Unit Name


Unit Code



Unit Duration

12 weeks


Graduate Diploma of Engineering (Industrial Automation)

Duration: 1 year


Master of Engineering (Industrial Automation)

Duration: 2 years

Year Level


Unit Creator/Reviewer

Dr. Srinivas Shastri /Hadi Harb





Credit Points



Grad Dip total course credit points = 24

(3 credits x 8 (units))


Masters total course credit points = 48

(3 credits x 12 (units) + 12 credits (Thesis))

Mode of Delivery

On-Campus or Online

Unit Workload

10 hours per week:

Lecture - 1 hour

Tutorial Lecture - 1 hours

Practical / Lab - 1 hour (where applicable)

Personal Study recommended - 7 hours (guided and unguided)


Unit Description and General Aims

This subject aims to provide students with an in-depth knowledge of the techniques and technologies employed in the automated control of industrial processes. The subject combines the fundamentals of process identification and feedback control design with a broad understanding of the hardware, system architectures and software techniques widely used to implement control solutions. Students will acquire the ability to analyze control problems and create solutions based on the use of modelling techniques and well-established software tools. This ability will help to prepare the students for the advanced control topics to be covered later in the course. 

Students will be able to describe the key features of control system equipment practices and their comparative investment costs as used in different sectors of industry. Control techniques for both continuous and batch process control will be covered, Students will undertake case studies to create and evaluate choices of system architectures and equipment solutions in terms of plant availability, initial cost and potential for improvements in plant performance indicators such as energy efficiency and production rates.


Learning Outcomes

On successful completion of this subject/unit, students are expected to be able to:

  1. Discriminate between the key features of industrial control systems.
    Bloom’s Level 5
  2. Apply mathematical modelling techniques to identify static and dynamic response characteristics of a continuous process.
    Bloom’s Level 5
  3. Design a feedback control system for a continuous process using transfer functions and stability analysis methods.
    Bloom’s Level 5
  4. Design a digital control system for a process using z-transform and discrete time system analysis.
    Bloom’s Level 6
  5. Design a control system for a process using Fuzzy logic.
    Bloom’s Level 6
  6. Describe and incorporate into relevant system designs the principles of batch process and manufacturing control system practices as recommended by International Standards ANSI/ISA- 88, and ANSI/ISA-95.
    Bloom’s Level 5


Bloom’s Taxonomy

The cognitive domain levels of Bloom’s Taxonomy:

Bloom’s Level

Bloom’s Category





Exhibit memory of previously learned material by recalling facts, terms, basic concepts, and answers.

Choose, Define, Find, How, Label, List, Match, Name, Omit, Recall, Relate, Select, Show, Spell, Tell, What, When, Where, Which, Who, Why



Demonstrate understanding of facts and ideas by organizing, comparing, translating, interpreting, giving descriptions, and stating main ideas.

Classify, Compare, Contrast, Demonstrate, Explain, Extend, Illustrate, Infer, Interpret, Outline, Relate, Rephrase, Show, Summarize, Translate



Solve problems to new situations by applying acquired knowledge, facts, techniques and rules in a different way.

Apply, Build, Choose, Construct, Develop, Experiment with, Identify, Interview, Make use of, Model, Organize, Plan, Select, Solve, Utilize



Examine and break information into parts by identifying motives or causes. Make inferences and find evidence to support generalizations.

Analyse, Assume, Categorize, Classify, Compare, Conclusion, Contrast, Discover, Dissect, Distinguish, Divide, Examine, Function, Inference, Inspect, List, Motive, Relationships, Simplify, Survey, Take part in, Test for, Theme



Present and defend opinions by making judgments about information, validity of ideas, or quality of work based on a set of criteria.

Agree, Appraise, Assess, Award, Choose, Compare, Conclude, Criteria, Criticize, Decide, Deduct, Defend, Determine, Disprove, Estimate, Evaluate, Explain, Importance, Influence, Interpret, Judge, Justify, Mark, Measure, Opinion, Perceive, Prioritize, Prove, Rate, Recommend, Rule on, Select, Support, Value



Compile information together in a different way by combining elements in a new pattern or proposing alternative solutions.

Adapt, Build, Change, Choose, Combine, Compile, Compose, Construct, Create, Delete, Design, Develop, Discuss, Elaborate, Estimate, Formulate, Happen, Imagine, Improve, Invent, Make up, Maximize, Minimize, Modify, Original, Originate, Plan, Predict, Propose, Solution, Solve, Suppose, Test Theory


Engineers Australia

The Australian Engineering Stage 1 Competency Standards for the Professional Engineer, approved as of 2013. This table is referenced in the mapping of graduate attributes to learning outcomes and via the learning outcomes to student assessment.

Stage 1 Competencies and Elements of Competency


Knowledge and Skill Base


Comprehensive, theory based understanding of the underpinning natural and physical sciences and the engineering fundamentals applicable to the engineering discipline.


Conceptual understanding of the mathematics, numerical analysis, statistics, and computer and information sciences which underpin the engineering discipline.


