Understanding Control Technologies

AGENDA Instructors ADDITIONAL INFO REGISTRATION

Overview

ISC’s "Control Fundamentals I" course has been a favourite among engineers since its inception and refinement over two decades ago. Presented many times at companies worldwide, this course targets engineers who use control techniques in their daily work but may need an update or have only had a basic introduction to control engineering theory at university.

This new course builds on Control Fundamentals I and prior attendance to the first course is not required. While maintaining its practical nature, it introduces slightly more advanced techniques that have proven highly useful in applications, such as tuning, auto-tuning, predictive control, Kalman filtering, and optimal control methods.

Designed to encourage the use of the techniques rather than focus on the mathematical basis of results, the course includes hands-on exercises in MATLAB/Simulink software to help engineers grasp the modelling and design techniques.

Participants are encouraged to ask questions throughout the course and at the end of each presentation. Additionally, coffee and lunch breaks provide opportunities for the participants to discuss their specific engineering problems with the instructors, whether related to modelling, simulation, control, condition monitoring, or implementation issues. Any remaining questions can also be addressed in the wrap-up session on the final day.

Instructors

Michael Grimble

Professor Michael Grimble

Professor Mike Grimble understands the needs of industry well, having worked for Ciba Geigy and Associated Electrical Industries (later GEC at Rugby). At Imperial College's Industrial Automation Group, he focused on modelling for the control of cold rolling mills. He later established industrial groups at Sheffield Hallam University and the University of Strathclyde where he continues as a Research Professor. His expertise lies in designing high-performance, robust control systems for various industrial applications. His industrial background enriches the industrial training courses with valuable motivation and insights.

PAWEL MAJECKI

Dr Pawel Majecki

Dr. Pawel Majecki conducted his research at the Industrial Control Centre at Strathclyde University before joining Industrial Systems and Control Ltd (ISC), which promotes technology transfer. He has worked with major international companies, applying advanced control methods, including predictive and optimal controls. Dr. Majecki has also led control training courses in the UK, Norway, Italy, Spain, and the USA. His extensive experience with MATLAB/Simulink enhances the hands-on training, helping delegates gain deeper insights into these tools and their application in design methods.

Delegates will find both instructors delighted to answer questions and discuss industrial problems during coffee breaks, lunch breaks, and at the end of the day.

Additional Information

Event Venue

Scottish Engineering, 105 W George St, Glasgow G2 1QL

Accommodation

Glasgow City Centre offers a wide range of accommodation, you can find our recommendations here.

Course Summary and Agenda (Download PDF)

Timings may change slightly.

Day 1: Basics of Control and System Modelling

9.00 Welcome
9.10 Motivation for Using Improved Control Design Methods (safe control, robustness, reliability, performance benefits obtained)
10.15 Physical Systems Modelling Methods (white and grey box modelling, state-space models, applications, simulation tools)
11.00 TEA/COFFEE
11.15 Hands-On Session: System Modelling using MATLAB/SIMULINK
12.30 LUNCH
13.30 Sensors and Actuators (wide ranging overview of the devices available)
14.30 TEA/COFFEE
14.45 Nonlinear Systems and Control (modelling and problems due to nonlinearities, linearization methods, hysteresis and compensation)
15.45 Hands-On Session: Frequency Response Analysis and Design Methods
17.00 CLOSE

Day 2 - Identification Methods and Control Design

09.00 Identification of the Models for Linear Systems (popular model-based algorithms to calculate models of systems from data collected).
10.15 TEA/COFFEE
10.30 Autotuning Methods (automatic methods of controller tuning after obtaining test results using system identification methods including PID controllers).
11.15 Hands-On Session: System Identification
12.00 Practical Aspects of Model Identification (identification methods and use of methods when implementing controls).
12.45 LUNCH
13.45 Hands-On Session: Computing Models, Control Design and Autotuning
14.45 TEA/COFFEE
15.00 State-Space Based Modelling Methods for More Advanced Control Methods (further details of types of SS structure and models produced).
16.00 Introduction to Predictive Control Methods (most successful modern control design method – motivation and basic ideas).
17.00 CLOSE

Day 3 - Optimal Control Design and Filtering/Estimation Methods

09.00 Introduction to Linear Quadratic Optimal Control Methods (basic ideas in optimal control and controller properties)
10.00 TEA/COFFEE
10.15 Hands-On Session: Linear System Optimal Control Design
11.00 Intuitive Introduction to Optimal Filtering (Kalman filtering and extended Kalman filtering methods for nonlinear applications)
12.00 LUNCH
13.00 Hands-On Session: Kalman Filtering Methods and Observers
13.45 Design Example on Dynamic Positioning (positioning system design, marine application example).
14.45 TEA/COFFEE
15.00 Model Based Condition Monitoring and Fault Detection Methods (overview of model based early detection and fault monitoring methods)
16.00 A Look to the Future Covering Artificial Intelligence and Machine Learning (artificial neural networks and optimization, genetic algorithms, data driven technologies available, using machine learning in control and estimation)
17.00 CLOSE

Prices and Discounts

  • Registration before 7th April 2025: £1,249 + VAT per delegate
  • Registration on/after 7th April 2025: £1,407 + VAT per delegate

For two or more places from the same organisation, each additional place is 10% off the single place fee.

Registration

Please complete the Online Registration Form.

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