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Control Under Uncertainty
Last Updated: 2026-06-03 00:07:32
Abstract
Beyond complexity, uncertainty is a key challenge. Models may be inaccurate, sensor data noisy, or actuator responses delayed. To address these issues, this module introduces essential tools such as system identification, state estimation, and robust control—methods that help maintain reliable performance despite real‑world imperfections.
Content
Besides complexity, another aspect is crucially important and needs to be addressed with the right tools: uncertainty. The mathematical models we build might not be sufficiently accurate to represent real world behaviour, the information gathered by the sensors might be affected by noise, the corrective actions we plan via the actuators might be delayed more than we expect. To cope with these practical considerations and many more, we introduce widely-used methods such as system identification, state estimation, and robust control.
General Information
- Language
- English
- Levels
- WBZ , NDS
- Frequency
- Yearly recurring
Examination
- Type
- ungraded semester performance
Registration & Places
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise | Control Under Uncertainty | No time listed | 6 h semesterly |