This course introduces a broad range of non-trivial techniques and approaches for modelling and simulation of dynamic engineering systems. Techniques include discrete event models; first- and second-order system models; time, frequency and state space relations; and feedback systems. These concepts are introduced through the modelling of electrical systems, mechanical systems, energy systems, control systems etc. Modelling software such as EXTENDSIM, Matlab and Simulink will be key tools in this course.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

After completing this course students will be expected to:

1. implement a wide range of deterministic and probabilistic system models.
2. demonstrate the relationship between discrete and continuous systems.
3. illustrate simple properties of dynamic systems in both time and frequency domains.
4. implement system models in Matlab.
5. evaluate the appropriate modelling paradigm(s) to describe behaviour of real engineering systems.

Professional Skills Mapping
Mapping of Learning Outcomes to Assessment and Professional Competencies

Research-Led Teaching

The selection of material in this course is heavily informed by current research trends in engineering and by the course convener's own research interests. In the Major project component of the course, students are guided towards using modeling methods and tools derived from cutting edge research in the engineering disciplines their project topic is drawn from. Students are actively encouraged to use their own research insights where applicable and appropriate.

Field Trips

N/A

Additional Course Costs

Nil

Examination Material or equipment

Detailed instructions for the Final exam component of the course will be provided on the Wattle course page.

Required Resources

All learning resources for this course are provided on the Wattle course page, including electronic copies of relevant textbooks. Access to the MATLAB/Simulink programming environment is provided through the ANU Information Commons (both on campus and virtually).

Recommended Resources

An extensive list of supplementary learning resources is provided on the Wattle course page.

Staff Feedback

Students will be given feedback in the following forms in this course:

• written comments
• verbal comments
• feedback to whole class, groups, individuals, focus group etc

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

Class Schedule

Week/Session	Summary of Activities	Assessment
1	Lecture: Course overview, key modelling concepts	On/Off-campus declaration, Major project team sign-up For further details, please see the course schedule on the Wattle course page.
2	Lecture: Equations of motion, Projectile motion Computer lab: Introduction to MATLAB, Simple numerical models, Numerical Integration	Computer lab, Quiz #1, Major project team sign-up finalized For further details, please see the course schedule on the Wattle course page.
3	Lecture: First and second order differential equations, Modelling pendulums, RLC circuits, spring mass damper systems Computer lab: First and second order differential equations, Comparison of numerical integration techniques Major project: work in teams	Computer lab, Quiz #2 For further details, please see the course schedule on the Wattle course page.
4	Lecture: n-th order differential systems, State space model derivation, Linear systems, Laplace analysis and transfer functions, Controllability Computer lab: State space simulation, Transfer functions, Controllability analysis Major project: work in teams Assignment: individual work	Computer lab, Quiz #3, Major project milestone #1 (project topic selection and justification) For further details, please see the course schedule on the Wattle course page.
5	Lecture: Random variables, Probability distributions (discrete and continuous), Gaussian and Poisson distributions Computer lab: Major project work Major project: work in teams Assignment: individual work	Quiz #4 For further details, please see the course schedule on the Wattle course page.
6	Lecture: Conditional probability, Bayes theorem, Filtering (including Kalman filter) Computer lab: Simulating random events, Probability distribution functions, Gaussian and Poisson distributions Major project: work in teams Assignment: individual work	Computer lab, Quiz #5, Major project milestones #2 and #3 (intended project outcome and peer feedback) For further details, please see the course schedule on the Wattle course page.
7	Lecture: Linear regression, Regularisation Computer lab: Major project work Major project: work in teams Assignment: individual work	Quiz #6, Major project milestone #4 (modelling framework and system model) For further details, please see the course schedule on the Wattle course page.
8	Lecture: Clustering, Classification, Machine learning Computer lab: Least squares linear regression, Tikhonov regularised regression, L1 penalised regression and the Lasso Major project: work in teams Assignment: individual work	Computer lab, Quiz #7, Assignment For further details, please see the course schedule on the Wattle course page.
9	Lecture: Logical graph models, Automata, Markov chains Computer lab: Clustering, Classification, Decision Trees Major project: work in teams	Computer lab, Quiz #8 For further details, please see the course schedule on the Wattle course page.
10	Lecture: Graph flows, Modelling differential systems using graphs, Bayesian networks Computer lab: Automata, Markov chains Major project: work in teams	Computer lab, Quiz #9 For further details, please see the course schedule on the Wattle course page.
11	Lecture: Artificial intelligence, Neural networks, Current research and development activities Computer lab: Neural networks Major project: work in teams	Computer lab, Quiz #10, Major project presentation For further details, please see the course schedule on the Wattle course page.
12	Lecture: course summary Major project: work in teams	Major project milestone #5 (peer feedback) and final report For further details, please see the course schedule on the Wattle course page.

Tutorial Registration

All sign-ups are managed through the Wattle course page

Assessment Summary

Assessment task	Value	Due Date
Quizzes	20 %	*
Assignment	15 %	27/09/2021
Major project	25 %	*
Final exam	40 %	*

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

Policies

ANU has educational policies, procedures and guidelines , which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Integrity Rule before the commencement of their course. Other key policies and guidelines include:

• Academic Integrity Policy and Procedure
• Student Assessment (Coursework) Policy and Procedure
• Special Assessment Consideration Guideline and General Information 
• Student Surveys and Evaluations
• Deferred Examinations
• Student Complaint Resolution Policy and Procedure
• Code of practice for teaching and learning

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

Participation

Participation is judged by successful submission of assessment tasks, there is no separate participation mark.

Examination(s)

The course includes a formal Final exam.

Assessment Task 1

Quizzes

Weekly self-marking on-line quizzes in multiple choice/short answer style (less than 15 minutes) run through the Wattle course page (10 quizzes, 2% each), due date is 4:00pm Friday each week as per the detailed course schedule on the Wattle course page. Quizzes test understanding of the material covered in lectures as well as results of computer labs.

Assessment Task 2

Assignment

Individual written assignment report (max. 10 pages) due 4:00pm Monday 2021-09-27.

Assessment Task 3

Major project

Major course project conducted in teams of 5 students, assessment is based on progressive milestone submissions (project topic selection and justification due 4pm Wednesday 2021-08-18, intended project outcomes due 4:00pm Wednesday 2021-09-01, initial peer feedback due 4:00pm Friday 2021-09-03, modelling framework and system model due 4:00pm Wednesday 2021-09-22, final peer feedback due 4:00pm Wednesday 2021-10-27), a project presentation (10 minutes) due in Week 11, and a written final project report due 4:00pm Wednesday 2021-10-27. A detailed Assessment guide and Marking rubric will be provided on the Wattle course page.

Assessment Task 4

Final exam

A 4 hour exam using the MATLAB programming environment to answer several modelling and analysis questions similar to those covered during the course. Requires the submission of MATLAB code and answers to the exam questions through the Wattle course page. Detailed instructions will be published on the Wattle course page. The exam will be held during the formal final examination period.

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.

The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.

The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.

 

The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

Individual assessment tasks may or may not allow for late submission. Policy regarding late submission is detailed below:

• Late submission not permitted. If submission of assessment tasks without an extension after the due date is not permitted, a mark of 0 will be awarded.
• Late submission permitted. Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.

Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

• ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
• ANU Access and inclusion for students with a disability or ongoing or chronic illness
• ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
• ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
• ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
• ANUSA supports and represents undergraduate and ANU College students
• PARSA supports and represents postgraduate and research students