Award in Advanced Control Engineering - L-Universit脿 ta' Malta

MQF Level

Duration and Credits

1 Semester

10 ECTS

Mode of Study

Part-time Online

If you're working in control, automation, or robotics and want to take your expertise to the next level, this fully online micro-credential is for you. You鈥檒l explore how to model, analyse, and control nonlinear systems鈥攕ystems that go beyond the limitations of linear models. You鈥檒l learn how to apply advanced techniques like feedback linearization, gain scheduling, sliding mode control, and adaptive and intelligent control methods using neural networks and fuzzy logic. These skills are essential when working with systems that operate in uncertain or changing environments, such as autonomous vehicles, smart grids, or advanced industrial processes. Through this course, you鈥檒l develop the ability to evaluate complex dynamics, select the right control approach, and build systems that can adapt and learn. The course forms part of the MSc in Intelligent Systems, Signals and Control and supports your continued professional growth by giving you the tools needed to lead innovation in sophisticated engineering contexts.

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Please check your eligibility to join this short course and time-tabling details with the Faculty of Engineering. The short course will only be delivered subject to a minimum number of applications being received.

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Semester 2

Compulsory Units (All students must register for this/these unit/s)

SCE5202	Nonlinear Systems and Control	5 ECTS
SCE5204	Adaptive and Intelligent Control	5 ECTS

This programme of study is governed by the Regulations for Micro-credentials, 2024.

By the end of the course you will:

Subject Knowledge and Understanding

Be able to model and analyse nonlinear dynamic systems by deriving state-space representations and evaluating system performance in both open- and closed-loop configurations;
Gain proficiency in applying advanced control strategies, including linearization, gain scheduling, feedback linearization, and sliding mode control, to manage complex system behaviour;
Learn to differentiate between non-adaptive, adaptive, and intelligent control methods, and determine which is most suitable for systems with uncertain or varying dynamics;
Be able to explain and apply core concepts of adaptive and intelligent control, such as parametric vs. functional uncertainty, adaptation, learning, and control using neural networks or fuzzy logic.

Intellectual Development

Enhance your analytical and problem-solving skills, enabling you to address complex, real-world control challenges with adaptable and innovative strategies.

Key and Transferable Skills

Develop systems thinking and practical experience relevant to a broad range of industries, preparing you for technical roles and continuous professional growth in advanced engineering and automation sectors.

Non EU Applicants:

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Graduates of this micro-credential will be prepared for roles such as:

Control Systems Engineer;
Automation Specialist;
Robotics Engineer;
Systems Modelling and Simulation Specialist;
Process Control Analyst.