Research Article
BibTex RIS Cite

Uyarlamalı genişletilmiş Kalman filtresi-tabanlı sabit anahtarlama frekanslı hız-algılayıcısız doğrudan moment kontrollü sürücü sisteminin tasarımı

Year 2020, Volume: 26 Issue: 5, 860 - 867, 23.10.2020

Abstract

Bu çalışmada, hız-algılayıcısızasenkron motor (ASM) kontrolü için uyarlamalı genişletilmiş Kalman filtresi (UGKF) tabanlı sabit anahtarlama frekanslı doğrudan moment kontrollü (SAF-DMK’lı) sürücü sisteminin tasarımı gerçekleştirilmektedir. Stator akısı tabanlı ASM modelini kullanan UGKF ile GKF’lerin kestirim başarımını doğrudan etkileyen ve geleneksel GKF’lerde sabit olarak kabul edilen sistem gürültüsü kovaryans matrisi çalışma koşullarına göre çevrimiçi olarak güncellenmektedir. UGKF’nin geleneksel DMK’lı sürücü yerine, SAF-DMK’lı sürücüye dahil edilmesinin nedeni geleneksel DMK kontrolündeki moment dalgalanmalarının ve değişken anahtarlama frekansından kaynaklanan anahtarlama kayıplarının azaltılmasıdır. SAF-DMK’lı sürücünün ihtiyaç duyduğu stator akısının stator duran eksen takımı bileşenlerine ve rotor mekanik açısal hızına ek olarak, stator akımının stator duran eksen takımı bileşenleri ve yük momenti önerilen UGKF tabanlı gözlemleyici ile kestirilmektedir. Yük momenti kestirimi ile önerilen hız-algılayıcısız sürücü sisteminin bozucu yük momenti değişimlerine karşı dayanıklı olması sağlanmaktadır. Son olarak, önerilen UGKF-tabanlı hız-algılayıcısız SAF-DMK’lı sürücü sistemi benzetim çalışmaları altında doğrulanmaktadır.

