| Obligation |
: |
Must |
| Prerequisite courses |
: |
ELE301 |
| Concurrent courses |
: |
ELE356 |
| Delivery modes |
: |
Face-to-Face |
| Learning and teaching strategies |
: |
Lecture, Question and Answer, Problem Solving, Other: This course must be taken together with ELE356 CONTROL SYSTEMS LABORATORY. |
| Course objective |
: |
The main purpose of this course is to teach fundamental analysis methods for control systems. The analysis methods discussed in the course are also useful for control system design; however analysis aspects of the methods will be emphasized. Various methods for transient analysis, steady-state analysis and stability analysis will be studied. To that end, after a comprehensive introduction to systems modeling; both frequency domain and time domain approaches are studied in detail. Design point of view is given implicitly via analysis examples. The topics covered in the course are reinforced via experiments conducted in ELE 356 (Control Systems Laboratory). |
| Learning outcomes |
: |
A student who completes the course successfully will 1. Understand the basic principles and characteristics of feedback control systems. 2. Obtain mathematical models of various physical systems. 3. Perform stability analysis of feedback control systems via different methods. 4. Understand the design and realization of control system components to meet given specifications. 5. Recognize, formulate and solve some control engineering problems. 6. Have a working knowledge of existing software tools necessary both for control engineering practice and academic research. |
| Course content |
: |
Historical perspective of control systems. Basic concepts of open-loop and closed-loop, feedback. Models of physical systems: electrical systems, mechanical systems, fluid systems, thermal systems, servomotors, electro-mechanical systems. Block diagrams, signal-flow graphs. Time response analysis, steady-state error analysis. Sensitivity, disturbance rejection and stability analysis, Routh-Hurwitz criterion. Root-Locus plotting. Frequency response analysis: Bode, polar and magnitude-phase plots, Nyquist analysis, gain/phase margins, Nichols chart. State-space analysis: State-space description, state transition matrix, similarity transformation, diagonalization of system matrix, modal decomposition, companion forms, transfer function decomposition, controllability and observability. State-space design: State feedback, state observer. |
| References |
: |
[1] Ogata K., Modern Control Engineering, 5/e, Prentice Hall, 2010.; [2] Dorf R.C., and Bishop R.H., Modern Control Systems, 12/e, Prentice Hall, 2011.; [3] Franklin G.F., Powell J.D, and Emami-Naeini A., Feedback Control of Dynamical Systems, 6/e, Prentice Hall, 2010.; [4] Golnaraghi F., and Kuo B.C., Automatic Control Systems, 9/e, John Wiley, 2009.; [5] Nise N.S., Control Systems Engineering, 6/e, John Wiley, 2011. |
Course Outline Weekly
| Weeks |
Topics |
| 1 |
Historical perspective of control systems, basic concepts of open-loop and closed-loop, feedback |
| 2 |
Models of physical systems: Electrical systems, mechanical systems |
| 3 |
Models of physical systems: Fluid systems, thermal systems |
| 4 |
Models of physical systems: Servomotors, electro-mechanical systems, block diagrams, signal-flow graphs |
| 5 |
Time response analysis |
| 6 |
Steady-state error analysis, sensitivity, disturbance rejection |
| 7 |
Stability analysis, Routh-Hurwitz criterion |
| 8 |
Root-Locus plotting |
| 9 |
Midterm Exam |
| 10 |
Frequency response analysis: Bode, polar and magnitude-phase plots |
| 11 |
Frequency response analysis: Nyquist analysis, gain/phase margins, Nichols chart |
| 12 |
State-space analysis: State-space description, state transition matrix, similarity transformation, diagonalization of system matrix |
| 13 |
State-space analysis: Modal decomposition, companion forms, transfer function decomposition, controllability and observability |
| 14 |
State-space design: State feedback, state observer |
| 15 |
Final exam preparation |
| 16 |
Final exam |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
| Key learning outcomes |
Contribution level |
| 1 |
2 |
3 |
4 |
5 |
| 1. |
Possesses the theoretical and practical knowledge required in Electrical and Electronics Engineering discipline. | | | | | |
| 2. |
Utilizes his/her theoretical and practical knowledge in the fields of mathematics, science and electrical and electronics engineering towards finding engineering solutions. | | | | | |
| 3. |
Determines and defines a problem in electrical and electronics engineering, then models and solves it by applying the appropriate analytical or numerical methods. | | | | | |
| 4. |
Designs a system under realistic constraints using modern methods and tools. | | | | | |
| 5. |
Designs and performs an experiment, analyzes and interprets the results. | | | | | |
| 6. |
Possesses the necessary qualifications to carry out interdisciplinary work either individually or as a team member. | | | | | |
| 7. |
Accesses information, performs literature search, uses databases and other knowledge sources, follows developments in science and technology. | | | | | |
| 8. |
Performs project planning and time management, plans his/her career development. | | | | | |
| 9. |
Possesses an advanced level of expertise in computer hardware and software, is proficient in using information and communication technologies. | | | | | |
| 10. |
Is competent in oral or written communication; has advanced command of English. | | | | | |
| 11. |
Has an awareness of his/her professional, ethical and social responsibilities. | | | | | |
| 12. |
Has an awareness of the universal impacts and social consequences of engineering solutions and applications; is well-informed about modern-day problems. | | | | | |
| 13. |
Is innovative and inquisitive; has a high level of professional self-esteem. | | | | | |
