Optimisation and Control is the study of operation and decision-making over networks. The knowledge and tools in this course can be used in various engineering domains such as communication networks, robotics, smart grids, intelligent transportation systems, biomedical engineering, and financial markets. The emphasis of this course will be on basic continuous statespace optimization theories, dynamic programming principles, linear quadratic optimal control, constrained optimal control and receding horizon control.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
- Address systematically, optimization problems in engineering and in particular continuous state-space convex programming.
- Apply numerical methods to solve complex optimization problems.
- Model and analyse network flow problems and apply dynamic programming principles to solve shortest path problems.
- Define the importance of optimality in feedback control design and derive solutions to linear quadratic optimal control.
- Design and implement receding horizon controllers based on constrained optimal control.
Indicative Assessment
- Computer Labs (5) [LO 2]
- Hardware Labs (10) [LO 1,2]
- Tutorial Assignments (20) [LO 2,3,5]
- Design Project (20) [LO 2,3,5]
- Final Exam (45) [LO 1,3,4]
The ANU uses 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. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.
Workload
Approximately 130 hours in total over the semester.
Inherent Requirements
Not applicable
Requisite and Incompatibility
Prescribed Texts
None
Assumed Knowledge
Calculus - Integration and techniques of integration. Functions of several variables - visualisation, continuity, partial derivatives and directional derivatives.Linear Algebra - theory and application of Euclidean vector spaces. Vector spaces: linear independence, bases and dimension; eigenvalues and eigenvectors; orthogonality and least squares.
Minors
Fees
Tuition fees are for the academic year indicated at the top of the page.
Commonwealth Support (CSP) Students
If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees.
- Student Contribution Band:
- 2
- Unit value:
- 6 units
If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
Where there is a unit range displayed for this course, not all unit options below may be available.
| Units | EFTSL |
|---|---|
| 6.00 | 0.12500 |
Course fees
- Domestic fee paying students
| Year | Fee |
|---|---|
| 2022 | $4740 |
- International fee paying students
| Year | Fee |
|---|---|
| 2022 | $6000 |
Offerings, Dates and Class Summary Links
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
Second Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 7344 | 25 Jul 2022 | 01 Aug 2022 | 31 Aug 2022 | 28 Oct 2022 | In Person | View |