Understanding Control Technologies
AGENDA Instructors ADDITIONAL INFO ONLINE REGISTRATION
Fundamentals of AI and Machine Learning for Control Engineers
Introduction to AI for Practical Control and Condition Monitoring
9 - 11 September 2025, Glasgow
Overview
Artificial Intelligence (AI) and Machine Learning (ML) have gained significant momentum in recent years, opening up new opportunities for services and products. These technologies are already impacting various aspects of industrial control systems design, from enhancing design procedures to improving system performance and robustness. AI and ML provide solutions to complex challenges, such as reducing design and commissioning times for systems with difficult dynamics.
AI can be utilized in control applications in two primary ways:
- Data analysis, where big data informs management actions or initiatives.
- Enhancing control or signal processing systems at the machine or plant level, including digital twins for modeling, prediction, and condition monitoring.
While much attention has been given to AI methods for data analysis, control engineers are particularly interested in data-driven machine learning control methods. These methods offer opportunities to develop new adaptive controllers, filters, and condition monitoring tools that compensate for uncertainties in system or signal characteristics.
The course will highlight key advances in AI for control engineers, focusing on how AI can improve system modelling and design. It will discuss both pure data-driven methods and those that combine AI with traditional models, showing the benefits of each approach. It will also cover how AI and ML can meet the practical demands of engineering systems, such as providing reliable and consistent performance despite uncertainties, and optimising system performance using meta-heuristic AI-inspired optimisation algorithms.
The course will include hands-on examples using MATLAB/Simulink and opportunities for discussion and questions.
Instructors
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.
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.
Dr Luca Cavanini
Dr Luca Cavanini is experienced in advanced control methods such as nonlinear model predictive control, optimisation, renewable power, mobile robotics, autonomous vehicle control, path planning, Artificial Intelligence, and machine learning techniques for control systems.
Delegates will find all 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
Glasgow City Centre
Accommodation
Glasgow City Centre offers a wide range of accommodation, you can find our recommendations here.
Agenda (Download PDF)
Timings may change slightly.
Day 1: Artificial Intelligence Fundamentals |
|
| 9.00 | WELCOME |
| 9.10 | Introduction to Intelligent Control and Machine Learning I (Core ideas in artificial intelligence, motivation, terminology, brief history of AI systems, classification problems, big data, deep learning, importance of AI in control applications.) |
| 10.15 | TEA/COFFEE |
| 10.30 | Introduction to Intelligent Control and Machine Learning II (Historical perspective, main ideas and techniques, machine learning, reinforcement learning, developments in AI, multi-agent systems, possible application areas, benefits in applications.) |
| 11.30 | Different Approaches to Modelling Systems (Including the AI approach to modelling and the physical system model equation based methods (model based), and system descriptions, parameterisation of models.) |
| 12.30 | LUNCH |
| 13.30 | Meta Heuristic Optimisation and Gradient Algorithms (AI based optimisation algorithms for linear and nonlinear systems, for training parameters, gradient methods.) |
| 14.30 | TEA/COFFEE |
| 14.45 | Neural Networks (Introduction to neural networks, neurons, activation functions, types of NN, forward and backward propagation, layers of neural networks, network structures, loss functions, advantages and disadvantages, and use in condition monitoring, fault detection and prognostics.) |
| 16.00 | Neural Networks Design Demonstration (Design and comparison of different NNs for torque demand prediction.) |
| 17.00 | CLOSE |
Day 2 - Artificial Intelligence in Modelling and Classical Control |
|
| 09.00 | Digital Twins for Control and Monitoring Applications (Digital Twin for modelling, condition monitoring, prediction, and control.) |
| 10.00 | TEA/COFFEE |
| 10.15 | Support Vector Machine Approach to System Identification (AI and SVM methods on modelling and system identification.) |
| 11.30 | Demonstration Support Vector Machine Approach to System Identification (SVM data-driven design tool demo/hand-on.) |
| 12.30 | LUNCH |
| 13.30 | Classical Control and use with AI/ML Methods (AI/ML methods for improving classical controllers, Neural Network Based Reinforcement, Learning for Automotive Control.) |
| 14.30 | TEA/COFFEE |
| 14.45 | AI in Control Systems: Limits and Advantages (Review of the role of AI in control system with discussion of limits, issues, and reasons for using together with advanced control.) |
| 15.45 | Relationship between Fuzzy Logic Based Algorithms and AI Methods (Introduction to Fuzzy Control and links to AI, Neuro-fuzzy application.) |
| 17.00 | CLOSE |
Day 3 - Artificial Intelligence in Advanced Controls |
|
| 09.00 | Optimisation and Optimal Control in AI Enhanced Systems (Introducing AI methods into Nonlinear and Predictive Controls, Use of Genetic Algorithms, Why AI is important in applications, such as automotive and examples.) |
| 10.00 | TEA/COFFEE |
| 10.15 | Introduction to Model Predictive Control (Motivational introduction to MPC methods and the solution approach, and why it is so successful, where it has advantages, and briefly overviews competing methods that are options such as classical, LQG, H∞ robust and nonlinear control design methods.) |
| 11.30 | AI Enhanced Model Predictive Control (The AI role in controllers design, AI for modelling/control/calibration, Introduction to the example AI predictor for LPV-MPC in automotive application.) |
| 12.30 | LUNCH |
| 13.30 | Hybrid-Electric Vehicle MPC-LPV Energy Management System Demonstration (Model Predictive Control-based Energy Management System and Benchmarking, the role of prediction and different predictor structures) |
| 14.30 | TEA/COFFEE |
| 14.45 | Review of the Current State of Combined AI and Control System Techniques (Review of the literature on combined AI and control techniques, new ideas and potential for modern control techniques and new developments.) |
| 16.00 | Discussion: Commercial Developments and Machine Learning Tools - Debate |
| 16.30 | CLOSE |
Prices and Discounts
- Registration before 1st August 2025: £1,428 + VAT per delegate
- Registration on/after 1st August 2025: £1,608 + 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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