UHF RFID 射频前端及其编解码设计

射频识别（Radio Frequency Identification，RFID）技术，是一种利用射频通信实现的非接触式的数据采集和自动识别技术（以下通称RFID技术）。而超高频射频识别技术（Ultra High Frequency RFID，UHF RFID）具有识别距离远、识别准确率高、识别速度快、抗干扰能力强等特点而成为当前研发的热点。UHF RFID读写器的难点就在于射频前端电路和基带编解码的设计，它们设计的好坏直接决定了读写器的性能好坏。 本文首先通过介绍UHF RFID读写器射频前端设计的基本原理，采用射频通用收发模块进行射频前端设计的方法，给出了以ADF7020收发芯片为核心的UHF RFID读写器的射频前端的整体设计和具体的实现电路，设计了包括射频收发电路、射频前端匹配电路、滤波电路、环行器电路、功率放大电路等。 其次根据EPC Gen-2的协议标准进行了UHF RFID读写器的基带编码解码的仿真设计，然后开发了以FPGA为核心的完整的数字基带硬件电路，实际调试表明整个基带编解码软件在硬件基带PCB板上运行状况良好，并能对EPC Gen-2的协议标准的命令进行正确的编码解码。 最后通过研究学习软件无线电的理论和开发方法，把UHF　RFID读写器的射频前端分成射频模拟前端和射频数字前端，给出了一种基于软件无线电思想的UHF RFID射频数字前端设计模型，并借助于SIMULINK中的信号处理工具箱对构建的数字前端的进行仿真验证，仿真结果验证了用软件无线电实现UHF RFID数字前端的可行性。

水下机器人-机械手系统构建与研究

描述了一水下机器人——机械手系统研究平台的搭建,详细介绍了三功能水下电动机械手的设计与实验,给出了载体分系统的设计结果,利用Matlab工具箱和M函数构建了系统仿真模型,可以有效地对系统规划和控制算法进行验证(包括分别对载体分系统和机械手分系统的控制),可为进一步的现场试验提供指导和方法验证。

自治水下机器人全自由度仿真

由于自治水下机器人技术的复杂性 ,系统仿真技术变得越来越重要。系统地分析了自治水下机器人 (AUV ,AutonomousUnderwaterVehicle)的运动模型和空间运动方程 ,运用MATLAB下的SIMULINK ,设计了自治水下机器人的全自由度仿真工具箱 ,包括机器人本体运动、位姿求解和坐标系转换等多个部分 ,可以方便地进行控制方法的全自由度的仿真。

远程AUV航行控制算法的应用研究

本文针对我国正在研制开发的长航程自治潜水器的特性及其对航行控制的要求，进行了以下研究：自适应模糊PID控制方法和单神经元自适应PID控制方法在航向控制回路的应用研究，以及沿规划路径航行的6自由度仿真。 本文首先介绍了远程AUV航行控制系统的组成，然后根据自治潜水器的各项参数建立了水平面和垂直面的数学模型，并对水平面和垂直面的数学模型进行了验证。 将PID控制与模糊控制的简便性、灵活性以及鲁棒性结合起来，为AUV设计了可在线修改PID参数的自适应模糊PID控制器，仿真结果证明了该种控制方法不但提高了AUV系统的动态特性，而且可在参数摄动和外界扰动时获得较好的控制性能。 将单神经元自适应PID控制方法应用在了航向控制回路。仿真实验表明，该控制器是一种设计简单、实现方便的智能控制器，具有动态性能好、稳态精度高、抗干扰性能强等特点。尤其对那些时变的、非线性的、滞后的被控对象，具有良好的控制效果，能有效的克服海流、波浪等扰动，提高AUV系统的动态特性。该方法适用于其它非线性、时变、强干扰的不确定复杂系统。 最后本文建立了基于Simulink的沿规划路径航行控制回路，进行了6自由度模型的仿真。在仿真中设定起始点和目的点，就可得到仿真的路径和达到目的点的时间。 关键词：自治潜水器；自适应模糊PID控制；单神经元自适应PID控制；自治水下机器人仿真

