Advanced Control Systems

Successful completion of the course will provide students with mastery of conventional and advanced concepts and techniques of control theory. This will enable the student to recognize, analyze and solve real-world problems using techniques from both conventional and modern control theory.

Reiteration of the studied material for control systems (Introduction to management systems; Modeling of systems; Determination of empirical models based on real measurements; Classical methods for analysis of control systems: time-domain analysis; state-space analysis; frequency domain analysis; Stability of control systems). Feedback control. PID control (basics of PID, basic and advanced algorithms for PID and their tunning, modifications of PID algorithms with the addition of reset windup, real implementation of PID controllers). Feedforward Control. Ratio Control. Cascade Control. Time-delay compensation. Adaptive Control (Concept; Variation of process parameters and repercussions; Adaptive control schemes; Problem of Adaptive control; Model Reference Adaptive Control (MRAC); Applications). Internal Model Control (IMC). Multivariable control. Model Predictive Control (MPC) (Concept; Selection of model for prediction; Receding-Horizon concept; Design of linear model predictive controller; Applications).

Slide presentations, interactive lectures, exercises (use of equipment and software), teamwork, case studies, invited guest lecturers, independent preparation and defense of project and seminar work, learning in digital environment (forums, consultations).

The students are obliged to complete and present a project assignment during the semester. A final written and/or oral exam is scheduled during the exam sessions. The students complete the course if they pass the final exam and had previously completed and presented the project assignment during the semester. The final grade takes into account the points from both the final exam and the project assignment.