Short Courses in Control and Systems Engineering
"This activity is appropriate for the maintenance or enhancement of a competence relevant to an individual's professional development."
The Short Courses Programme is intended as continuing professional development for engineers, and results from a comprehensive consultation and liaison with industry and individual engineers.
Individuals can choose to attend any number of the range of the Masters-level modules as a series of short courses. However, they are not credit bearing and no qualification can be gained from them.
Short Course modules and module summaries
| Module code, title and summary | Number of weeks |
|---|---|
| ACS6101: Foundations of Control Systems The module ACS6101 provides all students with appropriate pre-requisite knowledge for future modules. It also gives students a broad exposure to the fundamentals of systems modelling, classical control systems analysis and design and simulation. |
6 |
| ACS6102: State-space, Optimal Control and Nonlinear Systems The module ACS6102 introduces basic and advanced concepts of state space analysis and design together with topics in optimal control systems theory. Provides tools and methods for analysis of non-linear systems and introduces some recent global method in non-linear systems theory. Rigorous mathematical exposure to topics such as calculus of variations and Pontryagin's Maximum Principle is dealt with in parallel to the use of computer-based MATLAB toolboxes for state-space design. |
3 |
| ACS6103: Signal Processing and Estimation The module ACS6103 introduces students to the concepts and methods of systems identification, signal processing and estimation. It shows the practical application of the methods to several industrial case studies, provides background theory and practical methods for the design of discrete filters, and demonstrates the main ideas of low-level image processing. |
3 |
| ACS6110: Embedded Systems & Rapid Control Prototyping This module covers rapid prototyping of control systems on real hardware and how the eventual control system can be implemented as a real time embedded system using hardware and software. The prototyping hardware consists of a miniature three degree-of-freedom helicopter, connected to a PC via a National Instruments myDAQ data acquisition unit. This hardware is used to introduce data acquisition and leads on to the development of a robust control system design. The embedded systems part consists of a range of individual hardware components which are used to implement an embedded system for a control systems problem. Aspects such as component interfaces, communication protocols and control mechanisms are covered from both a hardware and software perspective, together with Real Time Operating Systems. Both sets of hardware are sufficiently low-cost, portable and robust to provide individual students with a `take-home lab', thus enabling the student to benefit from experiential based learning in a more flexible fashion than is otherwise provided by traditional laboratory classes. |
3 |
| ACS6116: Advanced Industrial Control This unit comprises concepts of active noise and vibration control (ANVC) and predictive control. The unit on ANVC introduces the basic concepts of analysis and design of active control systems using both mechanical vibration and acoustic signals as real-world examples. This unit on predictive control addresses control design techniques based on prediction, usually denoted model based predictive control (MPC). |
3 |
| ACS6117: Intelligent Systems This module provides an introduction to the theory and practice of machine learning and data modelling, and to fuzzy logic within a control and systems engineering context. We will look at the underlying principles of machine learning, data modelling and fuzzy logic, the advantages and limitations of the various approaches and effective ways of applying them in systems and control engineering, with the aim of making students appreciate the merits of the various technologies hence introduced. |
3 |
| ACS6118: Robotics and Multi Sensor Systems This module covers topics in the closely related disciplines of robotics and multi-sensor systems. The module initially covers robotic systems with an emphasis on case study driven material on the technical and theoretical aspects of robotics. Multi-sensor systems are now a common feature of many engineering applications including robotics. The second part of the module will introduce multi-sensor systems and approaches to data fusion. |
3 |