Modeling and Simulation of Position Estimation of Switched Reluctance Motor with Artificial Neural Networks

Transcription

1 Wold Academy of Science, Engineeing and Technology 57 9 Modeling and Simulaion of Poiion Eimaion of Swiched Relucance Moo wih Aificial Neual Newok Oguz Uun, and Edal Bekioglu Abac In he een udy, oiion eimaion of wiched elucance moo (SRM) ha been achieved on he bai of he aificial neual newok (ANN). The ANN can eimae he oo oiion wihou uing an ea oo oiion eno by meauing he hae flu linkage and hae cuen. Flu linkage-hae cuen-oo oiion daa e and uevied backoagaion leaning algoihm ae ued in aining of he ANN baed oiion eimao. A 4-hae SRM have been ued o veify he accuacy and feaibiliy of he ooed oiion eimao. Simulaion eul how ha he ooed oiion eimao give ecie and accuae oiion eimaion fo boh unde he low and high level efeence eed of he SRM. Keywod Aificial neual newok, modeling and imulaion, oiion obeve, wiched elucance moo. I. INTRODUCTION HE wiched elucance moo ae imle, low co, and T obu moo ha make hem favoable fo vaiable evo dive alicaion. Howeve, oque ile, acouic noie and oo oiion eno equiemen ae he main diadvanage of he moo [1-]. Seveal mehod have been inoduced o achieve oiion enole oeaion of he SRM in he ecen yea. The main incile ued in he oiion eimaion i he deivaion of oo oiion infomaion fom he ao cicui meauemen o hei deived aamee [3]. Thee aamee ae mainly ao hae volage and cuen. The flu linkage i deived fom hee aamee. Poiion eimaion i achieved by uing flu linkage and hae cuen. The vaiou enole mehod ublihed in he lieaue have been eenively claified in he Ref. [4]. The caabiliy of ANN make hem ideal oluion fo eimaion of aamee, modeling nonlinea chaaceiic, and comenaing diubance and unceainie in conol yem. Recenly, ANN echnique have aken lace in ealime conol and modeling alicaion owing o inceae in micooceo/micoconolle eed and caabiliie. Vaiou udie abou enole aamee eimaion and conol of SRM uing inelligen echnique have been eoed in he lieaue. Neual newok baed enole oiion eimaion of SRM ha been eened in [5-8]. Senole oiion conol of SRM baed on ANN wihou uing flu eimao i eoed in [9]. Cuen-flu-oo oiion look-u able baed oiion enole oeaion of SRM i given in [1]. NN i ued o conuc he look-u able in ha udy. Roo oiion eimaion of a SRM involving flu cuen mehod uing adaive newok fuzzy infeence yem (ANFIS) i eened in [11]. An aoach of ingle neuon PID conol fo oiion enole wiched elucance moo (SRM) baed on adial bai funcion NN i ooed in [1]. ANN and ANFIS baed enole oiion eimaion echnique wih digial flu linkage calculaion ae eened in [13]. Senole conol of ingle wich-baed wiched elucance moo dive uing neual newok ha been imlemened in [14-15]. The aim of hi udy i o develo a oiion eimao ha can be eaily ued fo he SRM oiion conol alicaion. A enole oiion eimaion of he SRM ha been buil on he bai of ANN. Poiion of he SRM i obained fom he ANN model a a funcion of he hae cuen and he flu linkage. The node numbe of hidden laye have been choen a oible a a minimum level. Taking ino accoun he eal alicaion, a mulilaye feedfowad NN (MFNN) ucue have been deigned in he udy o deceae he oce ime. A a eul, he comuaional load of oceo ha been deceaed. Simulaion udie have been efomed o een validiy and alicabiliy of he ooed oiion obeve. The obained eul eveal ha he develoed oiion obeve give effecive and accuae eul. II. ANN-BASED ROTOR POSITION ESTIMATOR Modeling and imulaion udie efomed in hi udy o deign he oiion obeve ae buil on he 4 hae, 5.5HP, 15 m, and 8/6 ole SRM given in Fig. 1. Oguz Uun i wih he Aban Izze Bayal Univeiy, Faculy of Engineeing and Achiecue, Deamen of Elecical and Eleconic Engineeing, Bolu, 148 Tukey ( oguzuun@ibu.edu.). Edal Bekioglu i wih Aban Izze Bayal Univeiy, Faculy of Engineeing and Achiecue, Deamen of Elecical and Eleconic Engineeing, Bolu, 148 Tukey (coeonding auho hone: ; fa: ; bekioglu_e@ibu.edu.). 3

