Master of Science in ​Computer Control & Automation

Master (Coursework)

Programme Type

Full-time, Part-time

Admissions (Coursework)

The MSc (Computer Control & Automation) programme provides practising engineers with advanced practical tools in the development, integration, and operation of computer-based control and automation systems.

  1. At least a good relevant bachelor's degree
  2. Relevant working experience is an advantage
  3. For applicants whose native language is not English, TOEFL/IELTS score is to be submitted with the application for admission:

         TOEFL Score (Test dates must be within 2 years or less from the date of application):

          ≥ 600 (paper-based)

          ≥ 250 (computer-based)

          ≥ 100 (internet-based)

         IELTS Score (Test date must be within 2 years or less from the date of application):

          ≥ 6.5

Programme Structure

There are two options of study, one with coursework and dissertation, and the other with coursework only. Each course is of 3 AUs and consists of 39 hours of lectures. Candidates who undertake a project of 6 AUs must submit a dissertation on it.

Option 1
Coursework + Dissertation

Option 2

8 courses + dissertation project
(30 AUs in total)
10 courses
(30 AUs in total)
4 specialized electives (≥ 12 AUs)
4 specialized electives ((≥ 12 AUs)
4 specialized electives (≤ 12 AUs)
6 specialized electives (≤ 18 AUs)
Dissertation (6 AUs)  

Full-time students are strongly recommended to select the dissertation option, however this option is recommended only for students with a high level of English proficiency. Students taking the dissertation option may take a longer time to complete the programme.

Note:  The programme structure will be subject to change without prior notice.



Both full-time and part-time programmes are offered (unless stated). Part-time candidates are expected to obtain permission from their employer before admission to the programme. All classes are conducted in the evenings, while ex aminations are conducted during office hours.


Type of Coursework Programme

Minimum Candidature

Maximum Candidature

Master of Science
1 year 3 year
Master of Science
2 year 4 year


Programme Calendar

Semester 1 August to December
Semester 2 January to May
Week 1 to 14 Lecture (Inclusive of 1-week recess)
Week 15 to 17 Examinations
Other Vacation


Graduate courses offered by Master of Science (MSc) Computer Control & Automation:

Specialized Elective Courses (Students are required to take a min of 4 out of all the 5 specialized elective courses)

Course Code

Course Title

Course Content


EE6203 Computer Control Systems Discrete-time system modelling and analysis. Cascade compensation. State-space design methods. Optimal control. Design and implementation of digital controllers.3
EE6204 Systems Analysis Linear, Dynamic and Integer Programming. Optimization Techniques. Random Processes. Queuing Models. Markov Decision Process.3
EE6221 Robotics & Intelligent Sensors Overview of robotics. Motion planning and control. Mobile robots . Controller hardware/software systems. Sensor systems and integration.3
EE6222 Machine Vision Fundamentals of image processing & analysis. Feature Extraction Techniques. Pattern / Object Recognition and Interpretation. Three- Dimensional Computer Vision. Three-Dimensional Recognition Techniques. Biometrics.3
EE6225 Process Control Basic control algorithms. Model Predictive Control. Multivariable control. Plant parameter estimation. Case studies in process control.3


General Elective Courses

Course Code

Course Title

Course Content


EE6010Project Management & TechnopreneurshipProject Initiation and Planning. Project Scheduling and Implementation. Project Monitoring, Control and Evaluation. Innovation and Entrepreneurship.3
EE6223 Computer Control Networks Data Networks in Control and Automation. Local Area Network Concepts and Fieldbus. Application Layer of Fieldbus and MAP. Internetworking and Protocols. Real-time Operating Systems and Distributed Control. Network Performance and Planning. Multimedia in Advanced Control and Instrumentation.3
EE6227 Genetic Algorithms and Machine Learning Review of Combinatorics and Probability. Introduction of Genetic Algorithms. Differential Evolution. Particle Swarm Optimization. Advanced Techniques. Principles of Machine Learning. Paradigms of Machine Learning. Kernel Methods.3
EE6401 Advanced Digital Signal Processing
Discrete signal analysis and digital filters. Power spectrum
estimation. Linear prediction and optimal linear filters. Multi-rate digital signal processing. DSP Architectures and applications.
EE6427 Video Signal Processing
Image and Video Basics. Image and Video Transform Coding.
Filtering and Error Resilience for Image and Video. Image and Video Coding Principles and Standards. Recent and Emerging Topics in Image and Video Processing.
EE6503 Modern Electric Drives
Introduction. DC Motor Drives. Induction Motor Drives. Synchronous Motor Drives. Servo-Motor Drives.
EE7204 Linear Systems
Input/Output System Models. State Space Representation. Norms of Signals and Systems. Decomposition of Linear Time-Invariant Systems. Linear Feedback Design. Convex Optimization for Linear System Analysis and Design.
EE7207 Neural and Fuzzy Systems
Introduction to artificial neural networks. Recurrent and Hopfield Neural Network. Multi-layer perception neural network. Radial basis function neural network. Support vector machines. Self-organizing map neural network. Applications of neural network. Fundamentals of fuzzy logic and fuzzy systems. Takagi-Sugeno (T-S) fuzzy modelling and identification. Stability analysis of fuzzy systems. Applications of fuzzy systems.
EE7403 Image Analysis and Pattern Recognition
Image Fundamentals. Image Enhancement and Restoration. Image Analysis. Decision Theory and Statistical Estimation. Classification and Clustering. Dimensionality Reduction.


Note: the above curriculum is subject to change.


Tuition Fee


Five MSc programmes (Communications Engineering, Computer Control & Automation, Electronics, Power Engineering and Signal Processing) are self-financed programmes.

Students of this programme are not eligible for Service Obligation/ MOE Subsidies.

The tuition fees per module (3 AUs) and per dissertation (6 AUs) for admission AY2020 onwards are shown in the tables as follows:

Admission Year Singaporeans
Singapore PRs
International Students
 (Per Module) (Per Dissertation)^ (Per Module) (Per Dissertation)^ (Per Module) (Per Dissertation)^
AY2020-2021 onwards  

Total Programme Fee

Total Programme Fee


Total Programme Fee

S$30,000 S$35,000 S$40,000

                                       *Exclusive of GST


                                       ^The tuition fee for Dissertation (6 AUs) will be twice of each module fee.


                                       All fees listed above are in Singapore dollars (S$), and subject to annual revision by the school.


                                       The tuition fee is exclusive of living expenses and miscellaneous student fees.

The deposit fee S$2,000 is payable upon acceptance of offer and non-refundable. It will be deductible from the full tuition fee.

Payment schedule for semester 1 and semester 2 is in September and February respectively.