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


Discernment of knowledge development and research directions within the engineering discipline.


Knowledge of engineering design practice and contextual factors impacting the engineering discipline.


Understanding of the scope, principles, norms, accountabilities and bounds of sustainable engineering practice in the specific discipline.


Engineering Application Ability


Application of established engineering methods to complex engineering problem solving.


Fluent application of engineering techniques, tools and resources.


Application of systematic engineering synthesis and design processes.


Application of systematic approaches to the conduct and management of engineering projects.


Professional and Personal Attributes


Ethical conduct and professional accountability.


Effective oral and written communication in professional and lay domains.


Creative, innovative and pro-active demeanour.


Professional use and management of information.


Orderly management of self, and professional conduct.


Effective team membership and team leadership.


Graduate Attributes

Successfully completing this Unit will contribute to the recognition of attainment of the following graduate attributes aligned to the AQF Level 9 criteria, Engineers Australia Stage 1 Competency Standards for the Professional Engineer and the Washington Accord and the Program Level Outcomes (PLO):

Graduate Attributes / Program Level Outcomes

(Knowledge, Skills, Abilities, Professional and Personal Development)

EA Stage 1 Competencies

Learning Outcomes

A. Effective Communication (PLO 1)

A1. Cognitive and technical skills to investigate, analyse and organise information and ideas and to communicate those ideas clearly and fluently, in both written and spoken forms appropriate to the audience.

2.2, 3.2

1, 4, 5

A2. Ability to professionally manage oneself, teams, information and projects and engage effectively and appropriately across a diverse range of international cultures in leadership, team and individual roles.

2.4, 3.2, 3.4, 3.5, 3.6


B. Critical  Judgement (PLO 2)


B1. Ability to critically analyse and evaluate complex information and theoretical concepts.

1.1, 1.2, 1.3, 2.1

2, 3

B2. Ability to creatively, proactively and innovatively apply theoretical concepts, knowledge and approaches with a high level of accountability, in an engineering context.

1.5, 2.1, 3.3, 3.4

4, 5

C. Design and Problem Solving Skills (PLO 3)


C1. Cognitive skills to synthesise, evaluate and use information from a broad range of sources to effectively identify, formulate and solve engineering problems.

1.5, 2.1, 2.3


C2. Technical and communication skills to design complex systems and solutions in line with developments in engineering professional practice.

2.2, 2.3

4, 5, 6

C3. Comprehension of the role of technology in society and identified issues in applying engineering technology ethics and impacts; economic; social; environmental and sustainability.

1.5, 1.6, 3.1


D. Science and Engineering Fundamentals (PLO 4)

D1. Breadth and depth of mathematics, science, computer technology and specialist engineering knowledge and understanding of future developments.

1.1, 1.2, 1.3, 1.4

4, 5

D2. Knowledge of ethical standards in relation to professional engineering practice and research.

1.6, 3.1, 3.5


D3. Knowledge of international perspectives in engineering and ability to apply various national and International Standards.

1.5, 1.6, 2.4, 3.4


E. Information and Research Skills (PLO 5)

E1. Application of advanced research and planning skills to engineering projects.

1.4, 2.4, 3.6


E2. Knowledge of research principles and methods in an engineering context.

1.4, 1.6




Unit Content and Learning Outcomes to Program Level Outcomes (PLO) via Bloom’s Taxonomy Level

This table details the mapping of the unit content and unit learning outcomes to the PLOs and graduate attributes at the corresponding Bloom’s Taxonomy level, specified by the number in the table.


Integrated Specification /

Program Learning Outcomes






Unit Learning Outcomes





































Unit Study




















Max Bloom’s level






Total PLO coverage








Student Assessment 

Assessment Type

(e.g. Assignment - 2000 word essay (specify topic)

Examination (specify length and format))

When assessed

(e.g. After Topic 5)


(% of total unit marks)

Learning Outcomes Assessed

Assignment 1

Type: Multi-choice test / Group work / Short answer questions / Role Play / Self-Assessment / Presentation

Example Topic: To be suggested by lecturer

After Topic 6


1, 2

Assignment 2 - Project Midterm

Type: Report / Research / Paper / Case Study / Site Visit / Problem analysis / Project / Professional recommendation / Self-Assessment

(Typical report 1,500 words maximum, excluding references. This is a progress report with; literature review, hypothesis, and proposal for workings)

Example Topic: Proposal for the analysis, design and modelling of a storage tank system

After Topic 8


1, 2, 3

Assignment 3

Type: Multi-choice test / Group work / Short answer questions / Role Play / Self-Assessment / Presentation

Example Topic: To be suggested by lecturer

After Topic 11


2, 3, 4, 5, 6

Assignment 4 - Final Project (Typical thesis 4000 words, excluding references, figures and tables. If a continuation of the midterm, this should complete the report by adding sections on: workings, implementation, results, verification/validation, conclusion/challenges and recommendations/future work.)

Example Topic: A continuation of the mid-term initial submission OR a “Control Systems Planning and Design Project” will be attempted which will include for justification of the type of equipment to be used in terms of cost, ease of use and availability when compared with plant improvement objectives.

