Last Updated S022021

MPE505

Unit Name Process Dynamics and Control
Unit Code MPE505
Unit Duration 1 Semester
Award

Master of Engineering (Chemical and Process)

Duration 2 years    

Graduate Certificate in Chemical and Process Engineering

Duration 6 months

Year Level One
Unit Creator / Reviewer N/A
Core/Elective: Core
Pre/Co-requisites Nil
Credit Points

3

Mode of Delivery Online 
Unit Workload

10 hours per week:10 hours per week:

Lecture - 1 hourTutorial Lecture - 1 hours

Practical / Lab - 1 hour (where applicable)

Personal Study recommended - 7 hours (guided and unguided)

Unit Description and General Aims

Process dynamics and control relate to the architectures, mechanisms, and algorithms for maintaining the output of a specific process within a desired range. These disciplines are extensively used in industry to enable mass production of consistent products from continuously operated processes such as oil refining, paper manufacturing, chemicals, power plants and many others.

The study within this unit encompasses a review of process control fundamentals through to multivariable control – including the nature of multivariable systems, process models, interaction analysis, loop pairing, and relative gain arrays. Digital process control and its applications, model predictive control, dynamic matrix control, and model algorithm control are likewise examined in detail.

Students are then guided through an in-depth application of statistical process control with advanced process control, and this unit concludes with a study of advanced topics in process control with an emphasis on the application of the technologies.

At the conclusion of this unit, students will have been imparted with the requisite knowledge to comprehend, manage, and resolve issues within detailed process dynamics and control systems.

Learning Outcomes

On successful completion of this Unit, students are expected to be able to:

  1. Demonstrate thorough knowledge of process control fundamentals.
  2. Apply key principles of multivariable control in a range of contexts.
  3. Demonstrate a detailed understanding and application of digital process control.
  4. Assess applications suitable for model predictive control and apply them.
  5. Select and justify statistical process control applications.
  6. Comprehend and appreciate how new control technologies are assisting industries to solve complex problems.

Student assessment

 

Assessment Type

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

Examination (specify length and format))

When assessed

(eg Week 5)

Weighting

(% of total unit marks)

Learning Outcomes Assessed

Assessment 1

Type: Multi-choice test

Word length: n/a

Topic: Fundamental concepts of process control, including multivariable control [This topic could change as determined by the lecturer].

Week 6

20%

1, 2, 3

Assessment 2

Type: Report (Midterm Project)

[This will include a progress report; literature review, hypothesis, and methodology / conclusions]

Word length: 1500

Topic: Select, justify and apply control strategies (PID/ multivariable/ model predictive) for plant assigned by the lecturer.

Week 9

25%

1 – 5

Assessment 3

Type: Report (Final Project)

[If a continuation of the midterm, this should complete the report by adding sections on: methodology, implementation / evaluation, verification / validation, conclusion / challenges and recommendations / future work. If this is a new report, all headings from the midterm and the final reports must be included.]

Word length: 4000

Topic: To be determined by each student in consultation with the lecturer.

Week 12

35%

1 – 6

Practical Participation (online/simulation)

Natural gas is readily available is Australia. Analyse why new downstream petrochemical process plants are not being built in Australia.

Continuous

15%

5, 6

Attendance

Continuous

5%        

1 – 6

Prescribed and Recommended readings

Suggested Textbook

  • Jean-Pierre Corriou, Process Control: Theory and Applications, Springer, 2004. (ISBN: 978-1-4471-3848-8)

  • Babatunde A. Ogunnaike, W. Harmon Ray, Process Dynamics, Modelling and Control, Oxford University Press, 1994. (ISBN: 0-19-509119-1)

 

Reference Materials

  • A number of peer-reviewed journals and websites as advised below (and during lectures):

    1. King M., Process Control: A Practical Approach, John Wiley & Sons Ltd, 2011. (ISBN: 978-0470975879);
    2. Terrence Blevins, Willy K. Wojsznis and Mark Nixon, Advanced Control Foundation: Tools, Techniques, and Applications MOBI, ISA, 2013. (ISBN: 978-1-937560-55-3);
    3. Continillo G, Crescitelli Sivestro, Giona M, Nonlinear Dynamics and Control in Process Engineering – Recent Advances, Springer, 2016. (ISBN: 978-88-470-2208-9);
    4. Lindgren,T. Gustafsson, H. Forsgren, D. Johansson and J. Östensson, Model predictive control of the chip level in a continuous pulp digester – A case study, Pulp & Paper Canada (2005);
    5. Joe Chircoski, Mario Leclerc, Laurier Morissette, Improved continuous digester controls using wood chip analyser at Zellstoff-Celgar, (2012);
    6. James B Rawlings, David Q Mayne, Model Predictive Control: Theory and Design, Nobb Hill Publishing, 2016. (ISBN: 978-0-9759377-3-0); and,
    7. Other material to be advised during the lectures.

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 & 2

Review of Process Plant Unit Operation and Process Control Fundamentals

  1. Process plant unit operation, process flow diagrams, material flows and balances
  2. Linear differential equations and process dynamics
  3. Mathematical Modelling – Analytical, Statistical, Neural Network
  4. Examples of mathematical models
  5. Control elements and types of controllers
  6. Nonlinear systems

Topic 3 & 4

System Dynamics, Manual and Automatic Control

  1. Proportional, integral and derivative systems
  2. First, Second and higher order systems
  3. Pure delay system and equivalent to first order with time delay system
  4. Manual/ Automatic control
  5. Steady state and dynamics of control systems
  6. Stability and instability of controlled process and control systems
  7. Performance of the control system

Topic 5 & 6

Single-Loop and Multivariable Process Control

  1. Feedback control systems and conventional feedback controller design
  2. Design of more complex control systems
  3. Controller design for non-linear systems
  4. Model based control
  5. Introduction to multivariable systems
  6. Design of multivariable controllers

Topic 7 & 8

Model Predictive and Statistical Process Control

  1. Dynamic matrix control
  2. Model based algorithmic control
  3. Non-linear model predictive control
  4. Introduction to Statistical Process Control
  5. Multivariable techniques
  6. Regression analysis/ process monitoring tools

Topic 9, 10 & 11

Process Control Systems – Case Studies

  1. Control of distillation columns
  2. Control of packed bed reactors
  3. Control of a polymerization process
  4. Kamyr pulp digester control with reliable bin level measurements
  5. CFD simulation of stirred vessel reactors
  6. Modelling of reaction-diffusion processes in ore-leaching with non-linear kinetics
  7. Dynamics and control of forced-unsteady-state catalytic combustors
  8. Integrated batch control
  9. Towards a joint process and control design for batch processes: Application to semi-batch polymer reactors

 

 

 

Topic 12

Project and 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 and to clarify any outstanding issues.  Instructors/facilitators may choose to cover a specialised topic if applicable to that cohort.

Software/Hardware Used

Software

  •  Additional resources or files: N/A

Hardware

  • Hardware: N/A