Abstract
The paper describes a novel online identification algorithm for a two-mass drive system. The multi-layer extended Kalman Filter (MKF) is proposed in the paper. The proposed estimator has two layers. In the first one, three single extended Kalman filters (EKF) are placed. In the second layer, based on the incoming signals from the first layer, the final states and parameters of the two-mass system are calculated. In the considered drive system, the stiffness coefficient of the elastic shaft and the time constant of the load machine is estimated. To improve the quality of estimated states, an additional system based on II types of fuzzy sets is proposed. The application of fuzzy MKF allows for a shorter identification time, as well as improves the accuracy of estimated parameters. The identified parameters of the two-mass system are used to calculate the coefficients of the implemented control structure. Theoretical considerations are supported by simulations and experimental tests.
| Original language | English |
|---|---|
| Article number | e146107 |
| Journal | Bulletin of the Polish Academy of Sciences: Technical Sciences |
| Volume | 71 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2023 |
Keywords
- Kalman filter
- electrical drives
- multi-layer estimator
- state estimation
- torsional vibration
ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics
- Information Systems
- General Engineering
- Computer Networks and Communications
- Artificial Intelligence