Embedded practical component: Students are to design and simulate a feedback / cascade control system using Matlab or similar software tools and include results in final project report.

Final Week


1, 2, 3, 4, 5, 6

Attendance / Tutorial Participation

Example: Presentation, discussion, group work, exercises, self-assessment/reflection, case study analysis, application.




Prescribed and recommended readings

Required textbook

  • King. Process Control - A Practical Approach, 2nd Edition. John Wiley & Sons, 2016 – ISBN: 978-1-119-15774-8
  • Altmann, D. Macdonald, Practical Process Control for Engineers and Technicians. Elsevier, 2005 – ISBN: 978-0-7506-6400-4
  • Mandal, Ajit K.. Introduction to Control Engineering - Modeling, Analysis and Design (3rd Edition). New Academic Science, 2017 – ISBN: 978-1-78183-099-4
  • Fadali, M. Sami Visioli, Antonio. Digital Control Engineering - Analysis and Design (2nd Edition). Elsevier, 2013 – ISBN: 978-0-12-394391-0


Recommended Reference Materials

  • Engineering Standard ANSI/ISA-88 Part 1 or IEC 61512-1
  • Engineering Standard ANSI/ISA-95 Part 1 or IEC 61512-1
  • Connell, Basic Math for Process Control. ISA, 2003 – ISBN: 978-1-55617-813-9 (Available on Knovel)
  • V. Dukkipati, MATLAB for Control System Engineers, 2nd Edition. New Academic Science, 2014 – ISBN: 978-1-78183-066-6
  • L. Trevathan, A Guide to the Automation Body of Knowledge, 2nd Edition. ISA, 2006 – ISBN: 978-1-55617-984-6
  • Number of journals and websites (advised during lectures).
  • Examples of journals include
    1. Journal of Process Control
    2. Control (Electronic access via ControlGlobal.com)

Unit Content:

One topic is delivered per contact week, with the exception of part-time 24-week units, where one topic is delivered every two weeks.

Topic 1

Control systems and their relationship to process operations

  1. Introduction to the purposes of industrial control systems and the role of the control system in achieving business objectives.
  2. Characteristic control system features in various industry sectors
  3. Process Variables, Manipulated Variables and Set Points
  4. Input/output relationships of typical process equipment modules: Tanks, Heat exchangers, reactors.

Topic 2

Process characteristics

  1. Process unit operations, flowcharts and the depiction of the control system.
  2. Overview of single control loops: level, temperature, pressure, and flow
  3. Linear differential equations and Introduction to process dynamics
  4. Overview of process characteristics: gain, dead time, response curve


Topic 3

First principle modelling

    1. The laws of Thermodynamics
    2. Concepts of heat and mass transfer
    3. Introduction to chemical reaction engineering
    4. First principle modelling
    5. Linearisation


Topic 4

Dynamics of continuous processes

  1. Laplace transform
  2. 1st and 2nd order processes.
  3. Transfer functions


Topic 5  

Fundamentals of feedback control

  1. Poles and zeros
  2. Transfer functions and block diagrams
  3. Feedback control overview


Topics 6

Proportional Integral Derivative Control.

  1. PID control
  2. Effect of a proportional control action on a process
  3. Effect of integral control action on a process
  4. Offset in P control


Topics 7

Analysis and design of feedback control systems
(Lab demonstrations and application software tools should be used (MATLAB Control System Toolbox) in association with this topic.

  1. Stability and dynamic behaviour of linear systems in feedback control.
  2. Design of feedback controllers
  3. Tuning feedback controllers


Topic 8

Frequency domain analysis

(Lab demonstrations and application software tools should be used (MATLAB Control System Toolbox) in association with this topic.

  1. Bode plot
  2. Bode stability criterion
  3. Nyquist stability criterion


Topic 9

Introduction to Digital Control Systems

  1. Discrete time systems
  2. Difference equations
  3. z-Transform
  4. Discretised PID controllers


Topic 10

Fuzzy Logic for Control Systems

  1. Fuzzy modelling and control
  2. Fuzzy sets and membership
  3. Fuzzy logic controllers


Topic 11

Automation system functions

  1. Introduction to safety critical control systems (Details in ME 508).
  2. Principles of batch process control based on ANSI/ISA-88/IEC 61512)
  3. Introduction to Enterprise-Control System Integration (ANSI/ISA-95/IEC 62264)
  4. Human factors and ergonomic design


Topic 12

Project and Course Review

In the final week students will have an opportunity to review the contents covered so far. Opportunity will be provided for a review of student work, to clarify any outstanding issues, and to work on finalising the major assessment report.


Software/Hardware Used


  • Software: Matlab (Toolboxes: Control System Toolbox, System Identification Toolbox, Statistics and Machine Learning Toolbox, Model Predictive Control Toolbox)
  • Version: R2019a
  • Instructions: Install the Student version on your computer OR use the software on Remote lab
  • Additional resources or files: N/A



  • N/A