Course Title: Real Time Estimation and Control

Part A: Course Overview

Course Title: Real Time Estimation and Control

Credit Points: 12.00


Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

EEET2221

City Campus

Undergraduate

125H Electrical & Computer Engineering

Face-to-Face

Sem 2 2006,
Sem 2 2007,
Sem 2 2010,
Sem 2 2012,
Sem 2 2014,
Sem 2 2015,
Sem 2 2016

EEET2223

City Campus

Postgraduate

125H Electrical & Computer Engineering

Face-to-Face

Sem 2 2006,
Sem 2 2007,
Sem 2 2010,
Sem 2 2012,
Sem 2 2014,
Sem 2 2015,
Sem 2 2016

Course Coordinator: Professor Liuping Wang

Course Coordinator Phone: +61 3 992 52100

Course Coordinator Email: liuping.wang@rmit.edu.au

Course Coordinator Location: 10.8.8


Pre-requisite Courses and Assumed Knowledge and Capabilities

EEET2109 Control Systems or equivalent courses


Course Description

This course is prepared for the fourth year students or Masters degree students in the engineering field in large. It is particularly suitable if you are studying electrical engineering, electronic engineering, communication engineering, aerospace engineering, and mechanical engineering. It is to familiarise you with the model predictive control technologies that include multivariable control systems, constrained control and process optimization.

Please note that if you take this course for a bachelor honours program, your overall mark in this course will be one of the course marks that will be used to calculate the weighted average mark (WAM) that will determine your award level. (This applies to students who commence enrolment in a bachelor honours program from 1 January 2016 onwards. See the WAM information web page for more information (www1.rmit.edu.au/browse;ID=eyj5c0mo77631).


Objectives/Learning Outcomes/Capability Development

At undergraduate level this course develops the following Program Learning Outcomes:

1.3 In-depth understanding of specialist bodies of knowledge within the engineering discipline.

2.1 Application of established engineering methods to complex engineering problem solving.

2.2 Fluent application of engineering techniques, tools and resources

At postgraduate level this course develops the following Program Learning Outcomes:

  • High levels of technical competence in the field
  • Be able to apply problem solving approaches to work challenges and make decisions using sound engineering methodologies


Learning Outcomes

  • To introduce advanced topics in discrete time systems, multivariable control systems, constrained control and process optimization, leading to skills in system simulation, multivariable control system design and analysis, and practical implementation of control systems.
  • Well developed oral and written communications.
  • Good teamwork
  • Independent and lifelong learning
     


Overview of Learning Activities

  • Reading text books
  • Attending lectures
  • Participating in tutorials
  • participating in laboratory activities


Overview of Learning Resources

The course will be based on the textbook ’Model predictive control system design and implementation using MATLAB’  by Liuping Wang.

The textbook is free to RMIT students and it can be downloaded through the link below.

The link is: https://login.ezproxy.lib.rmit.edu.au/login?url=http://dx.doi.org/10.1007/978-1-84882-331-0
This takes you straight to the electronic copy of the textbook, so you can download it for free.

The weblink includes EzProxy as part of the string, so when off campus, you will be taken to a login screen first, then to SpringerLink.


Overview of Assessment

  • There will be one final open book, mini-project based assessment (4 hrs) covering the whole course in November.
  • There will be one open- book mid- term test in week 6.
  • There will be one medium sized assignment in week 8.
  • There will be one laboratory report and attendance marking.