2 Wold Academy of Science, Engineeing and Technology 57 9 A' B' STATOR C' ROTOR D' A A. Feedfowad Algoihm P laye: I i he inu laye and he eny of hi laye, i and ψ ae he value of he cuen and flu linkage daa, eecively. The inu and he ouu of hi laye ae obained a follow. D C B {, ψ } i,and y whee... P () R laye: I i he fi hidden laye. The inu and he ouu of hi laye ae obained a follow. Fig. 1 Co ecion of 8/6 ole SRM The newok ucue hown in Fig. i ued fo eimaing he oo oiion by uing ANN. The newok i imila o he newok model given in [16]. The inu of he newok i and ψ ae he hae cuen and he flu linkage daa ae obained fom he non-linea full model of he SRM [17]. The ouu of newok i he acual oo oiion e haeθˆ comued accoding o he inu. θ i he deied oo oiion e hae, while e i he eo beween acual and deied oo oiion value. The newok i comoed of 4 laye: an inu laye ( P ), wo hidden laye ( R, S ), and an ouu laye (T ). i ψ, y w δ, y w, y w, y P R S T δ Fig. Achiecue of he neual newok fo modeling of he inducance and flu linkage In node a he R, S, and T, he ouu of he node i calculaed by uing acivaion funcion given a follow; c y ( ) e (1) σ Hee, eeen inu of he node, y eeen ouu of he node elaed o, c cene of Gauian funcion, and σ i widh. Feedfowad model of he laye can be decibed a follow. δ θˆ θ e P y. w, and y y ) whee... R (3) ( S laye: I i he econd hidden laye. The inu and he ouu of hi laye ae obained a follow. R y. w,and y y ) whee... S (4) ( T laye: I i he ouu laye. The inu and he ouu of hi laye ae obained a follow. S y. w, and y y ) (5) While he em above laye ae combined; inducance model can be eeed a follow, S R P ˆ θ y y y y. w. w. w (6) The eimaed oo oiion model i obained a a eul of he feedfowad algoihm. Once he feedfowad algoihm ha been comleed, he backoagaion leaning algoihm i ealized fo he oimizaion of he weigh in he newok. B. Backoogaion Leaning Algoihm To decibe he online leaning algoihm of he ANN uing he uevied gadien decen mehod, fi he enegy funcion E i choen a follow [16], ( 1 E( k ) e ( k ), whee k 1, L, K (7) K denoe oal numbe of inu-ouu aen. Eo value fo each aen, e( k) θ ( k) ˆ θ ( k) (8) 31

3 Wold Academy of Science, Engineeing and Technology 57 9 θ i he deied value ˆ ( k) whee (k) θ acual value. Accodingly, all he weigh in newok ae adued a follow, T laye: A no weigh i adued on hi laye, eo value in he newok ouu i backoagaed by making ue of chain ule. S laye: Weigh change on hi laye follow, ψˆ R laye: Weigh change on hi laye a follow, P laye: Weigh change on hi laye a follow, ae calculaed a (9) Δ w ae calculaed (1) ψ Δ w ae calculaed efeence i given in Fig. 3. The cuen and eed gahic have been given in Fig. 4 and Fig. 5, eecively. Acual and deied oo oiion gahic fo he 3 ad/ efeence eed have been given in Fig. 6, and he cuen wavefom a hi iuaion ha been given in Fig. 7. A een fom he figue, he acual oo oiion follow he deied oo oiion eciely. The hae cuen i 9 A a i i fied a he efeence age. Acual and deied oo oiion gahic fo he 15 ad/ efeence eed have been given in Fig. 8, and he cuen wavefom a hi iuaion ha been given in Fig. 9. A een fom he figue, he acual oo oiion follow he deied oo oiion eciely. Due o inceae in he efeence eed, he hae cuen ha deceaed. The hae cuen i.65 A a hi oeaing condiion. A een fom he oiion gahic, acual oiion ae following he deied oiion accuaely fo boh he low and he high efeence eed. Thee i a lighly diffeence beween acual and deied oiion only a he oin of hae cuen change. Thee change caued fom he hae anien oin. Phae cuen ae given fo he 6º mechanical oo oiion (one ole movemen) o how he effec of he hae change and he wiching angle (Fig. 1). A een fom he figue, he effec of he each hae i 15º. 6 5, ψˆ, and Δ w, w (11) ae leaning coefficien. Weigh change Δ, and Δ w ae obained a follow, oo oiion( degee ) 4 3 w ( k + 1) w ( k) + (1) w ( k + 1) w ( k) + (13) w ( k + 1) w ( k) + (14) In he beginning of newok aining, weigh value can be choen in elaion wih eviou daa o hey can be choen andom a well. In hi udy, he iniial value [,1] of weigh ae given andomly, and hee value ae limied a hee value duing he aining. Leaning coefficien ae alo eleced in [,1] ineval. III. SIMULATION RESULTS Simulaion udie have been achieved fo eing he efomance of he ANN baed oiion obeve decibed in he Secion II. Simulaion eul ae given fo he low and he high eed efeence, 3 ad/ and 15 ad/, eecively. The efeence cuen ha been fied a 9 A. The obained imulaion eul have been given in Fig Acual and deied oo oiion gahic unde 3-15 ad/ eed hae cuen ( A ) ime() Fig. 3 Acual and deied oo oiion fo 3-15 ad/ ime() Fig. 4 Phae cuen fo 3-15 ad/ 3

