外文翻译毕业论文

1、毕业论文（设计）外文翻译题 目： 电气工程毕业生使用MATLAB最优控制的过程 系部名称： 专业班级： 学生姓名： 学 号： 指导教师： 教师职称： 讲师 20 年月日电气工程毕业生使用MATLAB最优控制的过程 Asad Azemi 宾州法尼亚州大学大峡谷分校 电气工程系 莫尔文 PA 193551443 Edwin Engin Yaz 美国阿肯色州大学费耶特维尔校区 电气工程系 AR 72701摘要控制程序设计包，比如矩阵实验室MATLAB、矩阵模型、C语言控制系统、数学非线性现象的语言程序系统等等，已经变成了大学生和研究生系统课程和控制领域的重要材料。这些设计包记述了我们的经验，宾夕法尼

2、亚大学大峡谷分校和美国阿肯色州大学的最优控制课程就是利用这些设计包，也就是MATLAB，和它的控制系统，鲁棒控制和线性矩阵不等式工具箱。这篇论文我们描述适用于最优控制课程的MATLAB和它的控制系统工具箱的基本作用，然后我们将集中于MATLAB的特点，产生交互式仿真和用户界面控制。在交互式仿真指导书的帮助下能有效的阐明因为参数的变更系统响应的变化，也包括用一些例子阐明这些特点。讨论MATLAB怎样帮助减少计算作业分配的时间，接着是介绍如何使用图形用户界面，最后记录学生的积极反应。 简介 宾夕法尼亚大学的电气工程部门和阿肯色大学是以计算机辅助教育，所以计算机辅助设计包进入了他们的课程。这些课程增

3、加这些设计包的目的是通过实习和设计的经验提高学生对理论知识的理解能力。计算机辅助课程和计算机辅助设计包之前已经被它的制作者和他的同事们试用。这些软件不仅在大学里使用同时也被确认为新的教科书，而且以这些软件为基础修正了以前教科书上的习题和问题。合并这些程序包的优点和缺点以及它的概要也进入我们的课程，将在我们下面的文章里讲述。在每个院校使用的设计包里每个节段的提纲后面是概要，下面的课程是我们总结的它的优点和缺点。 基本优点使用这些工具的主要优点是：通过增加图形和交互仿真加强学生对理论知识的理解，可以用笔和纸分析更复杂的系统，如果没有类似的软件的帮助老师想能够指导相当复杂的问题也是不现实的。学生反映

4、关于使用这些设计包基本是有利的，许多计算机辅助设计包也是值得一提的，比如MATLAB，不再局限于某一特定的归档，早点使用这些设计包对学生有好处，为了更详细的了解它的优点读者可以参阅我们以前的文章。 基本缺点 使用这些程序设计包的三个缺点是：使用这些程序设计包计算机容易受影响，而且还要求学生或者老师学会如何使用这些计算机辅助程序设计包，并保证这些包括基准线课程的设计包作为必修课程的一部分，更多详细关于它的缺点的讨论可以参阅我们前部分章节的内容。 宾州法尼亚大学大峡谷分校的最有控制系统宾州法尼亚大学大峡谷校园是宾州法尼亚大学十八个校园的其中之一，是在费城区域的一个研究生中心，工程师们在那里工作来满

5、足教育的需求，利用各种各样的仿真设计包几乎所有的学生都变成了工程师。这些课程的目的是让学生的数学工具参数化，动态最优化，并且用于设计表现最好的动力系统。非线性系统课程包含下面的课题：1、 静态最佳化2、 离散系统的时间最优控制 2.1 线性二次调节器 2.2 次优反馈的稳态闭环控制系统 2.3 跟踪问题 2.4最终状态固定的调节阀与功能3、 最优控制的连续系统 3.1 线性二次调节器 3.2 次优反馈的稳态闭环控制系统 3.3 跟踪问题 3.4 最终状态固定的调节阀与功能 3.5 最终时间释放问题 3.6 约束输入问题4、动态规划 4.1 离散时间 学生每周的作业包括计算机的仿真和使用，考试部

6、分也包括用计算机仿真的作业，学生可以使用学生版本的MATLAB。 阿肯色州大学最优控制系统 本课程提供给本科生和研究所的学生，让他们为研究经典的状态空间控制技术做好充分准备。这些课程的目的是让学生的数学工具参数化，动态最优化，而且用于设计最好的动力系统。为实现这一目标，作者（E.Yaz）从1986年开始更新课程，从而下面的提纲代表性的总结了一学期的课程：1、 无约束和约束优化问题。（一课时）2、 成本函数和参数优化。（二课时）3、 最优充分必要条件。（三课时）4、 连续和离散时间的动态规划。（四课时）5、 最小值原理。（一课时）6、 最小值原理的应用。（三课时）7、 数值技术。（二课时）8、

