Control and Artificial Intelligence (CAI)

Course supervisor: doc. Ing. Anna Jadlovská, PhD.
Lecturer: doc. Ing. Anna Jadlovská, PhD.
Instructor: doc. Ing. Anna Jadlovská, PhD.
Laboratory: L513
Study program: Cybernetics and information-control systems
Degree: 2nd (Master)
Grade: 1st
Semester: Summer

Course aim

The main objective of the course is to familiarize students with the application of several types of discrete PSD / polynomial controller algorithms together with their practical verification on simulation models of dynamical systems (heat exchanger, robot-manipulator crane) as well as educational laboratory models (Helicopter, Ball & Plate, Magnetic Levitation) in the Matlab / Simulink programming environment, Control and Real Time Toolboxes in selected control structures. Another goal is to teach students to be adept in the individual stages of control algorithm design for self-tuning controllers - STC (identification of the physical model of a dynamic system from measured data and STC controller synthesis supported by Identification Toolbox and STC Library) and to familiarize them with modern methods and techniques for intelligent control algorithm design for the control of nonlinear dynamical systems (modified LQ algorithms and predictive control algorithms), which make use of the properties of neural networks in different applications such as the neural model NARX and NISS of the nonlinear system, neural controller, neural estimator using Neural, NNSID, and NNCTRL Toolboxes.