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KARAKTERFORDELING · V 2025
29 kandidater
Alle delene må normalt være bestått. Karakterfordelingen over gjelder emnet samlet.
Kilde: Data hentet fra Felles studentsystem ved NMBU, slik den var publisert for høsten 2026. NMBU har ikke kvalitetssikret og er ikke ansvarlig for innholdet på denne siden.
NMBU sin egen emnebeskrivelse — læringsutbytte, innhold og vurderingsform.
This course provides an in-depth exploration of control systems and feedback control, focusing on time-domain analysis and design. It begins with an introduction to control theory and the application of the Laplace transform for solving differential equations, establishing a strong foundation for dynamic system modeling in both the time and frequency domains.
Students will learn about the time response of linear time-invariant (LTI) systems, steady-state error, and stability analysis using the Routh-Hurwitz criterion, as well as step response methods. In addition, the course covers the principles and methodologies necessary for modelling, analyzing and designing control systems. This includes the design and tuning of controllers to meet desired performance criteria in real-world systems, with a focus on Proportional-Integral-Derivative (PID) controllers, controller and observer design using state feedback, and advanced techniques such as Linear Quadratic Control (LQC) and Model Predictive Control (MPC).
Students will also study state estimation using Kalman filters, which are essential for applications like robot motion planning and control, allowing systems to predict states in the presence of uncertainties.
The course incorporates a wide range of practical examples, which are simulated, controlled, and analyzed using Python, offering students hands-on experience in applying control system concepts to real-world scenarios.
Code:
All examples and problems covered in the course are simulated using Python and can be accessed in GitHub.
By the end of the course, students will be able to:
Individual exam on campus on the student's own PC. Grade rule: AF. Duration: 3 hours.
Mandatory requirements: The work requirements must be approved to sit for the exam.
K2 - Specified use of AI
Permitted Uses of AI:
Prohibited Uses of AI:
Ethical Considerations:
Consequences of Misuse:
Misuse of AI tools, such as submitting AI-generated work as your own, will be considered a violation of academic integrity and handled according to university policies.
The use of AI must comply with the guidelines for the use of artificial intelligence (AI) at NMBU.
Kilde: Data hentet fra Felles studentsystem ved NMBU, slik den var publisert for høsten 2026. NMBU har ikke kvalitetssikret og er ikke ansvarlig for innholdet på denne siden.
Hva burde andre vite før de tar dette? Anonymt, ingen innlogging.
Basert på hvor kandidatene til eksamen var registrert (DBH).
Emner som tas i de samme studieprogrammene som TEL240.
| Semester | Kandidater | Snitt | Stryk |
|---|---|---|---|
| Vår 2025 | 29 | D (2.45) | 10,3 % |
| Vår 2024 | 32 | C (3.34) | 0 % |
| Vår 2023 | 31 | B (3.55) | 0 % |
| Vår 2022 | 33 | B (3.58) | 0 % |
| Vår 2021 | 36 | C (3.36) | 0 % |
| Vår 2020 | 13 | – | 0 % |
| Vår 2019 | 19 | B (3.58) | 0 % |
| Vår 2018 | 31 | B (3.68) | 9,7 % |
| Vår 2017 | 30 | C (3.47) | 0 % |
| Vår 2016 | 22 | D (2.45) | 13,6 % |
| Vår 2015 | 46 | C (2.96) | 0 % |