This course introduces the fundamental principles of feedback control, system modeling, and stability. It covers the mathematical representation of dynamic systems using differential equations, transfer functions, and state-space models. The course provides the basics of modern control including time and frequency domain analysis, root locus, Bode plots, and Nyquist criteria for system stability, and follow up of topics related to digital control such as Z-transform analysis, discrete-time system representation, sampling, and aliasing.
Students will learn to design proportional-integral-derivative (PID) controllers, and control strategies for real-world applications in robotics, automotive systems, and industrial automation.
To participate in this course students must have passed:
- CI_3.02 “Signals and systems”, for which we recommend all students to review the following lectures:
- Lecture 7: Fourier Transforms
- Lecture 8: System Stability
- Lecture 9: z-Transform
- Lecture 10: Laplace Transform
- Lecture 13: Relations between CT and DT
- Python programming skills. If you want to renew your knowledge of Python, see the book Think Python 2th Edition by Allen Downey (Open Book)
Lecture: Thursday, 12:15 - 14:45 Exercise: Thursday, 15:00- 15:45 Format: On-site room 02 02 510 IoTLab
Modern control:
- Control Systems Engineering by Norman S. Nise (online pdf)
- Modern Control Systems by Richard C. Dorf and Robert H Bishop (online pdf)
- Modern Control Engineering by Katsuhiko Ogata (online pdf)
- Einstieg in die Regulungstechnik mit Python by Hans-Werner Philippsen
- Feedback Systems An Introduction for Scientists and Engineers by Karl Johan Astrom Richard M. Murray (online pdf)
Digital/Discrete control:
- Discrete Control Systems by Yoshifumi Okuyama (online pdf)
- Digital Control by Kannan M. Moudgalya (online pdf)
- Computer Controlled Systems: Theory and Design by Bj Wittenmark and Karl Johan Åström
- Digital Control System Analysis & Design by Aranya Chakrabortty and Charles L. Phillips (Person website)