This article proposes the speed estimation principles dedicated to the observer structures based on the machine mathematical model. The rotor speed is reconstructed based on the mathematical model of a machine by using both adaptive and nonadaptive schemes. The presented principle is generalized to the classical nonlinear system in the vector form and can be applied to induction machines. The proposed rotor speed reconstruction approach is based on an algebraic relationship, and the observer system mathematical model has the same rank as the induction machine. The speed observer structure can be unstable due to the challenge of stabilizing the sensorless control of the induction machine at low-speed, near zero speed, or in the low-speed regenerating mode of operation. As a result, the new stabilizing functions based on Lagrange identity are proposed in this work to improve the range of observer stability. The proposed approach includes newly developed stabilization mechanisms that ensure observer stability under both motoring and regenerating modes of operations at the low rotor speed and improve the observer range of stability. The Lyapunov theorem is used during the design procedure for stability purposes. The simulation and experimental studies are carried out for an induction machine adaptive and nonadaptive full-order observer. The experimental results show that stable operation of the system is obtained, and the range of observer stability is improved, especially at low-speeds and in a regenerating mode of operation, concluding that the proposed solution is suitable for use in industrial applications.
Autorzy
Informacje dodatkowe
- DOI
- Cyfrowy identyfikator dokumentu elektronicznego link otwiera się w nowej karcie 10.1109/tie.2024.3454460
- Kategoria
- Publikacja w czasopiśmie
- Typ
- artykuły w czasopismach dostępnych w wersji elektronicznej [także online]
- Język
- angielski
- Rok wydania
- 2025
Źródło danych: MOSTWiedzy.pl - publikacja "Stabilization Method for Speed Observer of Induction Machine" link otwiera się w nowej karcie