CET729 Multivariable Process Control

Course Provider

School of Electrical and Electronic Engineering (EEE)



Academic Unit



The course of Process Modeling is directed to provide a modern review of the model predictive control. Hence, it is important to learn the concThe course of Multivariable Process Control is directed to provide a modern review of multivariable process control engineering. Hence, it is important to learn multivariable control, decentralized control and centralized control. The objectives include equipping learners with (a) understanding of issues related to Multivariable Control strategies including fundamental concepts, loop pairing, decentralized control and decoupling control; and (b) case studies in multivariable process control system 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 multivariable control theory to the practical field of industrial process control. Specifically, they will understand  the interaction analysis of multivariable processes and its uses in the design of control systems. They will understand various controller-tuning  methodologies applied to the multivariable control systems. They will become aware of different practical control strategies as well as advanced  control techniques that are specifically suited for the multivariable processes. Extensive multivariable control system simulation projects and case studies  will provide the students with an insight into the actual application of multivariable control techniques in the industry processes.

Basic Control Algorithms

Review of Process control strategies. PID control system design. Direct Synthesis Control, Internal Model Control, Gain and Phase Margin Control.

Fundamental of Multivariable Control

Fundamental concepts, interaction analysis, static loop pairing, dynamic loop pairing, semi-dynamic loop pairing, stability.

Decentralized Control

RGA based detuning, process decomposition method, BLT method, Equivalent transfer based design.

Centralized Control

Simplified decoupling, generalized decoupling, inverted decoupling, Normalized decoupling, sparse control, block decoupling.

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
CET727 Process modelling1
CET728 Model Predictive 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.