规定的主导极点选择最优控制加权阵的原理,并在方法上作了一定改进。把传统的最优控制与极点配置结合起来,既得到了系统最优控制器,又得到了具有工程意义希望的性能指标。并成功地把最优控制理论应用于二级倒立摆控制系统,设计出具有期望主导极点的最优控制器,实现了对二级倒立摆系统的稳定控制。     

三维控件在教学实验中的应用研究

利用MFC和OpenGL开发了一个三维显示的ActiveX控件,此控件通过加入动力学模块来完成教学实验的计算机仿真,用户能通过鼠标操作和键盘操作控制实验仿真的过程,更易于让学生去理解和掌握实验内容。文中以实验教学中“单摆实验”为例子,在PowerPoint中进行效果测试。     

Online Balance Controllers for a Hopping and Running Humanoid Robot

This paper describes online balance controllers for running in a humanoid robot and verifies the validity of the proposed controllers via experiments. To realize running in the humanoid robot, the overall control structure is composed of an offline controller and an online controller. The main purpose of the online controller is to maintain dynamic stability while the humanoid robot hops or runs. The online controller is composed of the posture balance control in the sagittal plane, the transient balance control in the frontal plane and the swing ankle pitch compensator in the sagittal plane. The posture balance controller makes the robot maintain balance using an inertial measurement unit sensor in the sagittal plane. The transient balance controller makes the robot keep its balance in the frontal plane using gyros attached to each upper leg. The swing ankle pitch compensator prevents the swing foot from hitting the ground at unexpected times while the robot runs forward. HUBO2 was used for the running experiment. It was designed for the running experiment, and is lighter and more powerful than the previous walking robot platform, HUBO. With the proposed controllers, HUBO2 ran forward stably at a maximum speed of 3.24 km/h and this result verified the effectiveness of the proposed algorithm. In addition, in order to show the contribution of the stability, the running performance according to the existence of each controller was described by experiment.     

FGC多变量预测解耦控制仿真

该文提出一种基于线性化模型冷连轧机动态变规格(FGC)解耦控制器。该控制器采用预测控制算法，将解耦和控制器的设计融为一体，设计过程相对简单。仿真结果证明系统有很好的动态响应，很大程度上弥补了线性化模型的不足。     

Identification for control: Optimal input intended to identify a minimum variance controller

It is well known that the quality of the parameters identified during an identification experiment depends on the applied excitation signal. Prediction error identification using full order parametric models delivers an ellipsoidal region in which the true parameters lie with some prescribed probability level. This ellipsoidal region is determined by the covariance matrix of the parameters. Input design strategies aim at the minimization of some measure of this covariance matrix. We show that it is possible to optimize the input in an identification experiment with respect to a performance cost function of a closed-loop system involving explicitly the dependence of the designed controller on the identified model. In the present contribution we focus on finding the optimal input for the estimation of the parameters of a minimum variance controller, without the intermediate step of first minimizing some measure of the model parameter accuracy. We do this in conjunction with using covariance formulas which are not asymptotic in the model order, which is rather new in the domain of optimal input design. The identification procedure is performed in closed-loop. Besides optimizing the input power spectrum for the identification experiment, we also address the question of optimality of the controller. It is a wide belief that the minimum variance controller should be the optimal choice, since we perform an experiment for designing a minimum variance controller. However, we show that this may not always be the case, but rather depends on the model structure.     

The setpoint overshoot method: A simple and fast closed-loop approach for PID tuning

A simple method has been developed for PID controller tuning of an unidentified process using closed-loop experiments. The proposed method requires one closed-loop step setpoint response experiment using a proportional only controller, and it mainly uses information about the first peak (overshoot) which is very easy to identify. The setpoint experiment is similar to the classical Ziegler–Nichols (1942) experiment, but the controller gain is typically about one half, so the system is not at the stability limit with sustained oscillations. Based on simulations for a range of first-order with delay processes, simple correlations have been derived to give PI controller settings similar to those of the SIMC tuning rules (Skogestad (2003) [6]). The recommended controller gain change is a function of the height of the first peak (overshoot), whereas the controller integral time is mainly a function of the time to reach the peak. The method includes a detuning factor that allows the user to adjust the final closed-loop response time and robustness. The proposed tuning method, originally derived for first-order with delay processes, has been tested on a wide range of other processes typical for process control applications and the results are comparable with the SIMC tunings using the open-loop model.     

一种新式三维模糊控制的设计方法

本文介绍设计三维模糊控制器的一种新方法，这种算法能很容易的解决三维模糊控制器在实际中遇到的难题。通过仿真实验可以看出三维模糊控制比二维模糊控制有更优良的控制品质，同时具有很强的适应性和鲁棒性。     

Design and Robust Performance Evaluation of a Fractional Order PID Controller Applied to a DC Motor

This paper proposes a methodology for the quantitative robustness evaluation of PID controllers employed in a DC motor. The robustness analysis is performed employing a 23 factorial experimental design for a fractional order proportional integral and derivative controller (FOPID), integer order proportional integral and derivative controller (IOPID) and the Skogestad internal model control controller (SIMC). The factors assumed in experiment are the presence of random noise, external disturbances in the system input and variable load. As output variables, the experimental design employs the system step response and the controller action. Practical implementation of FOPID and IOPID controllers uses the MATLAB stateflow toolbox and a NI data acquisition system. Results of the robustness analysis show that the FOPID controller has a better performance and robust stability against the experiment factors.