有缆水下机器人主动升沉补偿系统的控制研究

在深海区域，海面的海况条件相对比较恶劣，支持母船受风、浪、涌、流影响而产生较大幅度的升沉运动对有缆水下机器人正常作业和收放操作有较大的影响，水下机器人中继器的升沉运动甚至可以造成系缆的损害而使机器人本体丢失。如何提高水下机器人在相对恶劣海况条件下的安全性能、特别是水下机器人与中继器安全的释放与回收成为当前深海有缆水下机器人开发所需要面临的一个重要问题。有缆水下机器人主动升沉补偿技术的研究，对于提高水下机器人在相对恶劣海况条件下的安全作业和收放具有重要的意义，对提高水下机器人抵御恶劣海况的能力具有重要的作用。 本文主要研究以液压绞车为执行机构的主动升沉补偿系统的控制。 研究了使用Kalman滤波方法根据测量得到的升沉加速度估计升沉运动加速度、速度和位移的滤波算法；建立了升沉补偿系统的模型，分析了升沉补偿系统的负载，以及升沉补偿对于液压系统功率、流量、压力的要求。 对电液比例阀的死区进行了补偿；设计了前馈控制算法，前馈控制简单实用，易于工程应用，能提高升沉补偿效率；但是其对参数敏感，需要实时调节控制预值，这些都会影响控制效果；为了得到更好的控制效果，设计了速度闭环的控制算法，结合升沉补偿系统可能功率不足的特点，需要估算其最大速度能力，先设置速度限制，将得到的升沉速度限制在速度能力范围内进行补偿，闭环控制具有抗干扰的能力，不需要实时调节控制预值，并且将正反方向的速度限制设为相同值时，补偿后的升沉位移不会漂移；针对系统功率有限和参数时变的特性，提出了智能预测控制算法，先是模型辨识，系统功率足够和功率不够时，模型结构不一样，需要在辨识时能识别处于哪种工况，并采用不同的控制策略，研究了功率足够时的自校正预测控制算法，使用智能预测控制算法，能够克服系统功率有限和参数时变给控制带来的困难。 建立了升沉补偿系统的matlab/simulink仿真模型和Amesim仿真模型，对功率足够和欠功率的情况进行了仿真，以验证控制的效果。 利用主动升沉补偿模拟液压绞车分析了控制预值实时调整的主动升沉补偿开环前馈控制的补偿效率。并利用作业型ROV收放系统的液压绞车进行了主动升沉补偿实验，实验表明分段死区补偿、前馈控制算法是有效的。

轮式移动机器人沙地行驶控制建模与仿真研究

结合车轮沙土相互作用的力学分析,研究解决轮式移动机器人沙地行驶车轮过度滑转下陷问题。考虑纵列式重复通过车轮沙土力学参数的修正,建立六轮式沙地移动机器人的动力学模型,以车轮滑转率为状态变量,设计了移动机器人沙地行驶的滑模驱动控制器跟踪车轮期望滑转率。MATLAB/Simulink仿真结果表明,采用该控制器可以较快地跟踪期望滑转率,有效地限制机器人车轮的滑转,避免车轮的过度下陷。