References

  • [1]Alsofyani IM, Idris NRN.“Lookup-table-based DTC of induction machines with improved flux regulation and extended Kalman filter state estimator at low-speed operation”. IEEE Transactions on Industrial Informatics, 12(4), 1412-1425, 2016.
  • [2]Kumar RH, Iqbal A, Lenin NC.“Review of recent advancements of direct torque control in induction motor drives-a decade of progress”. IET Power Electronics, 11(1), 1-15, 2018.
  • [3]Gdaim S, Mtibaa A, Mimouni MF.“Design and experimental implementation of DTC of an induction machine based on fuzzy logic control on FPGA”. IEEE Transactions on Fuzzy Systems, 23(3), 644-655, 2015.
  • [4]Krim S, Gdaim S, Mtibaa A, Mimouni MF.“Contribution of the FPGAs for complex control algorithms: sensorless DTFC with an EKF of an induction motor”. International Journal of Automation and Computing, 16(2), 226-237, 2019.
  • [5]Ouhrouche M, Errouissi R, Trzynadlowski AM, Tehrani KA, Benzaioua A.“A novel predictive direct torque controller for induction motor drives”. IEEE Transactions on Industrial Electronics, 63(8), 5221-5230, 2016.
  • [6]Wang D, Zhang L, Zhang J, Zhao X, Lin X.“A hybrid speed sensorless control of induction machine based on adaptive flux observer and high-frequency signal injection method”. 2018 IEEE 19thWorkshop on Control and Modeling for Power Electronics (COMPEL), Padua, Italy, 25-28 June2018.
  • [7]Basic D, Malrait F, Rouchon P.“Current controller for low-frequency signal injection and rotor flux position tracking at low speeds”. IEEE Transactions on Industrial Electronics, 58(9), 4010-4022, 2011.
  • [8]Xu D, Wang B, Zhang G, Wang G, Yu Y.“A review of sensorless control methods for AC motor drives”. CES Transactions on Electrical Machines and Systems, 2(1), 104-115, 2018.
  • [9]Pal A, Das S, Chattopadhyay AK.“An improved rotor flux space vector based MRAS for field-oriented control of induction motor drives”. IEEE Transactions on Power Electronics, 33(6), 5131-5141, 2018.
  • [10]Zaky MS, Metwaly MK, Azazi HZ, Deraz SA.“A new adaptive SMO for speed estimation of sensorless induction motor drives at zero and very low frequencies”. IEEE Transactions on Industrial Electronics, 65(9), 6901-6911, 2018.
  • [11]You J, Wu W, WangY.“An adaptive luenberger observer for speed-sensorless estimation of induction machines”. 2018 Annual American Control Conference (ACC), Milwaukee, WI,USA, 27-29 June 2018.
  • [12]Barut M, Demir R, Zerdali E, Inan R.“Real-time implementation of bi input-extended Kalman filter-based estimator for speed-sensorless control of induction motors”. IEEE Transactions on Industrial Electronics, 59(11), 4197-4206, 2012.
  • [13]Zhang Y, Yin Z, Li G, Liu J, Tong X.“A novel speed estimation method of induction motors using real-time adaptive extended Kalman filter”. Journal of Electrical Engineering & Technology, 13(1), 287-297, 2018.
  • [14]Yin Z, Li G, Zhang Y, Liu J, Sun X, Zhong Y.“A speed and flux observer of induction motor based on extended Kalman filter and Markov chain”. IEEE Transactions on Power Electronics, 32(9), 7096-7117, 2017.
  • [15]Alonge F, D’Ippolito F, Sferlazza A.“Sensorless control of induction-motor drive based on robust Kalman filter and adaptive speed estimation”. IEEE Transactions on Industrial Electronics, 61(3), 1444-1453, 2014.
  • [16]Yin ZG, Zhao C, Zhong YR, Liu J.“Research on robust performance of speed-sensorless vector control for the induction motor using an interfacing multiple-model extended Kalman filter”. IEEE Transactions on PowerElectronics, 29(6), 3011-3019, 2014.
