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Course content

Digital Control Systems

Code:
266520
Abbreviation:
D-1477
Higher education institution:
Faculty of Mechanical Engineering and Naval Architecture
ECTS credits:
6.0
Load:
30(E) + 30(L)
Issuing teachers:

Professor Joško Deur, PhD

Assistant Professor Branimir Škugor, PhD

Course contractors:

Assistant Professor Branimir Škugor, PhD (L)

Professor Joško Deur, PhD (L)

Course description:
Course objectives: Transferring the knowledge in the filed of digital control system design, including numerically optimized PID controllers, deadbeat controllers, state estimation and control, LQ regulator, polynomial controller, and adaptive controllers. Enrolment requirements and required entry competences for the course: Student responsibilities: Attending the lectures and exercises, studying the recommended literature, and making consultations when needed. Grading and evaluation of student work over the course of instruction and at a final exam: Two midterm exams, written exam for students who do not pass midterm exams, and oral exam. Lectures 1. Sampling process and discretetime transfer function 2. Analysis of discretetime control systems (steadystate accuracy, stability, transient performance) 3. Optimization of digital PID controller parameters 4. Deadbeat controller 5. Discretetime statespace description of process 6. Discretetime state control using poleplacement synthesis method 7. Fullorder discretetime estimator 8. Reducedorder discretetime estimator 9. Polynomial controller 10. Discretetime linear quadratic regulator (LQR) 11. Kalman filter 12. Adaptive control systems: fundamentals, controller types, concepts 13. Autotuning controller 14. Process parameter estimation and selftuning control 15. Fundamentals of model predictive control Exercises 1. Examples of signal and system time discretization 2. Examples of discrete system analysis 3. PID controller numerical optimization tool 4. Example of deadbeat controller and comparison with PID controller 5. Examples of statespace discrete systems 6. Example of digital state control 7. Examples of digital state and disturbance estimation 8. Midterm exam I 9. Example of polynomial controller synthesis 10. Example of LQ controller synthesis 11. Examples of Kalman filter application 12. Examples of adaptive mechatronic systems 13. Examples of autotuning controller 14. Examples of selftuning controller 15. Midterm exam II
Course languages:

Hrvatski

Mandatory literature:

J. Deur, B. Škugor (2022): Elektronički materijali/prezentacije s predavanja i vježbi

Recommended literature:

K.J. Astroem, B. Wittenmark (1997): Computer controlled systems

R. Isermann (1989): Digital control systems

Learning outcomes:

1. Analyze digital control systems

2. Create software tool for PID controller parameter optimization

3. Estimate state and disturbance variables for digital control applications

4. Design of digital state controller including linear quadratic regulator (LQR)

5. Design polynomial controller

6. Design adaptive controllers (gain scheduling, auto-tuning, self-tuning)

7. Examine digital control systems using computer simulation

8. Evaluate digital control performance with respect to various practical criteria

Course in study programme:
Code Name of study Level of study Semester Required/Elective
1168 Automatic Control graduate 2 required
1172 Mechatronics of Transportation Systems graduate 2 required
1173 Robotics graduate 2 required

* the course is not taught in that semester

Legend

  • E - Exercises
  • L - Lectures