Training courses are provided on a wide range of subjects, from fundamental
control theory to advanced control philosophies and expert systems. These
can be used as refresher courses for your engineers, or to bring a team
up to speed on new or advanced techniques.
The training courses can be customised so that the material targets
a particular area, alternatively examples can be used that have relevance
to the trainees' business.
The training courses described below represent the most comprehensive
available in the field of control engineering and can be focused on particular
requirements of the client company. Individual modules from different courses
can be mixed to form a client specific course. In addition the courses
can be aimed at technician to research engineer level
Should your company require course modules which are not listed then
our relationship with Strathclyde University can be exploited to ensure
that tuition on virtually any control technique can be provided. Courses
are generally run as and when required and can be conducted on your own
premises or here in Glasgow.
Control Fundamentals, Part 1 – Theory (2-day Course)
The course provides training at an engineering level in Classical Control Theory
and Control System Design. The course presents frequency and time domain analysis of
linear control systems. The PID controller and tuning methods are also covered.
Significant hands-on examples are used to reinforce the lectures. A follow on
course "Control Fundamentals 2 - Practice" extends this to looking at digital
control, non-linearities and system identification.
This is one of the most popular training course that we offer. It is especially
useful to those engineers who may not have had specific control theory teaching
during their electrical or mechanical engineering degrees. It also provides an
excellent refresher course in basic control engineering for practising engineers.
Control Fundamentals, Part 2 – Practice (2-day Course)
This is a follow-on course to "Control Fundmentals 1 - Theory" and covers additional, more
practical topics, including digital control, non-linearities and system identification. Again,
significant hands-on examples are used to reinforce the lectures.
Mathematics for Engineers and Control (3-day Course)
The course is suitable for engineers, academics and students who, from a non-mathematical background,
are currently practising in a field of engineering or science and wish to update or refresh their
mathematical knowledge. Engineering literature often assumes prior knowledge of mathematical terms.
By attending the above course, delegates will find such literature easier to understand. More
generally, this course will provide delegates with mathematical skills required to solve complex
engineering problems encountered in practice.
Predictive Control (1-day Course)
Predictive control is probably the most popular advanced control technique adopted by the industry.
Its popularity stems from capability for constraints handling and optimal control framework. The course
provides overview of Predictive Control techniques and then gives guidelines for analysis and tuning
of predictive controllers.
Overview of Modern Control Techniques (1-day Course)
This mid-level training course is aimed at design engineers, new graduates and those interested in
enhancing their understanding of advanced control. Some knowledge of classical control design techniques
and mathematics is preferable, but not essential. The course aims to provide each delegate with a much
clearer understanding of both the need for and some of the most popular approaches to advanced control. The focus will be less on formal mathematical proofs and more on practical application of each technique.
Introduction to Estimation and Kalman Filtering (2-day Course)
This course is aimed at introducing the Estimation theory, Kalman Filter and its application to
engineers. The Kalman Filter and Extended Kalman Filter theory and practical applications are
presented. Significant hands-on examples are used to reinforce the lectures.
Optimisation and System Identification (3-day Course)
This three day training course introduces two closely related topics of Optimisation and
System Identification. The Optimisation is extremely important subject used across all the
Engineering fields. For control engineering applications it is widely used for optimal control
and parameter identification/estimation. The system identification is probably the most important
and difficult step required for a successful modern control design. The Course is aimed at
engineers who are involved in system modeling and model based control/simulation. All presented
topics will be supported by practical engineering examples and will arm trainees with efficient
approach to tackle real-life problems. Lectures and Hands-On sessions will provide a methodology
and step-by-step guide of using all presented algorithms in their engineering practice.
Introduction to Robust and Multivariable Control Design (3-day Course)
The basic concepts of robustness of control system and problems associated with the multivariable
systems are introduced. Control techniques like Pole-Placement, Linear-Quadratic Optimal Control,
H-infinity and predictive control are introduced. Available computer design packages are discussed
and examples given during hands-on sessions.
Introduction to MATLAB/Simulink (1-day Course)
This short training course introduces MATLAB/Simulink engineering packages and presents its
application to control engineering problems.
Introduction to LabVIEW and Control Design/Simulation Toolkit (1-day Course)
This short training course introduces LabVIEW and Control Design and Simulation Toolkit. The
software tool capabilities are presented and its application to control engineering problems.
Fundamentals of Dynamic Control using LabVIEW
This is the standard Control Fundamentals course but it uses LabVIEW Simulation and Control design
during Hands-On sessions.
Introduction to Fuzzy Logic and Fuzzy Control (1-day Course)
This course provides a simple introduction to the concept of Fuzzy Logic and how it can be used
for control. An industrial application (paper making moisture control) is used in the hands-on to
illustrate the concepts.
Neural Networks for Modelling, Control and Fault Detection (1-day Course)
This course on Artificial Neural Networks covers topics ranging from simple introductory material
(the course assumes no prior knowledge of the subject) to more advanced application material,
looking at how neural networks can be applied for system modelling, estimation and fault detection.
The lectures were complemented by computer based hands-on examples, utilising Matlab and its Neural
Network toolbox. The course is also available as a 3- Day course.
Introduction to Nonlinear Control (3-day Course)
This three-day course presents a variety of nonlinear control techniques, including nonlinear
minimum variance, multiple model methods, nonlinear control using EKF and predictive control for
nonlinear systems. These topics are introduced through lectures and application orientated (automotive)
computer-based examples. The first day introduces the concept of a nonlinear system and how it is
represented and classical approaches for coping with nonlinearities, making the course ideal for
control engineers with no prior exposure to nonlinear control