ACADEMICS
Course Details
ELE 430 Computer Control
2020-2021 Fall term information
The course is not open this term
Timing data are obtained using weekly schedule program tables. To make sure whether the course is cancelled or time-shifted for a specific week one should consult the supervisor and/or follow the announcements.
Course definition tables are extracted from the ECTS Course Catalog web site of Hacettepe University (http://akts.hacettepe.edu.tr) in real-time and displayed here. Please check the appropriate page on the original site against any technical problems. Course data last updated on 15/01/2021.
ELE430 - COMPUTER CONTROL
| Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
|---|---|---|---|---|---|---|
| COMPUTER CONTROL | ELE430 | 8th Semester | 3 | 0 | 3 | 6 |
| Prerequisite(s) | ELE354 Control Systems | |||||
| Course language | English | |||||
| Course type | Elective | |||||
| Mode of Delivery | Face-to-Face | |||||
| Learning and teaching strategies | Lecture Question and Answer Problem Solving Other: This course must be taken together with ELE434 COMPUTER CONTROL LABORATORY. | |||||
| Instructor (s) | Faculty members | |||||
| Course objective | Today, control systems are largely realized in digital form either on a computer or on cards that have computing power such as microcontroller or DSP cards. In this course, the necessary background is given in order to be able to understand such control systems and it is aimed at equipping students with the knowledge and skills needed to analyse and realise such systems. | |||||
| Learning outcomes |
| |||||
| Course Content | Description of computer control. Sampling of continuous-time signals. Signal reconstruction: zero-order hold, aliasing. Linear difference equations and discrete-time transfer functions. Poles, zeros and stability. The jury's stability test. Modelling and block diagram analysis. Mapping between the s-plane and z-plane. Discrete-time equivalents to continuous-time transfer functions: hold equivalence, forward and backward difference method, Tustin's method, pole-zero mapping. Time response analysis. Robot locus and Bode design. State space representation. Canonical forms. Solution of state space equations. Discretization of continuous-time state space equations. Controllability, reachability and observability. State feedback and Ackermann's formula. Deadbeat control. Observers. Duality. | |||||
| References | [1] Ogata K., Discrete-Time Control Systems, 2nd Ed., Prentice Hall, 1995. [2] Franklin G.F., Powell J.D. and Workman M.L., Digital Control of Dynamic Systems, 2nd Ed., Addison Wesley, 1990. [3] Aström K.J. and Wittenmark B., Computer Controlled Systems: Theory and Design, 3rd Ed., Prentice Hall, 1997. | |||||
Course outline weekly
| Weeks | Topics |
|---|---|
| Week 1 | An overview of digital control systems, sampling of continuous-time signals, signal reconstruction and Z-transform. |
| Week 2 | Discrete-time systems and analysis: solution of difference equations; pulse response; convolution sum; poles, zeros and stability; Jury's stability test; shift operator calculus. |
| Week 3 | Analysis of discrete-time systems from a continuous-time point of view; block diagram analysis of sampled data systems, zero-order hold equivalence of a continuous-time system, mapping between the s-plane and the z-plane. |
| Week 4 | Discrete-time equivalents to continuous-time transfer functions: zero-order and first order hold methods, backward and forward difference methods, Tustin's method, Tustin's method with frequency prewarping, pole-zero mapping. |
| Week 5 | Transient and steady-state response analysis of discrete-time systems. |
| Week 6 | Discrete control system design based on the root-locus method. |
| Week 7 | Discrete control system design based on the root-locus method. |
| Week 8 | Discrete control system design based on the frequency response method. |
| Week 9 | Midterm Exam |
| Week 10 | State-space representation of discrete-time systems: direct programming method, nested programming method, partial-fraction expansion programming method, canonical forms and similarity transformation. |
| Week 11 | Solving discrete-time state-space equations, state transition matrix, solution by Z-trasform, discretization of continuous-time state-space equations. |
| Week 12 | Controllability and reachability, observability, duality, transforming state-space equations into canonical forms. |
| Week 13 | Design of discrete control systems in state-space: state feedback, deadbeat control, Ackermann's formula |
| Week 14 | Design of discrete control systems in state-space : observer and observer + state feedback. |
| Week 15 | Preparation for Final exam |
| Week 16 | Final exam |
Assesment methods
| Course activities | Number | Percentage |
|---|---|---|
| Attendance | 0 | 0 |
| Laboratory | 0 | 0 |
| Application | 0 | 0 |
| Field activities | 0 | 0 |
| Specific practical training | 0 | 0 |
| Assignments | 5 | 10 |
| Presentation | 0 | 0 |
| Project | 0 | 0 |
| Seminar | 0 | 0 |
| Midterms | 1 | 40 |
| Final exam | 1 | 50 |
| Total | 100 | |
| Percentage of semester activities contributing grade succes | 0 | 50 |
| Percentage of final exam contributing grade succes | 0 | 50 |
| Total | 100 | |
Workload and ECTS calculation
| Activities | Number | Duration (hour) | Total Work Load |
|---|---|---|---|
| Course Duration (x14) | 13 | 3 | 39 |
| Laboratory | 0 | 0 | 0 |
| Application | 0 | 0 | 0 |
| Specific practical training | 0 | 0 | 0 |
| Field activities | 0 | 0 | 0 |
| Study Hours Out of Class (Preliminary work, reinforcement, ect) | 14 | 4 | 56 |
| Presentation / Seminar Preparation | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Homework assignment | 5 | 4 | 20 |
| Midterms (Study duration) | 1 | 20 | 20 |
| Final Exam (Study duration) | 1 | 25 | 25 |
| Total Workload | 34 | 56 | 160 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
| D.9. Key Learning Outcomes | Contrubition level* | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1. PO1. Possesses the theoretical and practical knowledge required in Electrical and Electronics Engineering discipline. | X | ||||
| 2. PO2. Utilizes his/her theoretical and practical knowledge in the fields of mathematics, science and electrical and electronics engineering towards finding engineering solutions. | X | ||||
| 3. PO3. Determines and defines a problem in electrical and electronics engineering, then models and solves it by applying the appropriate analytical or numerical methods. | X | ||||
| 4. PO4. Designs a system under realistic constraints using modern methods and tools. | X | ||||
| 5. PO5. Designs and performs an experiment, analyzes and interprets the results. | X | ||||
| 6. PO6. Possesses the necessary qualifications to carry out interdisciplinary work either individually or as a team member. | X | ||||
| 7. PO7. Accesses information, performs literature search, uses databases and other knowledge sources, follows developments in science and technology. | X | ||||
| 8. PO8. Performs project planning and time management, plans his/her career development. | X | ||||
| 9. PO9. Possesses an advanced level of expertise in computer hardware and software, is proficient in using information and communication technologies. | X | ||||
| 10. PO10. Is competent in oral or written communication; has advanced command of English. | X | ||||
| 11. PO11. Has an awareness of his/her professional, ethical and social responsibilities. | X | ||||
| 12. PO12. Has an awareness of the universal impacts and social consequences of engineering solutions and applications; is well-informed about modern-day problems. | X | ||||
| 13. PO13. Is innovative and inquisitive; has a high level of professional self-esteem. | X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest