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The current and official versions of the course specifications are available on the web at http://www.usq.edu.au/course/specification/current.
Please consult the web for updates that may occur during the year.

ELE3105 Computer Controlled Systems

Semester 1, 2019 Online
Short Description: Computer Controlled Systems
Units : 1
Faculty or Section : Faculty of Health, Engineering and Sciences
School or Department : School of Mechanical and Electrical Engineering
Student contribution band : Band 2
ASCED code : 031399 - Electrical, Electronic Enginee
Grading basis : Graded

Staffing

Examiner: Paul Wen

Requisites

Pre-requisite: ELE2103 or Students must be enrolled in one of the following Programs: GCNS or GCEN or GDNS or MEPR or MENS or METC

Synopsis

To apply control to any 'real' problem, it is first necessary to express the system to be controlled in mathematical terms. The 'state space' approach is taught both for expressing the system dynamics and for analysing stability both before and after feedback is applied. These concepts involve revision and extension of matrix manipulation and the solution of differential equations. By defining a time-step to be small, these state equations give a means of simulating the system and its controller for both linear and nonlinear cases. Many of the implementations of on-line control now involve a computer, which applies control actions at discrete intervals of time rather than continuously. It is shown that discrete-time state equations can be derived which have much in common with the continuous ones. Simulation does not then rely on a very small time step. The operator 'z' is first introduced with the meaning of 'next', resulting in a higher order difference equation to represent the system, then shown to be a parameter in the infinite series which is summed to form a 'z- transform'. It is shown that the discrete-time transfer function in z can be derived from the Laplace transform of the continuous system, with additional terms to represent the zero order hold of the DAC. Analysis of stability in terms of the roots of a characteristic equation are seen to parallel the continuous methods and techniques of pole assignment and root locus are also seen to correspond. Techniques are presented for synthesising transfer functions by means of a few lines of computer code, to make stable control possible for systems which would be unstable with simple feedback.

Objectives

The course objectives define the student learning outcomes for a course. On completion of this course, students should be able to:

  1. design of a computer control feedback loop, including algorithms in software;
  2. analysis and simulation of control systems using state space methods; and
  3. design of systems in which the controllers have dynamics implemented in software.

Topics

Description Weighting(%)
1. Use of the Z-transform for analysis and design of computer control loops 15.00
2. Representation of discrete time dynamics in software 10.00
3. Discrete time state equations and stability analysis 10.00
4. Controller design and 'tuning' with controller dynamics, PID 15.00
5. Pole assignment, root locus and other methods in the complex plane 10.00
6. Derivation of state equations 10.00
7. Modelling and simulation by computer 10.00
8. Matrix analysis of continuous linear systems and controllers 15.00
9. Concepts of controllability and observability 5.00

Text and materials required to be purchased or accessed

ALL textbooks and materials available to be purchased can be sourced from USQ's Online Bookshop (unless otherwise stated). (https://omnia.usq.edu.au/textbooks/?year=2019&sem=01&subject1=ELE3105)

Please contact us for alternative purchase options from USQ Bookshop. (https://omnia.usq.edu.au/info/contact/)

Nise, NS 2014, Control systems engineering, 7th edn, Wiley, Hoboken, NJ.
MATLAB Student Edition, Version 7.0 (or later).

Reference materials

Reference materials are materials that, if accessed by students, may improve their knowledge and understanding of the material in the course and enrich their learning experience.
Dorf, RC & Bishop, RH 2016, Modern control systems, 13th edn, Pearson Prentice Hall, Upper Saddle River, NJ.
Ogata, K 2010, Modern control engineering, 5th edn, Pearson, Boston, MA.
Ogata, K 2012, Discrete-time control systems, 2nd edn, Prentice Hall, Englewood Cliffs, NJ.

Student workload expectations

Activity Hours
Assessments 36.00
Directed Study 52.00
Examinations 2.00
Private Study 65.00

Assessment details

Description Marks out of Wtg (%) Due Date Objectives Assessed Notes
ASSIGNMENT 1 200 20 16 Apr 2019 1,3
Assignment 2 200 20 04 Jun 2019 2,3
Restricted Exam 600 60 End S1 1,2,3 (see note 1)

Notes
  1. Student Administration will advise students of the dates of their examinations during the semester.

Important assessment information

  1. Attendance requirements:
    There are no attendance requirements for this course. However, it is the students' responsibility to study all material provided to them or required to be accessed by them to maximise their chance of meeting the objectives of the course and to be informed of course-related activities and administration.

  2. Requirements for students to complete each assessment item satisfactorily:
    To satisfactorily complete an assessment item a student must achieve at least 50% of the marks or a grade of at least C-. Students do not have to satisfactorily complete each assessment item to be awarded a passing grade in this course. Refer to Statement 4 below for the requirements to receive a passing grade in this course.

  3. Penalties for late submission of required work:
    Students should refer to the Assessment Procedure http://policy.usq.edu.au/documents.php?id=14749PL (point 4.2.4)

  4. Requirements for student to be awarded a passing grade in the course:
    To be assured of receiving a passing grade a student must obtain at least 50% of the total weighted marks available for the course (i.e. the Primary Hurdle), and have satisfied the Secondary Hurdle (Supervised), i.e. the end of semester examination by achieving at least 40% of the weighted marks available for that assessment item.

    Supplementary assessment may be offered where a student has undertaken all of the required summative assessment items and has passed the Primary Hurdle but failed to satisfy the Secondary Hurdle (Supervised), or has satisfied the Secondary Hurdle (Supervised) but failed to achieve a passing Final Grade by 5% or less of the total weighted Marks.

    To be awarded a passing grade for a supplementary assessment item (if applicable), a student must achieve at least 50% of the available marks for the supplementary assessment item as per the Assessment Procedure http://policy.usq.edu.au/documents/14749PL (point 4.4.2).

  5. Method used to combine assessment results to attain final grade:
    The final grades for students will be assigned on the basis of the weighted aggregate of the marks (or grades) obtained for each of the summative assessment items in the course.

  6. Examination information:
    Candidates are only allowed to access specific materials during a Restricted Examination. The only materials that candidates may use in the restricted examination for this course are:
    i. writing materials (non-electronic and free from material which could give the student an unfair advantage in the examination);
    ii. calculators which cannot hold textual information (students must indicate on their examination paper the make and model of any calculator(s) they use during the examination);

  7. Examination period when Deferred/Supplementary examinations will be held:
    Any Deferred or Supplementary examinations for this course will be held during the next examination period.

  8. University Student Policies:
    Students should read the USQ policies: Definitions, Assessment and Student Academic Misconduct to avoid actions which might contravene University policies and practices. These policies can be found at http://policy.usq.edu.au.

Assessment notes

  1. Students must familiarise themselves with the USQ Assessment Procedures (http://policy.usq.edu.au/documents.php?id=14749PL).

  2. Referencing in Assignments must comply with the Harvard (AGPS) referencing system. This system should be used by students to format details of the information sources they have cited in their work. The Harvard (APGS) style to be used is defined by the USQ library’s referencing guide. These policies can be found at http://www.usq.edu.au/library/referencing

Other requirements

  1. A basic familiarity with a programming language or MATLAB is assumed.