模糊控制毕业论文

模糊控制考核论文姓名：郑鑫 学号：1409814011 班级：1496411题目:模糊控制的理论与发展概述摘要 模糊控制理论是以模糊数学为基础,用语言规则表示方法和先进的计算机技术,由模糊推理进行决策的一种高级控制策。模糊控制作为以模糊集合论、模糊语言变量及模糊逻辑推理为基础的一种计算机数字控制，它已成为目前实现智能控制的一种重要而又有效的形式尤其是模糊控制和神经网络、遗传算法及混沌理论等新学科的融合，正在显示出其巨大的应用潜力。实质上模糊控制是一种非线性控制，从属于智能控制的范畴。模糊控制的一大特点是既具有系统化的理论，又有着大量实际应用背景。本文简单介绍了模糊控制的概念及应用，详细介绍了模糊控制器的设计，其中包含模糊控制系统的原理、模糊控制器的分类及其设计元素。关键词：模糊控制；模糊控制器；现状及展望Abstract Fuzzy control theory is based on fuzzy mathematics, using language rule representation and advanced computer technology, it is a high-level control strategy which can make decision by the fuzzy reasoning. Fuzzy control is a computer numerical contro which based fuzzy set theory, fuzzy linguistic variables and fuzzy logic, it has become the effective form of intelligent control especially in the form of fuzzy control and neural networks, genetic algorithms and chaos theory and other new integration of disciplines, which is showing its great potential. Fuzzy control is essentially a nonlinear control, and subordinates intelligent control areas. A major feature of fuzzy control is both a systematic theory and a large number of the application background.This article introduces simply the concept and application of fuzzy control and introduces detailly the design of the fuzzy controller. It contains the principles of fuzzy control system, the classification of fuzzy controller and its design elements.Key words: Fuzzy Control; Fuzzy Controller; Status and Prospects.引言传统的常规 PID 控制方式是根据被控制对象的数学模型建立，虽然它的控制精度可以很高，但对于多变量且具有强耦合性的时变系统表现出很大的误差。比例调节是根据被调量和设定值之间的差值来变化的，也就是说比例控制中余差不可避免。积分调节最终实现无余差调节，但是超调比较大。模糊控制是建立在人工经验基础之上的,它能将熟练操作员的实践经验加以总结和描述,并用语言表达出来,得到定性的、精确的控制规则,不需要被控对象的数学模型。并且模糊控制易于被人们接受,构造容易,适应性好。The introductionTraditional way of conventional PID control was established according to the mathematical 模糊控制考核论文姓名：郑鑫 学号：1409814011 班级：1496412model of controlled object, although it can be very high control precision, but for the multi-variable1and time-varying systems with strong coupling showed great error. Proportional control is based on the difference in value between set value and quantity of the modulated to change, that is to say, proportional control of residual is inevitable. Integral regulation achieve everything in a glance at poor regulation, but the overshoot is bigger. Fuzzy control is based on the artificial experience, it can skilled operators practical experience summarized and described, and the language expression, get a qualitative, precise control rules, not need mathematical model of controlled object. And fuzzy control is easy to be accepted by people, easy structure, good adaptability.第一章 模糊控制概述1.1模糊控制的概念及应用“模糊”是人类感知万物,获取知识,思维推理,决策实施的重要特征。“模糊”比“清晰”所拥有的信息容量更大,内涵更丰富,更符合客观世界。模糊逻辑控制(Fuzzy Logic Control)简称模糊控制(Fuzzy Control)，是以模糊集合论、模糊语言变量和模糊逻辑推理为基础的一种计算机数字控制技术。模糊控制理论是由美国著名的学者加利福尼亚大学教授 ZadehLA 于 1965 年首先提出,它是以模糊数学为基础,用语言规则表示方法和先进的计算机技术,由模糊推理进行决策的一种高级控制策。在 19681973 年期间ZadehLA 先后提出语言变量、模糊条件语句和模糊算法等概念和方法，使得某些以往只能用自然语言的条件语句形式描述的手动控制规则可采用模糊条件语句形式来描述，从而使这些规则成为在计算机上可以实现的算法。1974 年,英国伦敦大学教授 MamdaniEH 研制成功第一个模糊控制器, 并把它应用于锅炉和蒸汽机的控制，在实验室获得成功。这一开拓性的工作标志着模糊控制论的诞生并充分展示了模糊技术的应用前景。模糊控制实质上是一种非线性控制，从属于智能控制的范畴。模糊控制的一大特点是既具有系统化的理论，又有着大量实际应用背景。模糊控制的发展最初在西方遇到了较大的阻力；然而在东方尤其是在日本，却得到了迅速而广泛的推广应用。其典型应用的例子涉及生产和生活的许多方面， 以下为模糊控制在工业和生活方面的一些应用实例：1 净水场药品注人控制、上下水道处理系统2 各种溶沪： 电气炉 水泥生成炉的控翻、原子能发电供水控制、金属板成形控制3 城市垃圾焚烧炉的控制24 随道盾构机械、油压掘进机械、集装箱吊装的控制5 高速公路隧道的排气、换气控制6 汽车的定速行走控制、发动机的控制、模糊 AT 、自动观光船7 飞机离着陆控制、直升飞机控制、海上救难船控制8 机器人的控制： 扫除机械人、花道机械人、激光切割机器人、钓鱼机器人、9 升降机群管理、自动枪票机、自动门开关装置、自动贩卖机10 空调控制制冷 、制热机、多路空调系统、铁道车辆、11 造纸机、清酒酿造控制12 自动声音调整器、传感器位置选择13 电视会议系统、簇像机、电子喷水器、录像机、照像机、复印机、绘图机14 家电制品: 洗衣机、吸尘器、干澡机、冷藏箱、电子微波炉,电饭锅、电动剃须刀、1.2模糊控制的优点 1 简化系统设计的复杂性，特别适用于非线性、时变、模型不完全的系统上。 