Engineering Institute of Technology

 

Unit Name

ANALYSIS AND MODELLING OF DYNAMIC SYSTEMS

Unit Code

BIA 209S

 

Unit Duration

1 Term (2 Terms for 24 week delivery*)

Award

Bachelor of Science (Engineering) Duration 3 years

Year Level

Two

Unit Creator/Reviewer

 

Core/Sub-discipline

Sub-discipline

Pre/Co-requisites

 

BSC202C, BIA108S

Credit Points

3

 

Total Program Credit Points 81 (27 x 3)

Mode of Delivery

Online or On-campus

Unit Workload

(Total student workload including “contact hours” = 10 hours per week; 5 hours per week for 24 week delivery)

Pre-recordings / Lecture – 1.5 hours (0.75 hours for 24 week delivery)

Tutorial – 1.5 hours

(0.75 hours for 24 week delivery)

Guided labs / Group work / Assessments – 2 hours (1 hour for 24 week delivery)

Personal Study recommended – 5 hours (2.5 hours for 24 week delivery)

 

  • This unit may be delivered over 24 weeks (2 Terms) because the nature of the content is deemed suitable (from a pedagogical perspective) for a longer duration than the standard 12 week (1 Term). In addition, these 24-week duration Units require half the student workload hours, 5 hours per week, which allows the total load to be kept at 15 hours per week when combined with a typical 10 hours per week, 12-week Unit. EIT has extensive data to demonstrate that if the load is higher than 15 hours per week the attrition rate for part time students dramatically increases.

    Unit Description and General Aims

    The objective in presenting this unit is to provide students with the essential skills for identifying and analysing the characteristics of physical processes that are to be managed or constrained by control systems, and to provide the theoretical basis for the design of feedback control systems.

    The subject matter covered in this unit will include an introduction to the principles of: mathematical modelling of simple dynamic systems that are widely used to represent physical and chemical process operations; block diagram modelling with transfer functions using Laplace transforms; frequency and time domain analysis methods for the identification of dynamic lags in typical processes; and, classical feedback control models with a review of methods for determining stability of controllers and suitable loop gains and compensation parameters.

     

    Learning Outcomes

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

    1. Interpret and recognize the mathematical basis of 1st and 2nd order dynamic systems, and demonstrate by example the characteristic responses to disturbances.

    2. Explain and apply the principles of block diagram modelling using Laplace transforms in transfer functions.

    3. Design block diagram versions of feedback control applications and evaluate them for stability of control using Nyquist and Root locus plots.

    4. Apply industry standard software tools to expedite design of a single loop control system.

    5. Apply advanced process controls.

    6. Evaluate and discuss the impact of non-linearity in typical industrial control systems.

Professional Development

Completing this unit may add to students professional development/competencies by:

  1. Fostering personal and professional skills and attributes in order to:

    1. Conduct work in a professionally diligent, accountable and ethical manner.

    2. Effectively use oral and written communication in personal and professional domains.

    3. Foster applicable creative thinking, critical thinking and problem solving skills.

    4. Develop initiative and engagement in lifelong learning and professional development.

    5. Enhance collaboration outcomes and performance in dynamic team roles.

    6. Effectively plan, organise, self-manage and manage others.

    7. Professionally utilise and manage information.

    8. Enhance technologist literacy and apply contextualised technologist skills.

  2. Enhance investigatory and research capabilities in order to:

    1. Develop an understanding of systematic, fundamental scientific, mathematic principles, numerical analysis techniques and statistics applicable to technologists.

    2. Access, evaluate and analyse information on technologist processes, procedures, investigations and the discernment of technologist knowledge development.

    3. Foster an in-depth understanding of specialist bodies of knowledge, computer science, engineering design practice and contextual factors applicable to technologists.

    4. Solve basic and open-ended engineering technologist problems.

    5. Understand the scope, principles, norms, accountabilities and bounds associated with sustainable engineering practice.

  3. Develop engineering application abilities in order to:

    1. Apply established engineering methods to broadly-defined technologist problem solving.

    2. Apply engineering technologist techniques, tool and resources.

    3. Apply systematic technologist synthesis and design processes.

    4. Systematically conduct and manage technologist projects, work assignments, testing and experimentation.

Engineers Australia

The Australian Engineering Stage 1 Competency Standards for Engineering Technologists, 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

1.

Knowledge and Skill Base

1.1

Systematic, theory based understanding of the underpinning natural and physical sciences and the engineering fundamentals applicable to the technology domain.

1.2

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

1.3

In-depth understanding of specialist bodies of knowledge within the technology domain.

1.4

Discernment of knowledge development within the technology domain.

1.5

Knowledge of engineering design practice and contextual factors impacting the technology domain.

1.6

Understanding of the scope, principles, norms, accountabilities and bounds of sustainable engineering practice in the technology domain.

2.

