| Instructor(s) | Dr. Owais Khan [Coordinator] Office: ENG328 Phone: (416) 979-5000 x 556096 Email: owaiskhan@torontomu.ca Office Hours: | ||||||||||||||||
| Calendar Description | Introductory course for Biomedical Engineers: system modeling, simulation, analysis and classical-controller designs of linear, time-invariant, continuous time systems. System dynamic properties in time and frequency domains, performance specifications and basic properties of feedback are investigated. Stability analysis is reinforced through Routh-Hurwitz criterion, Root-Locus method, Bode plots, and Nyquist criteria. Concept of Bio-Robotics is introduced, and exposure to basics of state-space representation and feedback. Key control concepts are experienced through laboratory experiments using modular servo-system with open architecture, fully integrated with MATLab and Simulink; use of simulation tools; and solving design problems. | ||||||||||||||||
| Prerequisites | BME 532, CEN 199 | ||||||||||||||||
| Antirequisites | ELE 639 | ||||||||||||||||
| Corerequisites | None | ||||||||||||||||
| Compulsory Text(s): |
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| Reference Text(s): |
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| Learning Objectives (Indicators) | At the end of this course, the successful student will be able to:
NOTE:Numbers in parentheses refer to the graduate attributes required by the Canadian Engineering Accreditation Board (CEAB). | ||||||||||||||||
| Course Organization | 3.0 hours of lecture per week for 13 weeks | ||||||||||||||||
| Teaching Assistants | Ohiomueti Uantioje (ouantioje@torontomu.ca) Shayan Sepahvand (shayan.sepahvand@torontomu.ca) Lucas Machowski (lucas.machowski@torontomu.ca) | ||||||||||||||||
| Course Evaluation |
Note: In order for a student to pass a course, a minimum overall course mark of 50% must be obtained. In addition, for courses that have both "Theory and Laboratory" components, the student must pass the Laboratory and Theory portions separately by achieving a minimum of 50% in the combined Laboratory components and 50% in the combined Theory components. Please refer to the "Course Evaluation" section above for details on the Theory and Laboratory components (if applicable). | ||||||||||||||||
| Examinations | Midterm exam in Week 7 during the Lecture time, two hours, problem solving, closed book (covers Week 1-6). Final exam during exam period, closed book (covers Weeks 1-13) | ||||||||||||||||
| Other Evaluation Information | There are assignment problems for each chapter posted on the course D2L. The assignment will not be collected. However, students are expected to solve the assignment problems. Lab marks are based on attendance, successful completion of pre-lab problems, participation, completion of experiment steps, lab reports and successful reply to your TA questions during submission. Students will have the responsibility to achieve a working knowledge of the software packages that will be used in the lab. Students will work in groups of two. | ||||||||||||||||
| Other Information | Course Policy on the Use of Generative AI: Where GenAI is prohibited entirely in the development of coursework: -------------------------------------------------------------------- Use of Generative AI (e.g. ChatGPT, Grammarly, Perplexity, DeepL Translator) to develop or assist with any ideas or material submitted for coursework is expressly prohibited in this course. Use of Generative AI in this manner will be considered a breach of Policy 60. Where GenAI is permitted for grammar correction only: ----------------------------------------------------- Students may use Generative AI (e.g. ChatGPT, Grammarly, Perplexity, DeepL Translator) only for minor grammar correction. This includes translating individual words and correcting spelling, punctuation and basic grammar issues. AI tools may not be used to make substantial revisions such as edits to style, tone, content nor rewrite phrases.Failure to stay within these limits will be considered a breach of Policy 60. Where GenAI is permitted for ideation and brainstorming: -------------------------------------------------------- Students may use Generative AI (e.g. ChatGPT, Grammarly, Perplexity, DeepL Translator) for ideation and brainstorming but not