2 利用控制法则来描述系统变量间的关系。 3 不用数值而用语言式的模糊变量来描述系统，模糊控制器不必对被控制对象建立完整的数学模式。 4 模糊控制器是一语言控制器，使得操作人员易于使用自然语言进行人机对话。 5 模糊控制器是一种容易控制、掌握的较理想的非线性控制器，并且抗干扰能力强，响应速度快，并对系统参数的变化有较强的鲁棒性和较佳的容错性。 36 从属于智能控制的范畴。该系统尤其适于非线性，时变，滞后系统的控制。1.3模糊控制的缺点 1 模糊控制的设计尚缺乏系统性，这对复杂系统的控制是难以奏效的。所以如何建立一套系统的模糊控制理论，以解决模糊控制的机理、稳定性分析、系统化设计方法等一系列问题； 2 如何获得模糊规则及隶属函数即系统的设计办法，这在目前完全凭经验进行； 3 信息简单的模糊处理将导致系统的控制精度降低和动态品质变差。若要提高精度则必然增加量化级数，从而导致规则搜索范围扩大，降低决策速度，甚至不能实时控制； 4.如何保证模糊控制系统的稳定性即如何解决模糊控制中关于稳定性和鲁棒性问题还有待完善。The first chapter is summary of fuzzy control1.1 the concept and application of fuzzy control“Fuzzy“ human perception is everything, to acquire knowledge, thinking, reasoning, decision-making of important features. “Fuzzy“ than “clear“ have the information capacity of a larger, more abundant connotation, more in line with the objective world. Fuzzy Logic Control (Fuzzy Logic Control) referred to as “Fuzzy Control (Fuzzy Control), based on the Fuzzy set theory, Fuzzy language variable and Fuzzy Logic reasoning is the basis of a computer numerical Control technology. Fuzzy control theory is by the famous scholar at the university of California professor Zadeh, l. a. first proposed in 1965, it is based on fuzzy mathematics, expressed in the language rules method and advanced computer technology, by the fuzzy reasoning to make decisions of an advanced control strategy. During the period of 1968 1973, Zadeh, l. a. successively proposed language variable, fuzzy algorithm and the fuzzy conditional statement concepts and methods, make some of the past can only use natural language form of conditional statements describe the manual control rules can be used to describe fuzzy conditional statement form, so as to make these rules can be implemented on computer algorithm. In 1974, a professor at the university of London Mamdani, E, H, successfully developed the first fuzzy controller and apply it to the boiler and the control of the steam engine, to succeed in the laboratory. This pioneering work marks the birth of the fuzzy control theory and fully shows the application prospect of fuzzy technology.Fuzzy control is essentially a kind of nonlinear control, from belongs to the category of intelligent control. Fuzzy control is one of the biggest characteristic is both a systematic theory, and with a large number of practical application background. The development of fuzzy control is first encountered in the west the larger resistance; In the east, especially in Japan, however, has obtained the rapid and extensive popularization and application. Its typical application example involves many aspects of production and life, the following is some applications of fuzzy control in the aspect of industrial and living example:41 Drug injection water purification field population control, sewage treatment system2 All kinds of soluble Shanghai: cement generated in electric furnace control turn, nuclear power generation, water supply, sheet metal forming control3 Control of urban garbage incinerator4 The tunnel shield machine, hydraulic excavating machinery, container lifting control5 Exhaust and ventilation control of highway tunnel6 In constant speed control, automotive engine control, automatic fuzzy ats, sightseeing boats7 Aircraft, helicopters from landing control control, maritime rescue boat8 The robots control: cleaning robots, ikebana robots, fishing, laser