Engineering Application Ability

2.1

Application of established engineering methods to broadly-defined problem solving within the technology domain.

2.2

Application of engineering techniques, tools and resources within the technology domain.

2.3

Application of systematic synthesis and design processes within the technology domain.

2.4

Application of systematic approaches to the conduct and management of projects within the technology domain.

3.

Professional and Personal Attributes

3.1

Ethical conduct and professional accountability.

3.2

Effective oral and written communication in professional and lay domains.

3.3

Creative, innovative and pro-active demeanour.

3.4

Professional use and management of information.

3.5

Orderly management of self and professional conduct.

3.6

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 7 criteria, Engineers Australia Stage 1 Competency Standards for Engineering Technologists and the Sydney Accord:

 

Graduate Attributes

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

EA Stage 1 Competencies

Learning Outcomes

A. Knowledge of Science and Engineering Fundamentals

A1. Breadth of knowledge of engineering and systematic, theory-based understanding of underlying principles, and depth of knowledge across one or more engineering sub- disciplines

 

1.1, 1.3

 

1, 2, 3, 5

A2. Knowledge of mathematical, statistical and computer sciences appropriate for engineering technology

 

1.2

 

1, 2, 3

A3. Discernment of knowledge development within the technology domain

1.4

5, 6

A4. Knowledge of engineering design practice and contextual factors impacting the technology domain

 

1.5

 

B. Problem Solving, Critical Analysis and Judgement

B1. Ability to research, synthesise, evaluate and innovatively apply theoretical concepts, knowledge and approaches across diverse engineering technology contexts to effectively solve engineering problems

 

1.4, 2.1, 2.3

 

3, 5

B2. Technical and project management skills to design complex systems and solutions in line with developments in engineering technology professional practice

 

2.1, 2.2, 2.3, 3.2

 

C. Effective Communication

C1. 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

 

3.2

 

1, 2, 4, 5

C2. Ability to engage effectively and appropriately across a diverse range of cultures

3.2

 

D. Design and Project Management

D1. Apply systematic synthesis and design processes within the technology domain

2.1, 2.2, 2.3

 

D2. Apply systematic approaches to the conduct and management of projects within the technology domain

 

2.4

 

4, 5

E. Accountability, Professional and Ethical Conduct

E1. Innovation in applying engineering technology, having regard to ethics and impacts including economic; social; environmental and sustainability

 

1.6, 3.1, 3.4

 

E2. Professional conduct, understanding and accountability in professional practice across diverse circumstances including team work, leadership and independent work

 

3.3, 3.4, 3.5, 3.6

 

5, 6

Unit Competency and Learning Outcome Map

This table details the mapping of the unit graduate attributes to the unit learning outcomes and the Australian Engineering Stage 1 Competency Standards for the Engineering Technologist.

 

 

 

Graduate Attributes

A1

A2

A3

A4

B1

B2

C1

C2

D1

D2

E1

E2

 

Engineers Australia Stage 1 Competency Standards for Engineering Technologist

1.1

 

 

 

 

 

 

 

 

 

 

 

1.2

 

 

 

 

 

 

 

 

 

 

 

1.3

 

 

 

 

 

 

 

 

 

 

 

1.4

 

 

 

 

 

 

 

 

 

 

1.5

 

 

 

 

 

 

 

 

 

 

 

1.6

 

 

 

 

 

 

 

 

 

 

 

2.1

 

 

 

 

 

 

 

 

 

2.2

 

 

 

 

 

 

 

 

 

 

2.3

 

 

 

 

 

 

 

 

 

2.4

 

 

 

 

 

 

 

 

 

 

 

3.1

 

 

 

 

 

 

 

 

 

 

 

3.2

 

 

 

 

 

 

 

 

 

3.3

 

 

 

 

 

 

 

 

 

 

 

3.4

 

 

 

 

 

 

 

 

 

 

3.5

 

 

 

 

 

 

 

 

 

 

 

3.6

 

 

 

 

 

 

 

 

 

 

 

 

Unit Learning Outcomes

LO1

 

 

 

 

 

 

 

 

 

LO2

 

 

 

 

 

 

 

 

 

LO3

 

 

 

 

 

 

 

 

 

LO4

 

 

 

 

 

 

 

 

 

 

LO5

 

 

 

 

 

 

LO6

 

 

 

 

 

 

 

 

 

 

Student assessment

Assessment Type

When assessed

Weighting (% of total unit marks)

Learning Outcomes Assessed

 

Assessment 1

Type: Multi-choice test / Group work / Short answer questions / Practical / Remote Lab / Simulation

Example Topic: Process dynamics, mathematical models, time response to inputs, block diagrams, transfer functions, Laplace transforms

Students may complete a quiz with MCQ type answers and solve some simple equations to demonstrate a good understanding of the fundamental concepts

 

Week 4

(Week 8 for

24 week delivery)

 

15%

 

1, 2

 

Assessment 1

Type: Multi-choice test / Group work / Short answer questions / Practical / Remote Lab / Simulation

Example Topic: Frequency diagrams, bode plots, frequency response, root locus, steady state, 1st order and 2nd order modelling of physical processes

Students may complete a quiz with MCQ type answers and solve some simple equations to demonstrate a good understanding of the fundamental concepts

 

Week 7

(Week 14

for 24 week delivery)

 

20%

 

1, 2

 

Assessment 3

Type: Multi-choice test / Group work / Short answer questions / Practical / Remote Lab / Simulation / Project

/ Report

Example Topic: Matlab model of a process with development of a suitable controller showing responses (Bode plots, Nyquist, Root locus, PID).