  • [17]Smidl V, Peroutka Z.“Advantages of square-root extended kalman filter for sensorless control of ACdrives”. IEEE Transactions on Industrial Electronics, 59(11), 4189-4196, 2012.
  • [18]Jafarzadeh S, Lascu C, FadaliMS.“Square root unscented Kalman filters for state estimation of induction motor drives”. IEEE Transactions on Industry Applications, 49(1), 92-99, 2013.
  • [19]Alonge F, Cangemi T, D’Ippolito F, Fagiolini A, Sferlazza A.“Convergence analysis of extendedKalman filter for sensorless control of ınduction motor”. IEEE Transactions on Industrial Electronics, 62(4), 2341-2352, 2015.
  • [20]Zerdali E, Barut M.“The comparisons of optimized extended kalman filters for speed-sensorless control of induction motors”. IEEE Transactions on Industrial Electronics, 64(6), 4340-4351, 2017.
  • [21]Demir R, Barut M.“Novel hybrid estimator based on model reference adaptive system and extended Kalman filter for speed-sensorless induction motor control”. Transactions of the Institute of Measurement and Control, 40(13), 3884-3898, 2018.
  • [22]Almagbile A, Wang J, Ding W.“Evaluating the performance of adaptive Kalman filter methods in GPS/INS integration”. Journal of Global Positioning Systems, 9(1), 33-40, 2010.
  • [23]Dróżdż K.“Estimation of the mechanical state variables of the two-mass system using fuzzy adaptive Kalman filter -experimental study”. 2015 IEEE 2ndInternational Conference on Cybernetics (CYBCONF), Gdynia, Poland,24-26 June2015.
  • [24]Aydin M, Gokasan M, Bogosyan S.“Fuzzy based parameter tuning of EKF observers for sensorless control of induction motors”.Automation and Motion 2014 International Symposium on Power Electronics, Electrical Drives, Ischia, Italy, 18-20 June2014.
  • [25]Mohamed AH, Schwarz KP.“Adaptive Kalman filtering for INS/GPS”. Journal of Geodesy, 73(4), 193-203, 1999.
  • [26]Zerdali E, Yildiz R, Inan R, Demir R, Barut M.“Adaptive fading extended Kalmanfilter based speed-sensorless induction motor drive”. 2018 XIII International Conference on Electrical Machines (ICEM), Alexandroupoli, Greece, 3-6 September2018.
  • [27]Yin Z, Zhao C, Zhong YR, Liu J.“Research on robust performance of speed-sensorless vector control for the induction motor using an interfacing multiple-model extended Kalman filter”. IEEE Transactions on Power Electronics, 29(6), 3011-3019, 2014.
  • [28]Barut M, Bogosyan S, Gokasan M.“Speed-sensorless estimation for induction motors using extended Kalman filters”. IEEE Transactions on Industrial Electronics, 54(1), 272-280, 2007.
  • [29]Jwo DJ, Chung FC, Weng TP.Adaptive Kalman Filter for Navigation Sensor Fusion.Editors: Ciza Thomas.Sensor Fusion and its Applications, 65-90, Rijeka, Croatia, Intech Sciyo Press, 2010.
  • [30] Boutayeb M, Aubry D.“A strong tracking extended Kalman observer for nonlinear discrete-time systems”. IEEE Transactions on Automatic Control, 44(8), 1550-1556, 1999.
  • [31] Xia Q, Rao M, Ying Y, Shen X.“Adaptive fading Kalman filter with an application”. Automatica, 30(8),1333-1338, 1994.
  • [32]İnan R, Demi̇r R, Barut M.“Asenkron motorun karma kestirici tabanlı hız-algılayıcılı doğrudan vektör kontrolü”. Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 7(2), 612-623, 2018.
  • [33]Idris NRN, Yatim AHM. “Direct torque control of induction machines with constant switching frequency and reduced torque ripple”. IEEE Transactions on Industrial Electronics, 51(4), 758-767, 2004
Year 2020, Volume: 26 Issue: 5, 860 - 867, 23.10.2020