cutting machine,9 Lift the fleet management, gun ticket machine, automatic switching device, automatic vending machines10 Refrigeration and air conditioning control system of engine, multi-channel air conditioning system, railway vehicle,11 Paper machine, wine brewing control512 Automatic sound regulator, sensor location choice13 Video conference system, cluster like machine, electronic sprinkler, VCR, camera, copy machine, drawing machine14 Home appliances products: washing machines, vacuum cleaners, dry bath machine, cooler, electronic oven, electric rice cooker, electric razor1.2 the advantages of fuzzy control1 to simplify the complexity of system design, especially for nonlinear, time-varying and model incomplete system.2 control law is used to describe the relationship between the system variables.3 language instead of numerical type of fuzzy variables to describe the system, the fuzzy controller dont need to establish a comprehensive mathematical model of controlled object.4 controller, fuzzy controller is a language that operators easy to use natural language for the man-machine dialogue.5 fuzzy controller is a kind of easy to control and mastery of the ideal nonlinear controller, and strong anti-jamming capability, fast response speed, and the change of system parameters has strong robustness and better fault tolerance.6 from belongs to the category of intelligent control. This system is especially suitable for nonlinear, time varying and lag control system.1.3 the disadvantage of fuzzy control1 the design of the fuzzy control is still lack of systematic, the control of complex systems is difficult to work. So how to establish a system of fuzzy control theory, in order to solve fuzzy control mechanism, stability analysis, systematic design method for a series of problems;2 how to obtain fuzzy rules and membership functions, system design, complete with experience for this in the present;3 simple fuzzy information processing will reduce control precision of the system and the dynamic quality becomes poor. If you want to improve the accuracy of inevitable to increase 6the quantitative series, leading to rule search scope, reduce the decision-making speed, cant even real-time control;4. How to ensure the stability of the fuzzy control system is how to solve the fuzzy control on the stability and robustness problems remains to be perfect.第二章 模糊控制器的设计2.1 模糊控制系统的原理模糊控制作为以模糊集合论、模糊语言变量及模糊逻辑推理为基础的一种计算机数字控制，它已成为目前实现智能控制的一种重要而又有效的形式尤其是模糊控制和神经网络、遗传算法及混沌理论等新学科的融合，正在显示出其巨大的应用潜力。控制规律 执行机构 被控对象传感器给定量图 1 常见负反馈控制系统方框图由测量装置、控制器、被控对象及执行机构组成的自动控制系统，就是人们所悉知的常规负反馈控制系统。其结构如图 1 所示。然而经过人们长期研究和实践形成的经典控制理论，虽然对于解决线性定常系统的控制问题非常有效。随着计算机尤其是微机的发展和应用，基于由于式中 模糊量，所以为了对被控对象施加精确的控制，还需要将其清晰化转换为精确量 u，然后经 D/A 得模拟量送给执行机构，对被对象进行第一步控制。然后中断等待第二次采样，进行第二步控制.这样循环下去就实现了对被控对象的模糊控制。2.2模糊控制器的基本结构模糊控制器的基本结构包括知识库、模糊推理、输入量模糊化、输出量精确化四部分。71.知识库 知识库包括模糊控制器参数库和模糊控制规则库。模糊控制规则建立在语言变量的基础上。语言变量取值为“大”、“中”、“小”等这样的模糊子集,各模糊子集以隶属函数表明基本论域上的精确值属于该模糊子集的程度。因此,为建立模糊控制规则,需要将基本论域上的精确值依据隶属函数归并到各模糊子集中,从而用语言变量值(大、中、小等)代替精确值。这个过程代表了人在控制过程中对观察到的变量和控制量的模糊划分。由于各变量取值范围各异,故首先将各基本论域分别以不同的对应关系,映射到一个标准化论域上。通常,对应关系取为量化因子。为便于处理,将标准论域等分离散化,然后对论域进行模糊划分,定义模糊子集,如 NB、PZ、PS 等。 同一个模糊控制规则库,对基本论域的模糊划分不同,控制效果也不同。具体来说,对应关系、标准论域、模糊子集数以及各模糊子集的隶属函数都对控制效果有很大影响。这 3 类参数与模糊控制规则具有同样的重要性,因此把它们归并为模糊控制器的参数库,与模糊控制规则库共同组成知识库。 2.模糊化 将精确的输入量转化为模糊量 F 有两种方法: (1)将精确量转换为标准论域上的模糊单点集。精确量 x 经对应关系 G 转换为标准论域 x 上的基本元素,则该元素的模糊单点集 F 为 uF(u)=1 if u=G(x) (2)将精确量转换为标准论域上的模糊子集。 精确量经对应关系转换为标准论域上的基本元素,在该元素上具有最大隶属度的模糊子集,即为该精确量对应的模糊子集。 3.模糊推理 最基本的模糊推理形式为: 前提 1 IF A T