直驱式容积控制电液伺服系统的建模和仿真研究

电液伺服控制系统以其出力大、响应快、精度高而广泛地应用于国防与民用领域。但是，传统的电液伺服系统由于电液伺服阀对油液精度要求高，抗污染能力弱，从而在一定程度上限制了它更广泛的应用，随着技术的进步，出现了一种新型的电液伺服系统—直驱式容积控制电液伺服系统，它是由交流伺服电机驱动的液压泵与执行元件组成，它具有伺服电动机控制的灵活性和液压系统出力大的双重优点，具有高效节能、体积小、可靠性高等显著优点，在一定程度上弥补了传统电液伺服系统的不足，从而被认为是未来电液伺服控制系统的重要发展方向之一。本文的研究内容是以中国科学院沈阳自动化研究所与日本石川岛播磨重工业株式会社的合作项目“电液混合驱动系统（Hybrid Actuator System）研究与开发”为基础，开展原理与特性研究，主要研究内容有以下一些项目：研究直驱式容积控制电液伺服系统的工作原理、设计理论与控制方法，建立直驱式容积控制电液伺服系统的性能试验系统，进行该系统的静、动态性能仿真与分析，研制一套直驱式容积控制电液伺服系统的原理样机。 第一、直驱式容积控制电液伺服系统的原理与机械结构研究，研究直驱式容积控制电液伺服系统的工作原理与结构方案，详细分析比较与传统电液伺服系统的优缺点，研究基与双向定量泵集成阀体的一体化设计技术，进行直驱式容积控制电液伺服系统的系统设计。 第二、直驱式容积控制电液伺服系统的建模与控制算法研究，研究直驱式容积控制电液伺服系统的建模方法，建立直驱式容积控制电液伺服系统的数学模型，研究满足系统性能指标的PID控制策略，使系统在稳定的前提下具有良好的动态品质和高的稳态精度。 第三、直驱式容积控制电液伺服系统集成技术研究，该直驱式容积控制电液伺服系统是由交流伺服电动机、双作用定量泵、方向控制阀、液压缸，以及多个传感器共同组成的。研究系统模块化设计方法，研究系统集成技术，建立直驱式容积控制电液伺服系统与液压系统性能的最佳匹配方法，研究直驱式容积控制电液伺服系统的实现技术。 第四、直驱式容积控制电液伺服系统的性能仿真研究，在上述建立的伺服系统模型基础上，利用MATLAB内的动态仿真库SIMULINK，仿真分析直驱式容积控制电液伺服系统的静、动态性能，研究改善系统性能的措施方法。 第五、直驱式容积控制电液伺服系统的补油性能状态研究，详细分析系统在各种工况下的内部油液流动状态，并基于此研究补油阀体的集成设计，建立补油设备的数学模型，仿真分析该补油装备的静、动态运行性能，研究补油阀的设计技术，在上述分析基础上，设计加工满足系统运行性能状态的叠加式液控补油阀。 第六、在上述工作基础上，研制一套直驱式容积控制电液伺服系统，验证系统设计原理，控制算法，及系统集成技术、研究高性能直驱式容积控制电液伺服系统的设计方法和实现技术。 关键词 液压技术；交流伺服电动机；直驱式容积控制；动态特性；叠加液控补油阀

基于DSP的视觉焊缝跟踪控制系统的设计

目前，随着科技水平的进步，人们对焊接质量的要求越来越高，为了保证焊接质量，通常配备焊缝自动跟踪系统。视觉传感方式由于其采集信息量大，避免了与工件直接接触，易于实现焊接跟踪智能化，在焊缝跟踪领域得到广泛的应用。由于主动光视觉与被动光视觉相比具有抗干扰能力强等诸多优点，所以本文采用基于主动光视觉的焊缝跟踪系统。 论文第一部分介绍了焊缝跟踪图像采集与处理系统。对本文中所使用的图像传感器、光路系统的结构及获取特征点的图像处理方法进行了说明。 第二部分对焊缝跟踪控制系统的硬件设计进行说明。硬件部分主要是以TMS320F2812数字信号处理器为核心进行外围电路的设计。包括电源模块、串口通信模块、CAN口通信模块、接口电路模块等。为了使跟踪系统达到所需要的精度和快速性，电机是系统组成中一个非常重要的环节，是很关键的组成部件。所以本部分最后对伺服电机的选型过程进行详细说明。 第三部分介绍控制系统的软件结构。控制器软件系统包括初始化模块、串行通信模块、CAN通信模块、指令处理模块、纠偏控制模块等。针对超前检测式跟踪机构的特点，推导出超前偏差公式，实现纠偏控制模块的功能。 最后对控制方法进行仿真研究。针对焊缝跟踪系统的特点，应用MATLAB的Simulink模块进行控制方法的仿真研究。设计了PID控制器和模糊控制器，分别进行仿真研究，并且对仿真结果进行对比分析。

