• Offered by RS Electrical, Energy and Materials Engineering
  • ANU College ANU College of Engineering and Computer Science
  • Course subject Engineering

This course will only be offered from 2022

Network 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:

  1. Address systematically, optimization problems in engineering and in particular continuous state-space convex programming.
  2. Apply numerical methods to solve complex optimization problems.
  3. Model and analyse network flow problems and apply dynamic programming principles to solve shortest path problems.
  4. Define the importance of optimality in feedback control design and derive solutions to linear quadratic optimal control.
  5. Design and implement receding horizon controllers based on constrained optimal control.

Indicative Assessment

  1. Computer Labs (5) [LO null]
  2. Hardware Labs (10) [LO null]
  3. Tutorials (20) [LO null]
  4. Design Porject (20) [LO null]
  5. Final Exam (45) [LO null]

In response to COVID-19: Please note that Semester 2 Class Summary information (available under the classes tab) is as up to date as possible. Changes to Class Summaries not captured by this publication will be available to enrolled students via Wattle. 

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.

Inherent Requirements

Not applicable

Requisite and Incompatibility

To enrol in this course you must have successfully completed ENGN2228 and either MATH1013 or MATH1014.

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.  

If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Student Contribution Band:
2
Unit value:
6 units

If you are an undergraduate student and 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). You can find your student contribution amount for each course 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
Domestic fee paying students
Year Fee
2020 $4320
International fee paying students
Year Fee
2020 $5760
Note: Please note that fee information is for current year only.

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.

The list of offerings for future years is indicative only.
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 N/A

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