Abstract

References

  • [1]Alsofyani IM, Idris NRN.“Lookup-table-based DTC of induction machines with improved flux regulation and extended Kalman filter state estimator at low-speed operation”. IEEE Transactions on Industrial Informatics, 12(4), 1412-1425, 2016.
  • [2]Kumar RH, Iqbal A, Lenin NC.“Review of recent advancements of direct torque control in induction motor drives-a decade of progress”. IET Power Electronics, 11(1), 1-15, 2018.
  • [3]Gdaim S, Mtibaa A, Mimouni MF.“Design and experimental implementation of DTC of an induction machine based on fuzzy logic control on FPGA”. IEEE Transactions on Fuzzy Systems, 23(3), 644-655, 2015.
  • [4]Krim S, Gdaim S, Mtibaa A, Mimouni MF.“Contribution of the FPGAs for complex control algorithms: sensorless DTFC with an EKF of an induction motor”. International Journal of Automation and Computing, 16(2), 226-237, 2019.
  • [5]Ouhrouche M, Errouissi R, Trzynadlowski AM, Tehrani KA, Benzaioua A.“A novel predictive direct torque controller for induction motor drives”. IEEE Transactions on Industrial Electronics, 63(8), 5221-5230, 2016.
  • [6]Wang D, Zhang L, Zhang J, Zhao X, Lin X.“A hybrid speed sensorless control of induction machine based on adaptive flux observer and high-frequency signal injection method”. 2018 IEEE 19thWorkshop on Control and Modeling for Power Electronics (COMPEL), Padua, Italy, 25-28 June2018.
  • [7]Basic D, Malrait F, Rouchon P.“Current controller for low-frequency signal injection and rotor flux position tracking at low speeds”. IEEE Transactions on Industrial Electronics, 58(9), 4010-4022, 2011.
  • [8]Xu D, Wang B, Zhang G, Wang G, Yu Y.“A review of sensorless control methods for AC motor drives”. CES Transactions on Electrical Machines and Systems, 2(1), 104-115, 2018.
  • [9]Pal A, Das S, Chattopadhyay AK.“An improved rotor flux space vector based MRAS for field-oriented control of induction motor drives”. IEEE Transactions on Power Electronics, 33(6), 5131-5141, 2018.
  • [10]Zaky MS, Metwaly MK, Azazi HZ, Deraz SA.“A new adaptive SMO for speed estimation of sensorless induction motor drives at zero and very low frequencies”. IEEE Transactions on Industrial Electronics, 65(9), 6901-6911, 2018.
  • [11]You J, Wu W, WangY.“An adaptive luenberger observer for speed-sensorless estimation of induction machines”. 2018 Annual American Control Conference (ACC), Milwaukee, WI,USA, 27-29 June 2018.
  • [12]Barut M, Demir R, Zerdali E, Inan R.“Real-time implementation of bi input-extended Kalman filter-based estimator for speed-sensorless control of induction motors”. IEEE Transactions on Industrial Electronics, 59(11), 4197-4206, 2012.
  • [13]Zhang Y, Yin Z, Li G, Liu J, Tong X.“A novel speed estimation method of induction motors using real-time adaptive extended Kalman filter”. Journal of Electrical Engineering & Technology, 13(1), 287-297, 2018.
  • [14]Yin Z, Li G, Zhang Y, Liu J, Sun X, Zhong Y.“A speed and flux observer of induction motor based on extended Kalman filter and Markov chain”. IEEE Transactions on Power Electronics, 32(9), 7096-7117, 2017.
  • [15]Alonge F, D’Ippolito F, Sferlazza A.“Sensorless control of induction-motor drive based on robust Kalman filter and adaptive speed estimation”. IEEE Transactions on Industrial Electronics, 61(3), 1444-1453, 2014.
  • [16]Yin ZG, Zhao C, Zhong YR, Liu J.“Research on robust performance of speed-sensorless vector control for the induction motor using an interfacing multiple-model extended Kalman filter”. IEEE Transactions on PowerElectronics, 29(6), 3011-3019, 2014.
  • [17]Smidl V, Peroutka Z.“Advantages of square-root extended kalman filter for sensorless control of ACdrives”. IEEE Transactions on Industrial Electronics, 59(11), 4189-4196, 2012.
  • [18]Jafarzadeh S, Lascu C, FadaliMS.“Square root unscented Kalman filters for state estimation of induction motor drives”. IEEE Transactions on Industry Applications, 49(1), 92-99, 2013.
  • [19]Alonge F, Cangemi T, D’Ippolito F, Fagiolini A, Sferlazza A.“Convergence analysis of extendedKalman filter for sensorless control of ınduction motor”. IEEE Transactions on Industrial Electronics, 62(4), 2341-2352, 2015.
  • [20]Zerdali E, Barut M.“The comparisons of optimized extended kalman filters for speed-sensorless control of induction motors”. IEEE Transactions on Industrial Electronics, 64(6), 4340-4351, 2017.
  • [21]Demir R, Barut M.“Novel hybrid estimator based on model reference adaptive system and extended Kalman filter for speed-sensorless induction motor control”. Transactions of the Institute of Measurement and Control, 40(13), 3884-3898, 2018.
  • [22]Almagbile A, Wang J, Ding W.“Evaluating the performance of adaptive Kalman filter methods in GPS/INS integration”. Journal of Global Positioning Systems, 9(1), 33-40, 2010.
  • [23]Dróżdż K.“Estimation of the mechanical state variables of the two-mass system using fuzzy adaptive Kalman filter -experimental study”. 2015 IEEE 2ndInternational Conference on Cybernetics (CYBCONF), Gdynia, Poland,24-26 June2015.
  • [24]Aydin M, Gokasan M, Bogosyan S.“Fuzzy based parameter tuning of EKF observers for sensorless control of induction motors”.Automation and Motion 2014 International Symposium on Power Electronics, Electrical Drives, Ischia, Italy, 18-20 June2014.
  • [25]Mohamed AH, Schwarz KP.“Adaptive Kalman filtering for INS/GPS”. Journal of Geodesy, 73(4), 193-203, 1999.
  • [26]Zerdali E, Yildiz R, Inan R, Demir R, Barut M.“Adaptive fading extended Kalmanfilter based speed-sensorless induction motor drive”. 2018 XIII International Conference on Electrical Machines (ICEM), Alexandroupoli, Greece, 3-6 September2018.
  • [27]Yin Z, Zhao C, Zhong YR, Liu J.“Research on robust performance of speed-sensorless vector control for the induction motor using an interfacing multiple-model extended Kalman filter”. IEEE Transactions on Power Electronics, 29(6), 3011-3019, 2014.
  • [28]Barut M, Bogosyan S, Gokasan M.“Speed-sensorless estimation for induction motors using extended Kalman filters”. IEEE Transactions on Industrial Electronics, 54(1), 272-280, 2007.
  • [29]Jwo DJ, Chung FC, Weng TP.Adaptive Kalman Filter for Navigation Sensor Fusion.Editors: Ciza Thomas.Sensor Fusion and its Applications, 65-90, Rijeka, Croatia, Intech Sciyo Press, 2010.
  • [30] Boutayeb M, Aubry D.“A strong tracking extended Kalman observer for nonlinear discrete-time systems”. IEEE Transactions on Automatic Control, 44(8), 1550-1556, 1999.
  • [31] Xia Q, Rao M, Ying Y, Shen X.“Adaptive fading Kalman filter with an application”. Automatica, 30(8),1333-1338, 1994.
  • [32]İnan R, Demi̇r R, Barut M.“Asenkron motorun karma kestirici tabanlı hız-algılayıcılı doğrudan vektör kontrolü”. Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 7(2), 612-623, 2018.
  • [33]Idris NRN, Yatim AHM. “Direct torque control of induction machines with constant switching frequency and reduced torque ripple”. IEEE Transactions on Industrial Electronics, 51(4), 758-767, 2004
There are 33 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Research Article
Authors

