Linear Systems Theory

Subject ELEN90027 (2016)

Note: This is an archived Handbook entry from 2016.

Credit Points: 12.5
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2016:

Semester 1, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period 29-Feb-2016 to 29-May-2016
Assessment Period End 24-Jun-2016
Last date to Self-Enrol 11-Mar-2016
Census Date 31-Mar-2016
Last date to Withdraw without fail 06-May-2016

Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: 36 hours of lectures
Total Time Commitment:

200 hours


Enrolment in a research higher degree (MPhil or PhD) in Engineering



Recommended Background Knowledge:


Non Allowed Subjects:


Core Participation Requirements:

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website:


Prof Michael Cantoni


Prof Dragan Nesic


Subject Overview:


This subject provides a rigorous introduction to the mathematical tools commonly employed in the analysis of linear dynamical systems. Such system models arise across science and engineering. This subject is intended for research higher-degree students in engineering.


Topics include:

Linear Analysis - vector, normed and inner-product spaces, Banach and Hilbert spaces, linear operators, and matrix analysis; Sate-space models - input-output behaviour, reachability, observability, balanced truncation; coprime factorization Feedback control systems - internal stability, all stabilizing controllers Optimal filtering and control - quadratic measures of performance (H2 and Hinfinity); spectral factorization methods; Riccati equations

Learning Outcomes:


Having completed this subject it is expected that the student be able to:

  1. Rigorously apply the mathematics of linear analysis to characterize and approximate the behaviour systems
  2. Employ state-space methods to analyze and design linear feedback control systems
  3. Formulate and solve optimal linear filtering and control problems
  • Continuous assessment of homework assignments, not exceeding 40 pages in total over the semester (approximately 55-60 hours of work), worth 40%
  • One written examination at the end of semester, worth 60%.

Hurdle requirement: Students must pass the end of semester examination to pass the subject.

Intended Learning Outcomes (ILO's) 1 to 3 are assessed in the final written exam and through submitted homework assignments.

Prescribed Texts:


Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:

On completion of this subject, students will have developed the following skills:

  • Ability to apply knowledge of basic science and engineering fundamentals
  • In-depth technical competence in at least one engineering discipline
  • Ability to undertake problem identification, formulation and solution
  • Ability to utilise a systems approach to design and operational performance
  • Expectation of the need to undertake lifelong learning, capacity to do so
  • Capacity for independent critical thought, rational inquiry and self-directed learning
  • Profound respect for truth and intellectual integrity, and for the ethics of scholarship.


This subject is delivered through lectures and homework assignments.


Students are provided with lecture notes, including worked examples, assignment problems, and recommended reading lists comprising textbooks and journal articles.


Exposure to research literature and the rigour expected at the level of postgraduate study.

Related Course(s): Doctor of Philosophy - Engineering
Master of Philosophy - Engineering

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