7、连续和离散时间二次调节阀和它的变体。（六课时）9、 线性二次型跟踪和抑制扰动。（二课时）10、 线性二次调节阀的稳健型。（二课时）11、 介绍保成本，H方程和线性矩阵不等式的方法。（三课时）12、 暴露分析模拟系统。（二课时） 我们一课时通常要讲80分钟，给出两个典型的分类，其余分级根据每周布置的作业及每班学生作业的改正意见，每学期收集两次，第一次在每学期中，第二次在每学期末，来衡量学生综合的理解能力。家庭作业的解决方法主要利用MATLAB软件及其它的工具箱，它多年来被推荐为指定教材及参考书。学生根据普渡大学自助餐厅学生制定的评价标准和由E.Yaz提出的非正式书面反馈得到的结论。 利用MATL

8、AB实现系统最优控制的过程 基于上述课程纲要，MATLAB是我们发现的在课堂上最有用的工具，这部分我们将介绍它的特点。MATLAB和它的控制系统以及强健控制工具箱是理想的求解线性二次方程的调节器（H2控制）和H方程的控制问题。“lqr”指令在程序中用来解决线性二次方程问题，它的语法指令是： k,p,ev=lqr(A,B,Q,R,N) (1)K是最佳增益，p是方程式的结果，ev是最佳闭环特征值。A、B、Q、R、N分别是系统矩阵的输入矩阵、描述权重矩阵、控制权重矩阵、描述交叉的权重矩阵和二次方程线性指标的控制矩阵。一般形式的代数Katie方程可以用这个语句命令解决： X=are(A,B,C) (2

9、)当和，而且，常量增益反馈的应用程序，通过波特图可以看出导出的系统函数为递减函数。另外，奈奎斯特图(“nyquist (A, B, C, D)” )被滤波器的单输入系统导出。为了选择特殊的权重矩阵 和, (3)引出了哈密顿矩阵 （4）闭环系统特征值就是H的稳定特征值。自从H的特征多项式可以放入参量的根轨迹里，通过根轨迹图形(“rlocus”)可以控制闭环极点位置。由命令“are”的卡蒂方程有助于解决在最坏的或者“极大极小”的情况下标准状态反馈H的控制问题。在其他稳健设计最优控制系统里 （5）当 ，通常无穷大的二次方程的成本标准的最小值导出相同类型的H型代数方程式。最近，使用MATLAB的线性矩

10、阵不等式工具箱可以求出一些不可能追溯性分析的问题的近似解。多状态植物能量的最小的一个上限就是一个随机的例子 （6）当i 的取值范围为1至N。在运算时用连续的线性化控制非线性系统会导致这样的问题，尽管没有分析解决的方案，线性矩阵不等式允许解决凸优化的线性问题。 用MATLAB编写交互式模拟仿真MATLAB也能制造互动式模拟仿真，用几何图形仿真可以加强课堂讲解的品质。在互动模拟课程的帮助下能有效的说明因为参数变化而引起的系统响应的变化，这可以帮助学生更好的理解自己的课程，而且由于不需要学生自己编程序，也是的学生不受限制，即使不知道MATLAB的程序设计语言也能通过较少的时间了解它的特点。这个特点对

11、交互式数学软件的发展起重要作用。在图形用户界面功能的帮助下产生交互式模拟仿真，图形用户界面由图形对象组成，比如菜单、按钮、列表和区域，这些对象都是有意义的。当一个用户选择一个对象，他就期望有特定的行为发生。在MATLAB的环境下，使用用户界面控制图形用户界面。图一展示了最终例行程序状态下的用户界面最低管制能源标量系统的应用。系统模型和性能指标被下式给出 （7）当和分别表示状态和控制输入，r是正的权重标量因子。这个方程式将产生状态和最优相对于时间的图形，滑动器允许用户改变系统参数来观察结果的变化。图二说明在一个离散的固定在最终状态的线性二次方程的调节器下使用用户界面控制。系统模型和性能指标被下式

