毕业设计外文翻译

北京化工大学北方学院毕业设计 论文 外文文献原稿和译文 1 外文文献原稿和译文外文文献原稿和译文 原原 稿稿 Introduction In the modern industrial control field along with the rapid development of computer technology the emergence of a new trend of intelligent control namely to machine simulation human thinking mode using reasoning deduce and induction so the means the production control this is artificial intelligence One expert system fuzzy logic and neural network is the artificial intelligence of several key research hot spot Relative to the expert system the fuzzy logic belongs to the category of computational mathematics and contain the genetic algorithm the chaos theory and linear theory etc it comprehensive of operators practice experience has the design is simple and easy to use strong anti interference ability and reaction speed easy to control and adaptive ability etc In recent years in a process control built to touch estimation identify diagnosis the stock market forecast agricultural production and military sciences to a wide range of applications To carry out in depth research and application of fuzzy control technology the paper introduces the basic theory of fuzzy control technology and development and to some in the application of the power electronics are introduced Fuzzy Logic and Fuzzy Control 1 fuzzy logic and fuzzy control concept In 1965 the university of California Berkeley computer experts Lofty Zadeh put forward fuzzy logic concept the root lies in the area s logic or clear logic distribution used to define the confused unable to quantify or the problem of precision for in a man s von based on true false reasoning mechanism and thus create a electronic circuit and integrated circuit of the Boolean algorithm fuzzy logic to fill the gaps in special things in sampling and analysis of blank On the basis of fuzzy logic fuzzy set theory a particular things as the set of features membership he can be in is and no within the scope of the take between any value And fuzzy logic is reasonable quantitative mathematical theory the mathematical basis for 北京化工大学北方学院毕业设计 论文 外文文献原稿和译文 2 fundamental for is to deal with these the statistical uncertain imprecise information Fuzzy control based on fuzzy logic is a process of description of the control algorithm For parameters precisely known mathematical model we can use Berd graph or chart to analysts the Nyquist process to obtain the accurate design parameters And for some complex system such as particle reaction meteorological forecast equipment establishing a reasonable and accurate mathematical model is very difficult and for power transmission speed of vector control problems although it can be measured by the model that but for many variables and nonlinear variation the accurate control is very difficult And fuzzy control technology only on the basis of the practical experience and the operator and intuitive inference also relies on design personnel and research and development personnel of experience and knowledge accumulation it does not need to establish equipment model so basically is adaptive and have strong robustness After many years development there have been many successful application of the fuzzy control theory of the case such as Rutherford Carter and Ostergaard were applied and metallurgical furnace and heat exchangers control device 2 the analysis method is discussed Industrial control stability of the system is discussed the premise of the problem because of the nonlinear and not to the unity of the description make a judgment so the fuzzy control system analysis method of stability analysis has been a hot spot comprehensive in recent years you of scholars paper published the system stability analysis has these several circumstances 1 LiPuYa panov method direct method based on the discrete time D T and continuous time fuzzy control stability analysis and design method the stability condition of the relative comparison conservative 2 sliding variable structure system analysis method 3 round stability criterion methods use sector bounded nonlinear concept according to the stability criterion led to the stability of the fuzzy control 4 POPOV criterion 5 other methods such as relationship matrix analysis exceed stable theory phase plane matrix inequality or convex optimization method fuzzy hole hole 北京化工大学北方学院毕业设计 论文 外文文献原稿和译文 3 mapping etc detailed information and relevant literature many in this one no longer etc Set Design of Fuzzy Control The design of the fuzzy control is a very complicated process in general take the design steps and tools is more normative The fuzzy controller general use of the special software and hardware universal hardware chip in on the market at present is more including main products are shown below And special IC has developed very