The course is structured as follows:
Day 1: Introduction to extremum seeking control with applications
This lecture is about the problem of optimising a process without knowledge of a feasible model a priori. An introductory presentation will be given, with applications to energy, fluid dynamics and biotechnology.
Day 2: Introduction to Proportional – Integral – Derivative (PID) control and Kalman filtering with applications
This lecture will explain the fundamentals of PID control and Kalman filtering. Applications to drone modelling and control will be given.
Day 3: How to build a digital twin
In this lecture, students will learn how to formulate a dynamic model, build a simulator, and fit its parameters based solely on experimental data. Examples using ODE models, neural network models, and hybrid models will be considered. |