12、给出 （8） 下面是最优控制方程 被给出 被给出系统参数在连续的时间里被规定而且因为在采样周期被分离，程序能产生输出后的图形控制最佳输入和次优调节器。T的数值和最终时间可以通过滑动条改变。按钮A、B、和C允许用户改变系统参数，系统按钮在连续和离散时间里采样周期，复制系统的极点和最终时间。重启按钮根据参数的变化更新极点。尽管图形用户界面对观察因为参数变化引起系统相应的变化很有用，但是这个阶段很耗费时间而且需要掌握很深的关于MATLAB的知识。 结论在这篇论文里我们已经提出了在宾夕法尼亚大学和阿肯色州大学的毕业生课程里使用了MATLAB和它的附属工具箱。计算机仿真包提供了好多的好处，比如MATLA

13、B，它能增强我们对理论原理的理解，完成更多的更复杂的设计，增加学生的注意力，提高专业的发展。使用计算机仿真包的主要缺点是学生和老师需要额外的学习在容易受影响的计算机上维护和操作这些程序设计包并确保这些设计包进入我们的基础课程作为必修课程资料的一部分。在宾夕法尼亚大学里由于学生的背景各不相同，一些学生刚开始不会使用MATLAB，这就使得他们无法完成他们全部的作业，用户界面控制按钮会减少这样的问题，但同时也会增加老师的负担。大部分的学生反映使用MATLAB给他们起到了很积极的作用。 参考文献 1马丁,T.W.,Azemi,王勇智教授,Hewett大学电气工程专业施耐德,“PSpice电气工程实验室

14、ASEE周年研讨会,1992年,高等教育出版社,第1307-1308页。2安德鲁斯博士,Azmi,A.,查尔顿,S.,Yaz E.,“电气工程专业在仿真技术教育”方面的ASEE Gulf-Southwest节研讨会会议,1994年,第82页。3Azemi, A., Yaz, E.,“本科生非线性系统分析课程利用SIMULINK仿真和MATLAB软件”第26届教育会议前沿,第一卷,1996年,高等教育出版社，595-599页，美国犹他州盐湖城。4Azemi, A., Stook, C.,“本科用MATLAB计算电路课程,”第26届教育会议前沿,第一卷，1996年,第599-603页,美国犹他州盐

15、湖城。5Yaz, E., Azemi, A.,“利用MATLAB在电力工程两门研究生课程”第25次边界教育会议，第2c6.1-2c6.4页,1995年。6Dorf, R., Bishop, R.H. 现代控制系统,第七版译,联经出版事业出版社,1995年。7Saadat, H.使用MATLAB控制系统计算。麦格劳希尔集团，1993年。8Strum, R., Kirk, D.现代线性系统使用MATLAB。PWS出版公司。1994。9Franklin, G., Powell, J., Workman, M.数字控制动态系统。Addison-Wesley出版社,1990年。10Biship, R.H

16、.现代控制系统使用MATLAB和SIMULINK仿真分析和设计。清华大学出版社,199711Hanselman, D.C., Kuo, B.C.MATLAB工具在控制系统的分析和设计。Prentice Hall出版社，(第二版),1995年。12 Owens, D.H.多变量和最优系统。学术出版社:伦敦,1981年。13Boyd, S., et. al.线性矩阵不等式的体制和控制原理。暹罗:费城,宾夕法尼亚州,1994年。本文摘译自This paper appears in: Frontiers in Education Conference, 1997. 27th Annual Confer

17、ence. Teaching and Learning in an Era of Change. Proceedings.Issue Date:5-8 Nov 1997On page(s):13 - 17 vol.1Meeting Date:05 十一月 1997 - 08 十一月 1997Location: Pittsburgh, PA , USAPrint ISBN: 0-7803-4086-8References Cited:24INSPEC Accession Number:5781557Digital Object Identifier: 10.1109/FIE.1997.64480

18、1 Date of Current Version: 06 八月 2002Using MATLAB in a Graduate Electrical Engineering Optimal Control CourseAsad Azemi Edwin Engin YazDepartment of Electrical Engineering Department of Electrical EngineeringPenn State University University of ArkansasGreat Valley Campus Fayetteville, AR 72701Malver

19、n, PA 19355-1443Abstract - Control system design packages like MATLAB,MATRIXX, Control C, SIMNON, etc. have become essential ingredients of both undergraduate and graduate courses in the systems and controls area. This work describes our experience, at the Great Valley Campus of the Pennsylvania Sta

