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Unit outline_

ELEC3304: Control

Semester 2, 2022 [Normal day] - Camperdown/Darlington, Sydney

This unit is mainly concerned with the application of feedback control to continuous-time, linear time-invariant systems. It aims to give the students an appreciation of the possibilities in the design of control and automation in a range of application areas. The concepts learnt in this unit will be made use of heavily in many units of study in the areas of communication, control, electronics, and signal processing. The following specific topics are covered: Modelling of physical systems using state space, differential equations, and transfer functions, dynamic response of linear time invariant systems and the role of system poles and zeros on it, simplification of complex systems, stability of feedback systems and their steady state performance, Routh-Hurwitz stability criterion, sketching of root locus and controller design using the root locus, Proportional, integral and derivative control, lead and lag compensators, frequency response techniques, Nyquist stability criterion, gain and phase margins, compensator design in the frequency domain, state space design for single input single-output systems, pole placement state variable feedback control and observer design.

Unit details and rules

Academic unit School of Electrical and Computer Engineering
Credit points 6
Prerequisites
? 
ELEC2302 AND (MATH2061 OR MATH2067 OR MATH2021 OR MATH2961 OR AMME2000)
Corequisites
? 
None
Prohibitions
? 
AMME3500
Assumed knowledge
? 

Specifically the following concepts are assumed knowledge for this unit: familiarity with basic Algebra, Differential and Integral Calculus, Physics; solution of linear differential equations, Matrix Theory, eigenvalues and eigenvectors; linear electrical circuits, ideal op-amps; continuous linear time-invariant systems and their time and frequency domain representations, Laplace transform, Fourier transform

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Yash Shrivastava, yash.shrivastava@sydney.edu.au
Type Description Weight Due Length
Final exam (Open book) Type C final exam Final exam
End of Semester Exam
60% Formal exam period 2 hours
Outcomes assessed: LO6 LO7 LO8 LO9 LO10
Participation group assignment Labs
Labs and lab reports
7% Multiple weeks n/a
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10
Participation group assignment Tutorials
tutorials
8% Multiple weeks n/a
Outcomes assessed: LO1 LO2 LO3 LO6 LO7 LO8 LO9 LO10
Small test Mid-term exam
Midterm Exam
25% Week 09
Due date: 05 Oct 2022 at 11:00

Closing date: 05 Oct 2022
70 minutes
Outcomes assessed: LO6 LO10 LO9 LO8 LO7
group assignment = group assignment ?
Type C final exam = Type C final exam ?

Assessment summary

  • Tutorials: There will be 8 tutorials (of 2 hours each) during the semester. Tutorials will include analytical problem solving sessions on the material covered in the lectures, and computer aided solution/illustration. These sessions will give you the opportunity to explore the concepts in detail and are very helpful in understanding the material covered in the lecture. 
  • Labs: There will be 4 laboratories (of 3 hours each) during the semester. Laboratories are designed to introduce you to basic feedback control concepts and measurements. They will require you to do system identification for lab equipment, and implement/test a few standard controllers for it, and model and simulate dynamic systems, and controllers in Matlab. Students will work in groups of two or three, but will submit individual reports.
  • Mid-term exam: The midterm exam is scheduled to give you a practice run for the final exam. It will be of the same format as the final exam (but of shorter duration). This exam will be closed-book and closed-notes. It will test your conceptual understanding of the lecture material and tutorials.
  • Final exam: This exam will be closed-book and closed-notes. It will test your conceptual understanding of the lecture material and tutorials.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range

Description

High distinction

85 - 100

 

Distinction

75 - 84

 

Credit

65 - 74

 

Pass

50 - 64

 

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Multiple weeks Students need to spend roughly 3 hours each week on independent study to deeply engage with the material covered in that week Independent study (39 hr) LO1 LO6 LO7 LO8 LO9 LO10
Week 01 Introduction and review of Laplace Transform Lecture and tutorial (2 hr) LO1
Week 02 Modeling of physical systems Lecture and tutorial (5 hr) LO1 LO3 LO10
Week 03 Modeling of physical systems and linearization of nonlinear systems Lecture and tutorial (5 hr) LO1 LO3 LO10
Week 04 Time response of linear systems Lecture and tutorial (5 hr) LO3 LO6
Week 05 System reduction Lecture and tutorial (5 hr) LO2 LO3 LO4 LO5 LO7
Week 06 Stability of linear systems, Routh-Hurwitz criterion, and steady state errors Lecture and tutorial (5 hr) LO2 LO3 LO4 LO5 LO8
Week 07 Steady state errors, sensitivity, and root locus techniques Lecture and tutorial (5 hr) LO3 LO8 LO9
Week 08 Controller design using root locus Lecture and tutorial (5 hr) LO3 LO9
Week 09 Lecture devoted to Midterm Exam Lecture and tutorial (5 hr) LO6 LO7 LO8
Week 10 Controller design using root locus continued Lecture and tutorial (5 hr) LO2 LO3 LO4 LO5 LO9
Week 11 Frequency response and Bode plots Lecture and tutorial (5 hr) LO3 LO9
Week 12 Nyquist criterion for stability and controller design using frequency response techniques Lecture and tutorial (5 hr) LO2 LO3 LO4 LO5 LO9
Week 13 Controller design using state space techniques Lecture and tutorial (5 hr) LO3 LO9

Attendance and class requirements

  • Tutorials: Tutorials are devoted to practicing basic concepts covered in the lectures, and understanding how more complex tasks can be handled by putting these basic concepts together. The focus is on active learning, and group work and discussion is encouraged. Students will also get to present their solutions to the rest of the class.
  • Laboratories: Labs are devoted to hands-on experience with real control systems. Students will do the modeling, make measurements, and design control schemes for the lab equipment. They will also present their results in the format of lab reports.
  • Independent study: Students will need to do some preparation for tutorials and labs; they may need to read the texts and other references to fully master the basic concepts covered in the lectures.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

All readings for this unit can be accessed through the Library eReserve, available on Canvas.

  • Norman S. Nise, Control Systems Engineering (eigth). Wiley, 2019. ISBN 9781119594352.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. recognise the limits of the information presented in the lectures, and target information searches through varied sources and formats, so as to synthesise information relevant to the specific topic at hand
  • LO2. produce written and oral presentations in the form of lab reports and tutorial presentations
  • LO3. work in a team to discuss and draw upon the ideas and knowledge of others, to solve and present tutorial problems, and conduct lab experiments
  • LO4. conduct lab experiments, and take measurements to perform a model identification for a particular engineering problem
  • LO5. design and test feedback control schemes for the lab equipment to achieve different performance requirements
  • LO6. analyse the dynamic response of linear time invariant systems, and the role of system poles and zeros on it
  • LO7. simplify complex systems consisting of interconnections of several linear subsystems
  • LO8. determine the stability of feedback systems and their steady state performance
  • LO9. design simple controllers to achieve stability and transient performance requirements, using root locus, frequency response, and state space techniques
  • LO10. Model physical systems (e.g. electrical, mechanical, and electromechanical systems) using state space, differential equations, and transfer functions.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

Learning activities changed back to 13 weeks.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.