ADVANCED PROCESS CONTROL
Master of Engineering (Industrial Automation) Duration: 2 years
Dr. Srinivas Shastri
ME503 Industrial Process Control Systems
Masters total course credit points = 48
(3 credits x 12 (units) + 12 credits (Thesis))
Mode of Delivery
On-Campus or Online
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
The subject quickly moves from a review of process control fundamentals to multivariable control where the student will gain a deep understanding of the key principles ranging from nature of multivariable systems, process models to interaction analysis, loop pairing and relative gain arrays. The student is then exposed to a detailed review of digital process control and its application. A detailed examination is then performed of model predictive control ranging from dynamic matrix control, model algorithm control to design concepts. An in-depth application of statistical process control with advanced process control is then undertaken. The course is concluded by a study of advanced topics in process control with an emphasis on the application of the technologies.
On successful completion of this subject/unit, students are expected to be able to:
Demonstrate a deep understanding of process control fundamentals
Bloom’s Level 5
Apply key principles of multivariable control in a range of contexts
Bloom’s Level 5
Demonstrate a thorough understanding and application of digital process control as compared to the older analogue forms
Bloom’s Level 5
Assess applications for and be able to apply model predictive control within a variety of contexts
Bloom’s Level 6
Justify and be able to apply statistical process control at an advanced level
Bloom’s Level 6
Demonstrate an in-depth understanding of advanced process control across a wide variety of contexts
Bloom’s Level 5
The cognitive domain levels of Bloom’s Taxonomy:
Recall, define and list facts, concepts, methods, terminologies, theories and structures.
Demonstrate understanding by comparing, organizing, describing, translating, interpreting, paraphrasing, explaining and distinguishing.
Use knowledge to solve problems, identify connections and show relationships, in context.
Examine information, breakdown a problem, determine relationships and causes, make inferences, classify and infer from evidence.
Produce a pattern from relationships, propose operations, formulate a design, compose a hypothesis, reassemble information, construct, plan, invent, predict
Make judgements based on evidence and external criteria, determine best practice, optimise, validate ideas, judge and critique, assess, valuate and
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.
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
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.
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,
B. Critical Judgement (PLO 2)
B1. Ability to critically analyse and evaluate complex information and theoretical concepts.
1.1, 1.2, 1.3,
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,
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.
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,
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,
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.
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
Max Bloom’s level
Total PLO coverage
(e.g. Assignment - 2000 word essay (specify topic) Examination (specify length and format))
When assessed (e.g. Week 5)
Weighting (% of total unit marks)
Learning Outcomes Assessed
Type: Multi-choice test / Group work / Short answer questions / Role Play / Self-Assessment / Presentation
Example Topic: on “a proposed application of types of PID controllers, methods of tuning, dealing with dead time for a particular plant arrangement” AND/OR “Multivariable application with detailed discussion on process models employed, controller design procedure.”
Assignment 2 - Project Midterm
Type: Report / Research / Paper / Case Study / Site Visit / Problem analysis / Project / Professional recommendation
(Typical report 2,500 words maximum, excluding references. This Project will include a progress report; literature review, hypothesis, and proposed solution with concept workings)
Example Topic: on “Selection and application of different control strategies from fundamental PID, multivariable control and model predictive control for a plant proposed by the lecturer)”
Assignment 3 - Final Project
Type: Report (Final Project)
(Typical thesis 5,000 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.) Continuing the mid- term initial submission.
Example: May be in the form of quizzes, class tests, practical assessments, remote labs, simulation software or case studies
Attendance / Tutorial Participation
Example: Presentation, discussion, group work, exercises, self-assessment/reflection, case study analysis, application.
Prescribed and recommended readings
Process Control: Theory and Applications by Jean-Pierre Corriou ISBN 185-233-7761
Terrence Blevins,T., Wojsznis, W.K. & Nixon, M. (2012) Advanced Control Foundation: Tools, Techniques, and Applications. Industrial Society for Automation. Raleigh, USA. ISBN 978- 1937560553
The Control Handbook (Electrical Engineering Handbook), 1996 by William S. Levine (Editor) ISBN-13: 978-0849385704
Number of peer-reviewed journals and websites (advised during lectures). Some examples are listed below.
Perry’s Chemical Engineers Handbook, 8th edition, McGraw Hill (earlier editions are acceptable)
IEEE Transactions on Automatic Control
IEEE Transactions on Automation Science and Engineering
IEEE Transactions on Instrumentation and Measurement
IEEE Instrumentation and Measurement Magazine
Automation World Magazine
Manufacturing Automation Magazine
IDC notes and Reference texts as advised.
Other material advised during the lectures
One topic is delivered per contact week, with the exception of part-time 24-week units, where one topic is delivered every two weeks.
Topics 1 and 2
Review of process control fundamentals
Types of controllers
Topics 3 and 4
Introduction to multivariable control
The nature of multivariable systems
Multivariable transfer functions
Closed-loop dynamic analysis
Interaction analysis and loop pairing
Relative Gain Array
Controller Design Procedure
Topics 5, 6 and 7
Digital (computerised) process control
Sampling and conditioning of continuous signals
Continuous signal reconstruction
Discrete time systems
Concepts of z-Transforms
Pulse transfer functions
Digital controller and its design
Digital multivariable controllers
Topics 8 and 9
Model predictive control
Dynamic matrix control
Model algorithm control
Nonlinear model predictive control
Statistical process control
Introduction to SPC
1. Depending on the cohort and/or the interests of the students advanced topics will be discussed during this period. Where possible, industry experts will be invited to share their experiences with students. Applications of advanced process control will be examined in a variety of different contexts from mining, oil and gas to processing. Challenges such the implementation of good control in the absence of good measurements would be an example of a special topic. Students will also be introduced to concepts of Fuzzy control.
Project and/or Unit 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.