for research or for writing anything that will be submitted for credit. Failure to stay within these limits will be considered a breach of Policy 60. Where GenAI is optional: ------------------------ Students may use Generative AI (e.g. ChatGPT, Grammarly, Perplexity, DeepL Translator) in this course. However, If you misrepresent source material (as AI often does), that will be considered a breach of Policy 60 If your citations are not genuine (AI often makes up references), that will be considered a breach of Policy 60 Students are required to write a clear declarative statement describing how AI tools were used and the extent of its contribution to the final submission. Where GenAI is integral: ------------------------ Students are required to use Generative AI in this course. If you have concerns about using this technology and require alternative assessments, by the end of the second week of class, consult with the instructor to make alternate arrangements. Questions? Contact: Academic Integrity Office, Toronto Metropolitan University https://www.torontomu.ca/academicintegrity/ aio@torontomu.caPlease note that these statements are merely examples of how instructors may want to frame their expectations around GenAI. | ||||||||||||||||
Week | Hours | Chapters / | Topic, description |
|---|---|---|---|
1 | 3 | Chapter 1, 2, 3 | Introduction: Information session, General concepts of feedback and control systems, Closed-loop control versus Open-loop control, Modeling Mechanical and Electrical Systems, Differential Equations and Laplace Transform Review. |
2 | 3 | Chapter 4.1 - 4.2 | Transfer function representation, Block diagram rules and simplifications, Signal flow graphs Mason's Gain Formula. |
3 | 3 | Chapter 7.1 - 7.5, 7.8 | Linear System Time Response: Transient response analysis, First-order systems, Second-order systems, Higher-order systems and dominant poles. |
4 | 3 | Chapter 5, 7.6 | Stability Analysis: BIBO stability definition, Characteristic polynomials, Poles and stability conditions of LTI systems, Routh-Hurwitz stability criterion, Steady-State error analysis of feedback systems. |
5 | 3 | Chapter 9 | Root Locus Analysis: Closed-loop pole relation to the loop gain, Root locus graphical method of pole representation, Magnitude and angle laws, Root-locus plotting rules. |
6 | 3 | Chapter 11.1 - 11.3 | Design of Control Systems in Time Domain for PD, PI and PID controllers. |
---------- STUDY WEEK ---------- | |||
7 | 3 | Midterm Exam | |
8 | 3 | Chapter 10.1 - 10.2 | Frequency Response Analysis I: Frequency response, Frequency-domain representation, Bode Diagram, Relation between magnitude and phase, Cross over frequency Bandwidth. |
9 | 3 | Chapter 10.4 - 10.11 | Frequency Response Analysis: Polar Plots Nyquist Diagram Nyquist stability criteria Relative stability, Stability margins, Gain margin and phase margins |
10 | 3 | Chapter 11.1 - 11.5 | Design of Controller in Frequency Domain: Lead/Lag compensator and P PI PD and PID controller design in frequency-domain |
11 | 3 | Chapter 3.6 - 3.7, 4-3, 8.1-8.11 | State-Space Analysis: State-space representation of systems, State diagrams and state variables, State-space equations from high-order differential equations, State transition matrix, Characteristic equation and eigenvalues. |
12 | 3 | Chapter 8.12 - 8.19 | State-Space Design: Controllability and Observability of Linear Systems, State feedback control, Tracking objectives, Pole placement method, State feedback with integral control |
13 | 3 | Practice Problems | Course Review |
Week | L/T/A | Description |
|---|---|---|
2-3 | Lab 1.1 | Lab # 1.1: Introduction to Simulink, Open-Loop Control vs. Closed-Loop Control |
4-5 | Lab 1.2 | Lab # 1.2: Transient Response Analysis and Stability of 2nd and 3rd Order Systems. |
6-7 | Lab 2.1 | Lab # 2.1: Transfer Function Modeling of Physical Systems and Control. |
8-9 | Lab 2.2 | Lab # 2.2: Introduction to Lead and Lag Compensators |
10-11 | Lab 3.1 | Lab # 3.1: Introduction to PI PD and PID Controllers |
12-13 | Lab 3.2 | Lab # 3.2: State Space Modeling of Physical Systems and Control. |
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Refer to the Departmental FAQ page for furhter information on common questions.
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