Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
A comparative study on Kalman filtering techniques designed for state estimation of industrial AC drive systems
Date
2004-06-05
Author
Akin, B
Orguner, Umut
Ersak, A
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
191
views
0
downloads
Cite This
In this paper, two different Kalman Filtering techniques, Unscented Kalman Filter (UKF) and Extended Kalman Filter (EKF) are investigated and compared both experimentally and theoretically. These non-linear, stochastic observers are employed as a state estimation tool in field-oriented control (FOC) of sensorless AC drives in this work. Using the superiorities of Kalman filtering, rotor speed and dq-axis fluxes of an induction motor are estimated only with the sensed stator currents and voltages information. In order to compare the estimation performances of the observers explicitly, both of the observers are designed for the same motor model and run with the same covariance matrices under the same conditions. In the simulation results it is shown that, UKF, whose several intrinsic properties suggest its use over EKF in highly nonlinear systems, has more satisfactory rotor speed and flux estimates, which are the most critical states for FOC. These simulation results are supported with experimental results.
Subject Keywords
Induction motor
,
FOC
,
Speed estimation
,
UKF
,
EKF
,
Kalman filtering
,
State observer
URI
https://hdl.handle.net/11511/46848
DOI
https://doi.org/10.1109/icmech.2004.1364479
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
An experimental performance test of a derivative-free non-linear state observer designed for sensorless AC drives
Akın, B; Orguner, Umut; Ersak, Aydın (2004-06-05)
In this paper, a new Kalman Filtering technique, Unscented Kalman Filter (UKF) is utilized both experimentally and theoretically as a state estimation tool in field-oriented control (FOC) of sensorless AC drives. Using the advantages of this recent derivative-free nonlinear estimation tool, rotor speed and dq-axis fluxes of an induction motor are estimated only with the sensed stator currents and voltages information. In a previous study, simulations has shown that, UKF, whose several intrinsic properties s...
A Comparative Study on Non-Linear State Estimators Applied to Sensorless AC Drives: MRAS and Kalman Filter
Akin, Bilal; Orguner, Umut; Ersak, Aydin; Ehsani, Mehrdad (2004-11-06)
In this paper, two different nonlinear estimators applied to sensorless AC drives, Kalman Filtering techniques (EKF and UKF) and Model Reference Adaptive System (back emf ans reactive power models), are discussed and compared to each other. Both of the observer types are studied and analyzed both experimentally and theoretically. In order to compare the observers precisely, the observers are tested under the identical conditions.
State estimation of induction motor using unscented Kalman filter
Akin, B; Orguner, Umut; Ersak, A (2003-06-25)
In this paper, a new estimation technique, unscented Kalman filter (UKF) is applied to state observation in field oriented control (FOC) of induction motor. UKF, a recent derivative-free nonlinear estimation tool, is used for estimating rotor speed and fluxes using sensed stator current and voltages. In the simulations, UKF, whose several intrinsic properties suggest its use over EKF in highly nonlinear systems, turned out to be very similar to EKF in flux estimates. The simulation results also show that UK...
Comparison of Bayesian MAP Estimation and Kalman Filter Methods in the Solution of Spatio-Temporal Inverse ECG Problem
Aydin, Umit; Serinağaoğlu Doğrusöz, Yeşim (2009-09-12)
In this study, spatial only, and spatio-temporal Bayesian Maximum a Posteriori (MAP) methods and an another spatio-temporal method, the Kalman filter approach, are used to solve the inverse electrocardiography (ECG) problem. Training sets are used to obtain the required a priori information for all methods. Two different approaches are employed to calculate the state transition matrix (STM), which maps the epicardial potentials in two consecutive time instants in the Kalman filter method. The first one uses...
An ab initio study of dissociative adsorption of H-2 on FeTi surfaces
Izanlou, A.; Aydınol, Mehmet Kadri (2010-02-01)
Dissociative adsorption of H-2 on clean FeTi (001), (110) and (111) surfaces is investigated via ab initio pseudopotential-plane wave method. Adsorption energies of H atom and H-2 molecule on Fe and Ti terminated (001) and (111) and FeTi (110) surfaces are calculated on high symmetry adsorption sites. It is shown that, top site is the most stable site for horizontal H-2 molecule adsorption on (001) and (111) surfaces for both terminations. The most favorable site for H atom adsorption on these surfaces howe...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
B. Akin, U. Orguner, and A. Ersak, “A comparative study on Kalman filtering techniques designed for state estimation of industrial AC drive systems,” 2004, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/46848.