外文翻译---电气工程毕业生使用matlab最优控制的过程-电气类(编辑修改稿)

外文翻译---电气工程毕业生使用matlab最优控制的过程-电气类(编辑修改稿)内容摘要：

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 presented 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 Advantages The main advantages of using these tools are: the reinforcement of student understanding of theoretical principles by means of enhanced graphical aids and interactive simulations, analysis of more plex systems that can be treated by pencil and paper, and the instructors ability to assign fairly plex design problems that otherwise would have be unrealistic 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 MATLAB[16], are no longer limited to a a specific filed. Early exposure to these packages will benefit the students. For a more detailed discussion of this topic readers can refer to our previous works [2][4]. General Disadvantages Three of the disadvantages of using these packages are the maintenance and operation of these packages on an accessible puter system, the extra work required by students (and instructors) 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 Valley Penn State Great 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 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 Optimization 2. Optimal Control of DiscreteTime Systems Linear Quadratic Regulator SteadyState Closedloop Control of SubOptimal Feedback The Tracking Problem Regulator with Function of Final State Fixed 3. Optimal Control of ContinuousTime Systems Linear Quadratic Regulator SteadyState Closedloop Control of SubOptimal Feedback The Tracking Problem Regulator with Function of Final State Fixed FinalTimeFree Problem Constrained Input Problem 4. Dynamic Programming DiscreteTime Systems [14] and [15] are used in teaching the course. Students are given weekly assignments that also include puter simulation/usage. Exams also include a take home part that have puter simulations. Student have access to student versions of MATLAB. Optimal Control Systems at the University of Arkansas This course is offered to advanced undergraduate and graduate students with adequate preparation in classical and state space control 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 acplish these goals, the author (E. Yaz) has been updating the course materials since 1986 so that 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 discretetime (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 discretetime quadratic regulator (LQR) and its variants (6 classes) 9. Linear quadratic tracking and disturbance rejection (2 classes) 10. Robustness 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 inclass are given and the rest of the grading is based on weekly homework assignments and the student portfolio which is posed of the class notes that the student takes and the homework assignment corrections. The portfolios are collected twice, once in time to give midsemester。