A hybrid power system for remote areas in Jordan

This paper presents a techno-economic assessment for a unique Isolated Hybrid Power System (IHPS) design for remote areas isolated from the grid which also has the capability of being operated as a smart μ-grid. The share of renewable energy sources in resource poor developing countries is low. In these countries an increase in the share of alternative energy (wind, water and sun) delivered with inexpensive operationally robust generation and delivery systems is seen to the way forward. In our design also incorporates a novel storage system to increase the effectiveness of the Isolated IHPSs previously reported in the literature. The configuration reported is a system consisting of, the wind and sun powered generation complemented with batteries, fuel cell unit and a diesel generator. The modelling design and simulations were based on Simulations conducted using MATLAB/SIMULINK, and HOMER Energy Planning and Design software tools. The design and simulation of a new storage approach incorporating Hydrogen Peroxide (H2O2) fuel cell (increasing the efficiency of the fuel cell from 35% to 65%) and a single board computer (Raspberry Pi) used for the energy management and control the system are the novel features of our design. The novel control strategy implemented also includes a synchronization capability that facilitates IHPS to IHPS or IHPS to Main-Grid connection. In the paper after briefly but comprehensively detailing the design and simulations we will present the results on which we conclude that smart independent systems that can utilize indigenous renewable energy with a capability of being able to synchronize with the grid or each other are the most optimal way of electrifying resource poor developing countries in a sustainable way with minimum impact on the environment and also achieve reductions in Green House Gases.

Sistemas fotovoltaicos este-oeste con capacidad de almacenamiento en la industria

El objetivo de este proyecto fin de carrera es ajustar el perfil generado por un sistema fotovoltaico con orientación este-oeste que dispone de una batería al perfil de demanda de distintas industrias en Alemania. Se ha puesto especial énfasis a los siguientes paquetes de trabajo: • Comparación de la eficiencia de un sistema fotovoltaico este-oeste frente a los resultados obtenidos con la típica orientación sur • Simulación de una instalación fotovoltaica este-oeste con una batería en una industria, basada en el software MATLAB / Simulink • Optimización económica. Los resultados obtenidos muestran que nunca es económico instalar un campo fotovoltaico este-oeste en vez de una instalación con orientación sur, en caso de que la única ventaja esperada sea el ensanche de la curva de generación de potencia.

Simulation of coupled heat and moisture transfer in air-conditioned buildings

The simultaneous heat and moisture transfer in the building envelope has an important influence on the indoor environment and the overall performance of buildings. In this paper, a model for predicting whole building heat and moisture transfer was presented. Both heat and moisture transfer in the building envelope and indoor air were simultaneously considered; their interactions were modeled. The coupled model takes into account most of the main hygrothermal effects in buildings. The coupled system model was implemented in MATLAB-Simulink, and validated by using a series of published testing tools. The new program was applied to investigate the moisture transfer effect on indoor air humidity and building energy consumption under different climates. The results show that the use of more detailed simulation routines can result in improvements to the building's design for energy optimisation through the choice of proper hygroscopic materials, which would not be indicated by simpler calculation techniques.

Coordinated Control of DFIG and FSIG-based Wind Farms under Unbalanced Grid Conditions

This paper investigates the control and operation of doubly-fed induction generator (DFIG) and fixed-speed induction generator (FSIG) based wind farms under unbalanced grid conditions. A DFIG system model suitable for analyzing unbalanced operation is developed, and used to assess the impact of an unbalanced supply on DFIG and FSIG operation. Unbalanced voltage at DFIG and FSIG terminals can cause unequal heating on the stator windings, extra mechanical stresses and output power fluctuations. These problems are particularly serious for the FSIG-based wind farm without a power electronic interface to the grid. To improve the stability of a wind energy system containing both DFIG and FSIG based wind farms during network unbalance, a control strategy of unbalanced voltage compensation by the DFIG systems is proposed. The DFIG system compensation ability and the impact of transmission network impedance are illustrated. The simulation results implemented in Matlab/Simulink show that the proposed DFIG control system improves not only its own performance, but also the stability of the FSIG system with the same grid connection point during network unbalance.

