CET727 Process Modelling

Course Provider

School of Electrical and Electronic Engineering (EEE)



Academic Unit



The course of Process Modeling is directed to provide a modern review of process parameter identification in process control engineering. Hence, it is important to learn parameters identification methods and process control systems. The objectives include equipping learners with (a) understanding of issues related to parameters identification including fundamental concepts, step input, relay feedback, time domain and frequency domain identification method; and (b) case studies in process parameter identification to enhance skills and techniques for tackling practical multivariable process control system design problems. . 

This course is part of:
- Graduate Certificate in Computer Control and Automation
- FlexiMasters  in Computer Control and Automation

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On completion of the course, the learners should be able to understand t he role and relevance of parameter identification in the practical field of industrial process control. Specifically, they will understand the modeling of processes and how to obtain the parameter in the design of  control systems. They will understand various identification methodologies applied to the process control systems. Extensive parameter  identification simulation projects and case studies will provide the learners with an insight into the actual application of modelling techniques in the  industry processes;

Open loop step input identification method

Basic concepts of process modelling, graphic method, two point method, log method, area method, least squares method, multivariable process  identification.

Closed-loop step input identification method

Least squares method, Fourier transformation, closed-loop identification in  time domain, closed-loop identification in frequency domain, recursive  identification method.

Relay feedback identification

Fundamental of relay feedback, ultimate frequency, simple identification method, frequency domain identification method, enhanced relay feedback  method.

Concept and theoretical basis of model predictive control

Fundamental of model predictive control, the concept of model predictive  control, the design parameters of model predictive control, the challenges of  model predictive control, the applications of model predictive control.

Automation Engineers for upgrading and Engineers who wish to switch to the automation field.

Standard Course Fee: S$1,620

SSG Funding Support

Course fee payable after SSG funding, if eligible under various schemes

Fee BEFORE funding & GST

Fee AFTER funding & 8% GST

Singapore Citizens (SCs) and Permanent Residents (PRs) (Up to 70% funding)



Enhanced Training Support for SMEs (ETSS)


SCs aged ≥ 40 years old
SkillsFuture Mid-career Enhanced Subsidy (MCES)
(Up to 90% funding)

• NTU/NIE alumni may utilise their $1,600 Alumni Course Credits. Click here for more information.

Read more about funding
CET715 Discrete Time System Modelling and Analysis1
CET716 State-Space Design Methods1
CET717 Optimal Control, Design and Implementation of Digital Controllers1
CET718 Linear and Nonlinear Programming1
CET719 Random Processes and Queuing Models1
CET720 Decision Analysis1
CET721 Robot Kinematics1
CET722 Robot Control1
CET723 Robotic Sensing and Sensors1
CET724 Image Processing for Vision1
CET725 Pattern Recognition and Stereo Vision1
CET726 Three-dimensional computer vision1
CET728 Model predictive control1
CET729 Multivariable process control1

Listed courses are:

  • Credit-bearing and stackable to Graduate Certificate in Computer Control and Automation (total 9AUs) and FlexiMasters in Computer Control and Automation (total 15AUs).
  • SSG funded and SkillsFuture Credit approved.