Veranstaltung
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Veranstaltung
Semester:
Wintersemester
2023
2.01.340 Uncertainty Modelling for Control in Digitalised Energy Systems -
Veranstaltungstermin | Raum
- Donnerstag, 19.10.2023 8:00 - 10:00 | A03 4-403
- Freitag, 20.10.2023 8:00 - 10:00 | A03 4-403
- Donnerstag, 26.10.2023 8:00 - 10:00 | A03 4-403
- Freitag, 27.10.2023 8:00 - 10:00 | A03 4-403
- Donnerstag, 2.11.2023 8:00 - 10:00 | A03 4-403
- Freitag, 3.11.2023 8:00 - 10:00 | A03 4-403
- Donnerstag, 9.11.2023 8:00 - 10:00 | A03 4-403
- Freitag, 10.11.2023 8:00 - 10:00 | A03 4-403
- Donnerstag, 16.11.2023 8:00 - 10:00 | A03 4-403
- Freitag, 17.11.2023 8:00 - 10:00 | A03 4-403
- Donnerstag, 23.11.2023 8:00 - 10:00 | A03 4-403
- Freitag, 24.11.2023 8:00 - 10:00 | A03 4-403
- Donnerstag, 30.11.2023 8:00 - 10:00 | A03 4-403
- Freitag, 1.12.2023 8:00 - 10:00 | A03 4-403
- Donnerstag, 7.12.2023 8:00 - 10:00 | A03 4-403
- Freitag, 8.12.2023 8:00 - 10:00 | A03 4-403
- Donnerstag, 14.12.2023 8:00 - 10:00 | A03 4-403
- Freitag, 15.12.2023 8:00 - 10:00 | A03 4-403
- Donnerstag, 21.12.2023 8:00 - 10:00 | A03 4-403
- Donnerstag, 11.1.2024 8:00 - 10:00 | A03 4-403
- Freitag, 12.1.2024 8:00 - 10:00 | A03 4-403
- Donnerstag, 18.1.2024 8:00 - 10:00 | A03 4-403
- Freitag, 19.1.2024 8:00 - 10:00 | A03 4-403
- Donnerstag, 25.1.2024 8:00 - 10:00 | A03 4-403
- Freitag, 26.1.2024 8:00 - 10:00 | A03 4-403
- Donnerstag, 1.2.2024 8:00 - 10:00 | A03 4-403
- Freitag, 2.2.2024 8:00 - 10:00 | A03 4-403
- Freitag, 8.3.2024 8:30 - 10:45 | A05-1-135
- Dienstag, 9.4.2024 15:30 - 17:45 | A05-1-135
Beschreibung
1. Mathematical modeling of uncertainty in linear and nonlinear dynamic systems
2. Stochastic modeling approaches
• Probability distributions
• Bayesian state estimation for discrete-time systems (linear/nonlinear) and for continuous-time systems (linear)
• Linear estimation techniques in an extended state-space (Carleman linearization for special system classes)
• Monte-Carlo methods
3. Estimation of states, parameters and simulation of uncertain processes
• Outlook: Markov models
• Outlook: Bayesian networks
4. Set-based approaches
• Set-based algorithms: Forward-backward contractor and bisection techniques
• Interval methods for a verified solution of ordinary differential equations and for a stability proof of uncertain systems
• Estimation of states and parameters as well as simulation of uncertain processes
5. Outlook: Synthesis of controllers and state observers under an explicit description of uncertainty
2. Stochastic modeling approaches
• Probability distributions
• Bayesian state estimation for discrete-time systems (linear/nonlinear) and for continuous-time systems (linear)
• Linear estimation techniques in an extended state-space (Carleman linearization for special system classes)
• Monte-Carlo methods
3. Estimation of states, parameters and simulation of uncertain processes
• Outlook: Markov models
• Outlook: Bayesian networks
4. Set-based approaches
• Set-based algorithms: Forward-backward contractor and bisection techniques
• Interval methods for a verified solution of ordinary differential equations and for a stability proof of uncertain systems
• Estimation of states and parameters as well as simulation of uncertain processes
5. Outlook: Synthesis of controllers and state observers under an explicit description of uncertainty
Lehrende
SWS
4