20、te University and the University of Arkansas, with the use of one of these packages, namely MATLAB with its Control Systems, Robust Control and LMI toolboxes in an optimal control course. In this paper we will describe those standard functions of MATLAB and Control Systems Toolbox that are most appr

21、opriate for use in an optimal control course. Next, we will focus on some special features of MATLAB that can be used to produce interactive simulations, using user interface controls. With the help of interactive simulations instructors caneffectively illustrate the change in system response due to

22、 parameter variations. Examples illustrating these features are included. A discussion of how MATLAB helps in reducing the amount of time spent in performing computational homework assignments and the advantages of using graphics user interface control will follow. Finally, the general positive stud

23、ent reaction will be reported. IntroductionThe Electrical and Engineering Departments at Penn State University and the University of Arkansas are incorporating computer aided engineering (CAE) and computer aided design (CAD) packages into their curricula. The intent of augmenting the curriculum with

24、 these packages is to enhance the students theoretical understanding of thematerial with hands on analysis and design experience. The benefits of CAE and CAD packages in the classroom have been realized by the authors and their co-workers before 1-6. The benefits of using these packages in a univers

25、ity setting is also confirmed by the number of new textbooks, and revisions of previously printed textbooks incorporating new exercises and problems based on these packages, such as 7-15. A summary of the advantages and disadvantages of incorporating these packages into our graduate curricula are pr

26、esented below. The summary is followed by sections outlining the use of each package in each institution. A summary of the advantages and disadvantages of incorporating these packages into our curriculum are presented below. General AdvantagesThe main advantages of using these tools are: the reinfor

27、cement of student understanding of theoretical principles by means of enhanced graphical aids and interactive simulations, analysis of more complex systems that can be treated by pencil and paper, and the instructors ability to assign fairly complex design problems that otherwise would have be unrea

28、listic without the help of such software. Student response concerning the use of these packages is generally favorable. It is also worth mentioning that the use of many CAE packages, such as MATLAB16, are no longer limited to a a specific filed. Early exposure to these packages will benefit the stud

29、ents. For a more detailed discussion of this topic readers can refer to our previous works 2-4. General DisadvantagesThree of the disadvantages of using these packages are the maintenance and operation of these packages on an accessible computer system, the extra work required by students (and instr

30、uctors) to learn how to use CAE packages, and assuring that the packages are included in the baseline curriculum as part of the required course material. A more detailed discussion of this topic can be found in our previous works 2-4. Optimal Control Systems at Penn State Great ValleyPenn State Grea

31、t Valley Campus, one of the eighteen campuses of the Penn State University, is a graduate center designed to address the educational need of the working engineers in Philadelphia area. Almost all of our students are working engineers, with a wide variety of backgrounds using simulation packages. The

32、 goals of this course are to expose the students to the mathematical tools of parametric and dynamic optimization and their uses in designing optimally behaving dynamic systems. The nonlinear systems course covers the following topics:1. Static Optimization2. Optimal Control of Discrete-Time Systems

33、2.1 Linear Quadratic Regulator2.2 Steady-State Closed-loop Control of Sub-Optimal Feedback2.3 The Tracking Problem2.4 Regulator with Function of Final State Fixed3. Optimal Control of Continuous-Time Systems3.1 Linear Quadratic Regulator3.2 Steady-State Closed-loop Control of Sub-Optimal Feedback3.3

34、 The Tracking Problem3.4 Regulator with Function of Final State Fixed3.5 Final-Time-Free Problem3.6 Constrained Input Problem4. Dynamic Programming4.1 Discrete-TimeSystems 14 and 15 are used in teaching the course. Students are given weekly assignments that also include computer simulation/usage. Ex

35、ams also include a take home part that have computer simulations. Student have access to student versions of MATLAB. Optimal Control Systems at the University of ArkansasThis course is offered to advanced undergraduate and graduate students with adequate preparation in classical and state space cont

36、rol techniques. The goals of this course are to expose the students to the mathematical tools of parametric and dynamic optimization and their uses in designing optimally behaving dynamic systems. To accomplish these goals, the author (E. Yaz) has been updating the course materials since 1986 so tha

37、t the following topics are typically covered in a semester:1. Unconstrained and constrained optimization problems (1 class)2. Cost function and parametric optimization (2 classes)3. Necessary and sufficient conditions for optimality (3 classes)4. Dynamic programming in continuous- and discrete-time