Development and Validation of a Forklift Truck Powertrain Simulation

Fuel economy has become an important consideration in forklift truck design, particularly in Europe. A simulation of the fuel consumption and performance of a forklift truck has been developed, validated and subsequently used to determine the energy consumed by individual powertrain components during drive cycles.
The truck used in this study has a rated lifting capacity of 2500kg, and is powered by a 2.6 litre naturally aspirated diesel engine with a fuel pump containing a mechanical variable-speed governor. The drivetrain consisted of a torque convertor, hydraulic clutch and single speed transmission.
AVL Cruise was used to simulate the vehicle powertrain, with coupled Mathworks Simulink models used to simulate the hydraulic and control systems and governor. The vehicle has been simulated on several performance and fuel consumption drive cycles with the main focus being the VDI 2198 fuel consumption drive cycle.
To validate the model, a truck was instrumented and measurements taken to compare the performance and instantaneous fuel consumption to simulated values. The fuel injector pump was modified and calibrated to enable instantaneous fuel flow to be measured.
The model has been validated to within acceptable limits and has been used to investigate the effect four different torque converters have on the fuel consumption and performance of the forklift truck. The study demonstrates how the model can be used to compare the fuel consumption and performance trade-offs when selecting drivetrain components.

Calculation of Critical Clearing Time of Embedded Generation for Relay Setting Based on Optimisation Method

his paper proposes an optimisation-based method to calculate the critical slip (speed) of dynamic stability and critical clearing time (CCT) of a self-excited induction generator (SEIG). A simple case study using the Matlab/Simulink environment has been included to exemplify the optimisation method. Relationships between terminal voltage, critical slip and reactance of transmission line, CCT and inertial constant have been determined, based on which analysis of impact on relaying setting has been further conducted for another simulation case.

Optimisation of Kinetic Parameters for an After-treatment Catalyst

Mathematical modelling has become an essential tool in the design of modern catalytic systems. Emissions legislation is becoming increasingly stringent, and so mathematical models of aftertreatment systems must become more accurate in order to provide confidence that a catalyst will convert pollutants over the required range of conditions. 
Automotive catalytic converter models contain several sub-models that represent processes such as mass and heat transfer, and the rates at which the reactions proceed on the surface of the precious metal. Of these sub-models, the prediction of the surface reaction rates is by far the most challenging due to the complexity of the reaction system and the large number of gas species involved. The reaction rate sub-model uses global reaction kinetics to describe the surface reaction rate of the gas species and is based on the Langmuir Hinshelwood equation further developed by Voltz et al. [1] The reactions can be modelled using the pre-exponential and activation energies of the Arrhenius equations and the inhibition terms. 
The reaction kinetic parameters of aftertreatment models are found from experimental data, where a measured light-off curve is compared against a predicted curve produced by a mathematical model. The kinetic parameters are usually manually tuned to minimize the error between the measured and predicted data. This process is most commonly long, laborious and prone to misinterpretation due to the large number of parameters and the risk of multiple sets of parameters giving acceptable fits. Moreover, the number of coefficients increases greatly with the number of reactions. Therefore, with the growing number of reactions, the task of manually tuning the coefficients is becoming increasingly challenging. 
In the presented work, the authors have developed and implemented a multi-objective genetic algorithm to automatically optimize reaction parameters in AxiSuite®, [2] a commercial aftertreatment model. The genetic algorithm was developed and expanded from the code presented by Michalewicz et al. [3] and was linked to AxiSuite using the Simulink add-on for Matlab. 
The default kinetic values stored within the AxiSuite model were used to generate a series of light-off curves under rich conditions for a number of gas species, including CO, NO, C_{3H8 and C3H6. These light-off curves were used to generate an objective function.} 
This objective function was used to generate a measure of fit for the kinetic parameters. The multi-objective genetic algorithm was subsequently used to search between specified limits to attempt to match the objective function. In total the pre-exponential factors and activation energies of ten reactions were simultaneously optimized. 
The results reported here demonstrate that, given accurate experimental data, the optimization algorithm is successful and robust in defining the correct kinetic parameters of a global kinetic model describing aftertreatment processes.