Remzi İnan This is me

Emrah Zerdali This is me

Publication Date October 23, 2020
Published in Issue Year 2020 Volume: 26 Issue: 5

Cite

APA İnan, R., & Zerdali, E. (2020). Uyarlamalı genişletilmiş Kalman filtresi-tabanlı sabit anahtarlama frekanslı hız-algılayıcısız doğrudan moment kontrollü sürücü sisteminin tasarımı. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 26(5), 860-867.
AMA İnan R, Zerdali E. Uyarlamalı genişletilmiş Kalman filtresi-tabanlı sabit anahtarlama frekanslı hız-algılayıcısız doğrudan moment kontrollü sürücü sisteminin tasarımı. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. October 2020;26(5):860-867.
Chicago İnan, Remzi, and Emrah Zerdali. “Uyarlamalı genişletilmiş Kalman Filtresi-Tabanlı Sabit Anahtarlama Frekanslı hız-algılayıcısız doğrudan Moment Kontrollü sürücü Sisteminin tasarımı”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 26, no. 5 (October 2020): 860-67.
EndNote İnan R, Zerdali E (October 1, 2020) Uyarlamalı genişletilmiş Kalman filtresi-tabanlı sabit anahtarlama frekanslı hız-algılayıcısız doğrudan moment kontrollü sürücü sisteminin tasarımı. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 26 5 860–867.
IEEE R. İnan and E. Zerdali, “Uyarlamalı genişletilmiş Kalman filtresi-tabanlı sabit anahtarlama frekanslı hız-algılayıcısız doğrudan moment kontrollü sürücü sisteminin tasarımı”, Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol. 26, no. 5, pp. 860–867, 2020.
ISNAD İnan, Remzi - Zerdali, Emrah. “Uyarlamalı genişletilmiş Kalman Filtresi-Tabanlı Sabit Anahtarlama Frekanslı hız-algılayıcısız doğrudan Moment Kontrollü sürücü Sisteminin tasarımı”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 26/5 (October 2020), 860-867.
JAMA İnan R, Zerdali E. Uyarlamalı genişletilmiş Kalman filtresi-tabanlı sabit anahtarlama frekanslı hız-algılayıcısız doğrudan moment kontrollü sürücü sisteminin tasarımı. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2020;26:860–867.
MLA İnan, Remzi and Emrah Zerdali. “Uyarlamalı genişletilmiş Kalman Filtresi-Tabanlı Sabit Anahtarlama Frekanslı hız-algılayıcısız doğrudan Moment Kontrollü sürücü Sisteminin tasarımı”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol. 26, no. 5, 2020, pp. 860-7.
Vancouver İnan R, Zerdali E. Uyarlamalı genişletilmiş Kalman filtresi-tabanlı sabit anahtarlama frekanslı hız-algılayıcısız doğrudan moment kontrollü sürücü sisteminin tasarımı. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2020;26(5):860-7.

ESCI_LOGO.png    image001.gif    image002.gif        image003.gif     image004.gif