38、(3 classes)5. The minimum principle (1 class)6. Applications of the minimum principle (3 classes)7. Numerical techniques (2 classes)8. The continuous- and discrete-time quadratic regulator (LQR) and its variants (6 classes)9. Linear quadratic tracking and disturbance rejection (2 classes)10. Robustn

39、ess properties of LQR (2 classes)11. Introduction to guaranteed cost, H , and linear matrix . inequality methods (3 classes)12. Exams (2 clauses) Our class is normally 80 minutes of lecture. Typically two in-class are given and the rest of the grading is based on weekly homework assignments and the

40、student portfolio which is composed of the class notes that the student takes and the homework assignment corrections. The portfolios are collected twice, once in time to give mid-semester feedback and also, at the end of the semester, to measure the students general understanding. The major use of

41、the MATLAB software and its toolboxes is in homework solutions. The textbooks 14,15, 17, and 18 have been used individually over the years as the recommended textbook for the course together with reference books 19-22. The student responses that are mentioned in the conclusion are based on the stand

42、ard student evaluations using the Purdue Cafeteria form and also an informal written feedback solicited by E. Yaz. Use of MATLAB in Optimal Control Systems CourseIn this section we will present those features of the MATLAB that we have found most useful in our classes, based on the aforementioned co

43、urse outlines. The MATLAB and its Control Systems and Robust Control toolboxes are ideal for solving linear quadratic regulator (H2 Control) and H control problems. .The command “lqr” (“dqlr” in the discrete-time case) used in homework assignments to solve the linear quadratic regulator problems. Th

44、e syntax for this command isK, p, ev = lqr (A, B, Q, R, N) (1)where K is the optimal gain, P is the solution of the algebraic Riccati equation, and “ev” are the optimal closed loop eigenvalues. The quantities A, B, Q, R, N are respectively the system matrix input matrix, state weighing matrix, contr

45、ol weighting matrix and the weighting in the cross product of the state and control in the quadratic performance index. A general form of the algebraic Riccati equation can be solved by commandX = are (A, B, C) (2)Where and . Moreover, since the application of the optimal constant gain feedback u =

46、-Kx results in a linear time-invariant system description, stability margins can be found by Bode plots (“bode”). Also, the Nyquist plot (“nyquist (A, B, C, D)” )derived byKalman for single input systems. For the special choice of weighting matrices和, (3)the Hamiltonian matrix (4)is formed. The clos

47、ed loop system eigenvalues are just the stable eigenvalues of H . Since the characteristic polynomial for H can be put in the root locus form for the parameter “ ” by using root-locus plots (“rlocus”), one can control the closed loop pole locations. In the worst case or “minimax” the solution of the

48、 standard state feedback H. control problem is given by a special algebraic Riccati equation that can be solved by the command “are.” In other optima robust design of control system (5)where minimization of the usual infinite horizon quadratic cost criterion leads to the same type of “H ” type algeb

49、raic Riccati equation. .More recently, the MATLABs LMI toolbox 23became available, that makes the numerical solution of some problems that are not analytically traceable possible.One just example is minimizing an upper bound on the“stochastic” energy of the state of a multi-mode plant (6) where i =1

50、-N .The control of nonlinear systems with successive linearizations during the operation will lead to this kind of problems. Although, there is no known analysis solution, the LMI formulation allows a numerical solution to this convex optimization problem 24. Interactive Simulations with MATLABMATLA

51、B is also capable of producing interactive simulations. This can enhance the quality of presentation with graphical simulations. With the help of interactive simulations instructors can effectively illustrate the change in system response due to parameter variations. This helps students gain a bette

52、r understanding of the subject. Moreover, since there is no need for students to do any programming, this will allow students with limited or no knowledge of MATLAB programming to access features of MATLAB with little investments of time. This feature is essential in an interactive courseware develo

53、pment. Interactive simulations are produced with the help of graphical user interface (GUI) functions. The GUI is made up of graphical objects, such as menus, buttons, lists, and fields. These objects have meanings; when a user chooses an object there is an expectation that a certain kind of action

54、will take place. In MATLAB the GUI is implemented using user interface (UI) controls.Figure 1 shows the application of user interface inminimum control energy for a scalar system with fixed final state. The system model and performance index are given by (7)where and denote the state and control inp

55、ut,respectively. r is a positive scalar weighting factor. This program will produce plots of the state and the optimal input vs. time. The sliders will allow the user to change the system parameters and observe the resulting changes. Figure 2 illustrates the use of user interface control in a discrete-time fixed final state linear quadratic regulator. The system model and performance in