Students may complete a quiz with MCQ type answers or solve some simple problems or using software to complete a practical.

 

Week 10

(Week 20

for 24 week delivery)

 

20%

 

3, 4, 5

 

Assessment 4

Type: Examination Example Topic: All topics

An examination with a mix of detailed report type questions and/or simple numerical problems to be completed in 3 hours

 

Final Week

 

40%

 

1 to 6

 

Attendance / Tutorial Participation

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

 

Continuous

 

5%

 

1 to 6

Assessment Type

When assessed

Weighting (% of total unit marks)

Learning Outcomes Assessed

analysis, application.

 

 

 

 

Prescribed and Recommended Readings

Textbook

Barraclough, B, Dutton, K, Thompson, S 1997, The Art of Control Engineering, Prentice Hall ISBN-13: 978-0201175455

 

Reference

Ferrarini, L, Veber, C, 2009, Modeling, Control, Simulation, and Diagnosis of Complex Industrial and Energy Systems, ISA, ISBN 978-1-62870-506-5. Online version available at: https://app.knovel.com/hotlink/toc/id:kpMCSDCIE3/modeling-control-simulation/modeling- control-simulation

 

 

Notes and Reference texts

Knovel library: https://app.knovel.com

IDC notes and Reference texts as advised. Other material 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.

 

Topics 1 and 2

 

Introduction to Process Dynamics and Mathematical Models

  1. Review of 1st and 2nd order linear differential equations

  2. Representation of physical processes by linear differential equations

  3. Examples of linearity and non-linearity in physical processes

  4. Representation of dynamic processes using transfer functions

  5. Derivation of Laplace transforms for impulse, step, and ramp functions

  6. The transfer function in block diagram models

 

Topic 3

Time Response Modelling

  1. Block diagram notations and examples

  2. Representation of process dynamics by 1st and 2nd order transfer functions

  3. Transfer functions for time delays in the process response

  4. Determination of time responses to pulse, step, and ramp inputs

  5. Modelling of feedback control systems

  6. Higher order dynamic models and their simplification to approximate 2nd order plus dead time

 

Topics 4 and 5

Modelling of process characteristics in Matlab

  1. Steady state process model representations to identify inputs, outputs, and disturbance influences

  2. Development of a 1st order model from typical physical process such as a stirred hot water tank

  3. Development of a 2nd order model from a spring and weight model, and from a cascaded water tank process

  4. Development of a feed heater model with disturbances

  5. Detailed application model of a feedback control loop applied to a 1st order process

 

Topic 6

Frequency domain analysis

  1. Frequency response plots and their interpretation

  2. Bode diagrams

  3. Nyquist Diagrams

  4. Root locus diagrams

  5. Robust control systems

 

Topics 7 and 8

Stability analysis of single loop feedback controllers (SISO)

  1. Stability criteria for feedback control

  2. Compensation by lead lag elements to achieve stability

  3. Configuration and tuning of feedback controllers using S plane models

  4. Feed forward control techniques and benefits for disturbance rejection

  5. Exercises with Matlab to verify stability and response of controllers

 

Topics 9 and 10

Advanced Process Control

  1. Advanced vs classical control

  2. Internal Model Control - IMC (disturbance rejection and control, delays and feedforward)

  3. Model Predictive Control - MPC (state space, transfer function, impulse response, observers, and etc.)

  4. MPC steady state optimization (Degrees of freedom, slogans for maximization and minimization, and etc.)

  5. Reference models

  6. Control model formulation (Quadratic vs Geometric control, horizon length, weight matrix, and etc.)

 

Topic 11

Non-linear processes and controller techniques

  1. Typical sources of non-linearity in the controllers and processes

  2. Modelling examples of non-linear processes

  3. Methods for control of non- linear processes

  4. Response modelling exercises

 

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 specialized topic if applicable to that cohort.

The Engineering Institute of Technology (EIT) is dedicated to ensuring our students receive a world-class education and gain skills they can immediately implement in the workplace upon graduation. Our staff members uphold our ethos of honesty and integrity, and we stand by our word because it is our bond. Our students are also expected to carry this attitude throughout their time at our institute, and into their careers.