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Unit of study_

AMME9501: System Dynamics and Control

Semester 1, 2022 [Normal day] - Camperdown/Darlington, Sydney

This unit of study aims to allow students to develop an understanding of methods for modeling and controlling linear, time-invariant systems. Techniques examined will include the use of differential equations and frequency domain approaches to modeling of systems. This will allow students to examine the response of a system to changing inputs and to examine the influence of external stimuli such as disturbances on system behaviour. Students will also gain an understanding of how the responses of these mechanical systems can be altered to meet desired specifications and why this is important in many engineering problem domains. The study of control systems engineering is of fundamental importance to most engineering disciplines, including Electrical, Mechanical, Mechatronic and Aerospace Engineering. Control systems are found in a broad range of applications within these disciplines, from aircraft and spacecraft to robots, automobiles, computers and process control systems. The concepts taught in this course introduce students to the mathematical foundations behind the modelling and control of linear, time-invariant dynamic systems. In particular, topics addressed in this course will include: Techniques for modelling mechanical systems and understanding their response to control inputs and disturbances (this will include the use of differential equations and frequency domain methods as well as tools such as Root Locus and Bode plots); Representation of systems in a feedback control system as well as techniques for determining what desired system performance specifications are achievable, practical and important when the system is under control; Theoretical and practical techniques that help engineers in designing control systems, and an examination of which technique is best in solving a given problem.

Unit details and rules

Unit code AMME9501
Academic unit Aerospace, Mechanical and Mechatronic
Credit points 6
Prohibitions
? 
AMME8501
Prerequisites
? 
AMME9500
Corequisites
? 
None
Assumed knowledge
? 

AMME5500 or AMME9500. Students are assumed to have a good background knowledge in ordinary differential equations, Laplace transform methods, linear algebra and mathematical modeling of mechanical systems

Available to study abroad and exchange students

No

Teaching staff

Coordinator Guodong Shi, guodong.shi@sydney.edu.au
Lecturer(s) Guodong Shi, guodong.shi@sydney.edu.au
Type Description Weight Due Length
Final exam (Open book) Type C final exam hurdle task Final Canvas Exam
Canvas-based examination.
30% Formal exam period 2 hours
Outcomes assessed: LO1 LO2 LO3 LO4
Small continuous assessment Weekly problem sets
Solutions to small problem sets submitted to Canvas for each week.
5% Multiple weeks n/a
Outcomes assessed: LO1 LO5 LO4 LO3 LO2
Assignment Design project 1
A control system design project with prescribed system requirements.
20% Week 06 n/a
Outcomes assessed: LO1 LO2 LO5
Assignment group assignment Laboratory report
In-person or online Matlab labs.
20% Week 12 n/a
Outcomes assessed: LO1 LO2 LO3 LO4 LO5
Assignment Design project 2
An open design project on control systems.
25% Week 13 n/a
Outcomes assessed: LO2 LO3 LO4 LO5
hurdle task = hurdle task ?
group assignment = group assignment ?
Type C final exam = Type C final exam ?

Assessment summary

  • Weekly problem sets: The weekly problem sets test straightforward application of mathematical techniques to example problems. Similar problems will be given as worked examples in the tutorials; full solutions will be published after the submission due. The score will be Fail/Pass. You pass the assignment and receive the full 5% marks if you submit at least 9 out of 12 problem set solutions on time; you fail the assignment and receive 0% mark if you submit less than 9 out of 12 problem set solutions on time. 
  • Design projects: The design projects test these skills and additionally a broader range of abilities, including critical reasoning about mathematical modelling, experiment design, data visualisation, drawing conclusions from mathematics and empirical results, and written communication skills.
  • Laboratory report: The laboratory component allows hands-on experimentation with a real control system, and presents a series of increasingly challenging design problems. The laboratory is done in pairs, and a pdf report submitted at the end of semester.
  • Final exam: Students must pass the final exam in order to pass the subject.
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 sydney.edu.au/students/guide-to-grades.

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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

The Assessment Procedures 2011 provide that any written work submitted after 11:59pm on the due date will be penalised by 5% of the maximum awardable mark for each calendar day after the due date. If the assessment is submitted more than 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.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

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
Please select a valid week from the list below Six hours for each week on studying lecture notes and textbook, watching pre and post-class recordings, working on assignments and projects Independent study (78 hr) LO1 LO2 LO3 LO4 LO5
Week 01 Introduction to dynamics and feedback Lecture and tutorial (5 hr) LO1 LO2
Week 02 First-order dynamical systems Lecture and tutorial (5 hr) LO1 LO2
Week 03 First-order control systems Lecture and tutorial (5 hr) LO1 LO2
Week 04 Second and higher-order systems Lecture and tutorial (5 hr) LO1 LO2 LO3
Week 05 Second-order control systems Lecture and tutorial (5 hr) LO1 LO2 LO3
Week 06 Linear systems: general theory Lecture and tutorial (5 hr) LO1 LO2 LO3
Week 07 State-feedback control design Lecture and tutorial (5 hr) LO1 LO2 LO3
Week 08 State estimators and output feedback Lecture and tutorial (5 hr) LO1 LO2 LO3
Week 09 Control system applications in engineering and beyond Lecture and tutorial (5 hr) LO3 LO4 LO5
Week 10 Transfer functions and frequency analysis Lecture and tutorial (5 hr) LO3 LO4 LO5
Week 11 Frequency design Lecture and tutorial (5 hr) LO3 LO4 LO5
Week 12 Fundamental limitations of feedback control design Lecture and tutorial (5 hr) LO3 LO4 LO5
Week 13 Course summary and Perspectives on machine learning approaches for control systems Lecture and tutorial (5 hr) LO3 LO4

Attendance and class requirements

Attendance: Attendance and participation will be marked in the lab, and you will get zero for the lab component if you do not get the participation mark for your timetabled laboratory, unless you have a valid special consideration.

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.

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. mathematically model mechanical and other systems and determine their response characteristics based on the physical properties of the system and Laplace transform methods
  • LO2. understand how desired specifications of a mechanical system such as stability, overshoot, rise time, the time constant of a system, natural frequency and damping ratio can be represented mathematically and how they depend on system parameters
  • LO3. demonstrate an ability to design controllers and meet specifications using tools such as Root Locus, Bode Plots, and State Space; understand the relative strengths and weaknesses of each technique
  • LO4. understand the role of feedback in providing robustness to modelling uncertainty and external disturbances
  • LO5. analyse and design control loops using Matlab and Simulink software tools.

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.

(1) Short videos before/after the lectures on technical preliminaries/extensions. (2) More hands-on examples for Matlab. (3) Design Project 01 will be redesigned; Design Project 02 will have more technical support for system modeling.

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.