• Offered by RS Electrical, Energy and Materials Engineering
  • ANU College ANU College of Engineering and Computer Science
  • Course subject Engineering
  • Areas of interest Engineering
  • Academic career PGRD
  • Course convener
    • Prof Ian Petersen
  • Mode of delivery In Person
  • Offered in Second Semester 2019
    See Future Offerings

This course introduces students to recently developed and advanced techniques for solving complex control problems. The course presents theory and methodology for analysis and modelling of systems and signals, and methods for design and synthesis of feedback controllers. The emphasis of this course will be on robust control and optimal control of dynamical systems. 

Learning Outcomes

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

Upon successful completion of this course, students will be able to:
  1. Define and explain the basic properties of multivariable linear systems such as controllability, observability, and transfer functions.
  2. Describe and evaluate nonlinear dynamical systems and apply linearization techniques when appropriate
  3. Compute signal norms and system gains to evaluate and compare dynamic systems
  4. Derive linear quadratic optimal controllers for scalar systems, and evaluate how design parameters influence the closed-loop system properties.
  5. Formulate solutions to linear H-infinity optimal control.
  6. Explain and discuss the basic principles behind model-predictive control, including how the design parameters influence the closed-loop performance.
  7. Design and assess model-predictive controllers for real-world dynamical systems.

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

Indicative Assessment

Problem sets 20%, Hardware lab report 10%, Computer lab 5%, Project report 15%, Project presentation 10%, Final exam 40%

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

12 × 2 hr Lectures, 2 × 3 hr Labs, 6 × 2 hr Tutorials

Requisite and Incompatibility

To enrol in this course you must be studying a Master of Engineering, and have completed ENGN3223 or ENGN6223 or an equivalent course in control systems.

Assumed Knowledge

Mathematics including differential equations, complex numbers and Laplace transforms, matrices, Physics including classical mechanics and electrical circuits.

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
2019 $4320
International fee paying students
Year Fee
2019 $5700
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

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
9195 22 Jul 2019 29 Jul 2019 31 Aug 2019 25 Oct 2019 In Person N/A

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