- Please register to State Estimation on elearning.ovgu.de.
Time and Location
- summer semester only
- see lsf.ovgu.de
- It is a frequent situation in process operation and process control that the quantities one is interested in cannot be measured directly. State estimation (sometimes also called model based measurement) is a technique that reconstructs the state vector of a system from online simulations in combination with available measurements. This course introduces advanced approaches of state estimation for different classes of systems. In the first part, observability criteria for linear systems and the classical Luenberger observer are revisited. The second part is dedicated to the Kalman filter as the workhorse of state estimation and to its nonlinear extensions. The third part discusses observation techniques for nonlinear systems.
- Observability of LTI systems
- Luenberger observer for LTI systems
- Kalman filter for linear time discrete and time continuous systems
- Extended Kalman filter
- Unscented Kalman filter
- Kalman filter update with constraints
- Nonlinear observers