fast it special IC and software controller integrates in together In the process of design the design of the general to take steps for 1 considering whether the subject by fuzzy control system That is considered the routine control mode of may 2 from equipment operation personnel place to get as much information 3 and selecting the mathematical model could if use the conventional method design estimate the equipment performance characteristics 4 determine the fuzzy logic control object 5 determine the input and output variables 6 determine the variables as determined the belonging of the range 7 confirm the variables of the corresponding rules 8 determine the scale coefficients 9 if have a ready made mathematical model of fuzzy controller with already certain of system simulation observation equipment performance and constantly adjust rules and scale coefficients until reaching satisfaction performance Or to design fuzzy controller 10 real time operation controller constantly adjust to the best performance Fuzzy Control Application and Prospect As artificial intelligence of a new research field the fuzzy control absorb lessons from the traditional design method and other new technology s essence in many fields has made considerable progress In the new type of power electronic and automatic control system some experts in the linear adding the conditions of the power amplifier the application of the fuzzy control based on the servo motor control in the fuzzy control system with the PID and model reference adaptive control MRAC 北京化工大学北方学院毕业设计 论文 外文文献原稿和译文 4 comparison proved the advantages of the method of fuzzy control Fuzzy turn sent gain tuned controller views of the induction motor drive system vector control Fuzzy control as a is the development of new technology now in most experts also to focus on application system research and make considerable achievement but in the theory research and system analysis or relative backward so much so that some scholars have questioned its theoretical basis and effective In view of this can be clear that the fuzzy control the combination of theory and practice is still needs to be further explored The development prospects are very attractive and in recent years its theoretical study also made significant progress In the past forty years of the development process the fuzzy control also has some limitations 1 control precision low performance is not high stability is poorer 2 theory system is not complete 3 the adaptive ability low For these weaknesses the fuzzy control and some other new technology such as neural network NN genetic algorithm and the combination of to a higher level of application development expand the huge space Summary Fuzzy control as a comprehensive application example in the global information the push of wave in the next few decades to the rapid development of economy will inject new vitality the expert thinks the next generation of industrial control is the basis of fuzzy control and neural network and chaos theory as the pillar of the artificial intelligence With the fuzzy control theory research and further more perfect of the scope of application of the growing and supporting the development and manufacture of IC the fuzzy control will be open to the field of industrial automation development of light application prospect but also to the various areas of the researchers suggest more important task 北京化工大学北方学院毕业设计 论文 外文文献原稿和译文 5 译译 文文 引言引言 在现代工业控制领域 伴随着计算机技术的突飞猛进 出现了智能控制的 新趋势 即以机器模拟人类思维模式 采用推理 演绎和归纳等手段 进行生 产控制 这就是人工智能 其中专家系统逻辑和神经网络是人工智能的几个重 点研究热点 相对于专家系统 模糊逻辑属于计算数 模糊学的范畴 包含遗 传算法 混沌理论及线性理论等内容 它综合了操作人员的实践经验 具有设 计简单 易于应用 抗干扰能力强 反应速度快 便于控制和自适应能力强等 优点 近年来 在过程控制 建摸 估计 辩识 诊断 股市预测 农业生产 和军事科学等领域得到了广泛应用 为深入开展模糊控制技术的研究应用 本 文综合介绍了模糊控制技术的基本理论和发展状况 并对一些在电力电子领域 的应用作了简单介绍 模糊逻辑与模糊控制模糊逻辑与模糊控制 1 模糊逻辑与模糊控制的概念 1965 年 加州大学伯克利分校的计算机专家 Lofty Zadeh 提出 模糊逻辑 的概念 其根本在于区分布尔逻辑或清晰逻辑 用来定义那些含混不清 无法 量化或精确化的问题 对于冯 诺依曼开创的基于 真 假 推理机制 以及 因此开创的电子电路和集成电路的布尔算法 模糊逻辑填补了特殊事物在取样 分析方面的空白 在模糊逻辑为基础的模糊集合理论中 某特定事物具有特色 集的隶属度 他可以在 是 和 非 之间的范围内取任何值 而模糊逻辑是 合理的量化数学理论 是以数学基础为为根本去处理这些非统计不确定的不精 确信息 模糊控制是基于模糊逻辑描述的一个过程的控制算法 对于参数精确已知 的数学模型 我们可以用 Berd 图或者 Nyquist 图来分析家其过程以获得精确的 设计参数 而对一些复杂系统 如粒子反应 气象预报等设备 建立一个合理 而精确的数学模型是非常困难的 对于电力传动中的变速矢量控制问题 尽管 可以通过测量得知其模型 但对于多变量的且非线性变化 起精确控制也是非 常困难的 而模糊控制技术仅依据与操作者的实践经验和直观推断 也依靠设 计人员和研发人员的经验和知识积累 它不需要建立设备模型 因此基本上是 自适应的 具有很强的鲁棒性 历经多年发展 已有许多成功应用模糊控制理 北京化工大学北方学院毕业设计 论文 外文文献原稿和译文 6 论的案例 如 Rutherford Carter 和 Ostergaard 分别应用与冶金炉和热交换 器的控制装置 2 分析方法探讨 工业控制系统的稳定性是探讨问题的前提 由于难以对非线性和不统一的 描述 做出判断 因此模糊控制系统的分析方法的稳定性分析一直是一个热点 综合近年来各位学者的发表的论文 目前系统稳定性分析有以下集中 1 李普亚诺夫法 基于直接法的离散时间 D T 和连续时间模糊控制的稳 定性分析和设计方法 相对而言起稳定条件比价保守 2 滑动变结构系统分析法 3 圆稳定性判据方法 利用扇区有界非线性概念 根据稳定判据可推导模糊 控制的稳定性 4 POPOV 判据 5 其他方法如关系矩阵分析法 超稳定理论 相平面法 矩阵不等式或凸 优化法 模糊穴穴映射等 详细资料及有关文献很多 在这里不再一一阐述 模糊控制的设置设计模糊控制的设置设计 模糊控