4 Wold Academy of Science, Engineeing and Technology 57 9 eed (ad/) ime() Fig. 5 Roo eed oo oiion( degee ) ime() Fig. 8 Acual and deied oo oiion fo 15 ad/ oo oiion( degee ) hae cuen ( A ) ime() Fig. 6 Acual and deied oo oiion fo 3 ad/ ime() Fig. 9 Phae cuen fo 3 ad/ hae cuen ( A ) ime() Fig. 7 Phae cuen fo 3 ad/ hae cuen ( A ) and oo oiion (degee) i i i 3 i ime() Fig. 1 Phae cuen and oo oiion 33

5 Wold Academy of Science, Engineeing and Technology 57 9 IV. CONCLUSION A enole oiion obeve ha been deigned fo he 8/6 SRM. ANN baed nonlinea model including feedfowad and backoagaion leaning algoihm ha been conuced o achieve oiion eimaion of he SRM. Poiion of he SRM i obained fom he ANN model a a funcion of hae cuen and flu linkage. The calculaion oce ha been aken ino accoun o aly he develoed model on he eal alicaion effecively. Simulaion udie have been efomed o aove and how caabiliy of he ANN baed enole oiion eimao. The imulaion eul how ha he develoed cheme give ueio oiion chaaceiic of he SRM. REFERENCES [1] R. Kihnan, Swiched Relucance Moo Dive: Modeling, Simulaion, Analyi, Deign, and Alicaion. Boca Raon, FL: CRC Pe, Jun. 1. [] E. Mee, A oo oiion eimao fo wiched elucance moo uing CMAC, Enegy Conveion and Managemen, 44 (3) [3] E. Mee and D. A. Toey, An aoach fo enole oiion eimaion fo wiched elucance moo uing aificial neual newok, IEEE Tan. Powe Elecon., vol. 17, no. 1, Jan., [4] M. Ehani, and B. Fahimi, Eliminaion of oiion eno in wiched elucance moo: Sae of he a and fuue end, IEEE Tan. Ind. Elecon., vol. 49, no. 1, Feb., [5] D.S. Reay, Y. Deouky, and B.W. William, The ue of neual newok o enhance enole oiion deecion in wiched elucance moo, IEEE Inenaional Confeence on Syem, Man, and Cybeneic, 1998, [6] H. S. Ooi and T. C. Geen, Simulaion of neual newok o enole conol of wiched elucance moo, in Poc. IEEE Powe Elecon. Vaiable Seed Dive, Se. 1998, [7] D. S. Reay and B. W. William, Senole oiion deecion uing neual newok fo he conol of wiched elucance moo, in Poc. IEEE In. Conf. Conol Al., vol., Aug. 1999, [8] T. Lachman, T. R. Mohamad, and S. P. Teo, Senole oiion eimaion of wiched elucance moo uing aificial neual newok, in Poc. IEEE In. Conf. Robo., Inell. Sy. Signal Poce., vol. 1, Oc. 3,. 5. [9] B. Enayai, and S.M. Saghaiannead, Senole oiion conol of wiched elucance moo baed on aificial neual newok, IEEE ISIE 6, July 9-1, 6, Moneal, Quebec, Canada, [1] W.S. Baik, M.H. Kim, N.H. Kim, and D.H. Kim, Poiion enole conol yem of m uing neual newok, Poc. IEEE PESC, vol. 5, Jun. 4, [11] S. Paamaivam, R. Aumugam, B. Umaniahewai, Accuae oo oiion eimaion fo wiched elucance moo uing ANFIS, Confeence on Convegen Technologie fo Aia-Pacific Region TENCON 3, Volume 4, Oc [1] T. Shi, C. Xia, M. Wang and Qian Zhang, Single neual PID conol fo enole wiched elucance moo baed on RBF neual newok, Poceeding of he 6h Wold Conge on Inelligen Conol and Auomaion, June 1-3, 6, Dalian, China, [13] S. Paamaivam, S. Viayan, M. Vaudevan, R. Aumugam, and Ramu Kihnan, Real-ime veificaion of AI baed oo oiion eimaion echnique fo a 6/4 ole wiched elucance moo dive, IEEE Tanacion on Magneic, vol. 43, no. 7, July 7, [14] C. Hudon, N:S. Lobo, R. Kihnan, Senole conol of ingle wich baed wiched elucance moo dive uing neual newok, The 3h Annual Confeence of he IEEE Induial Eleconic Sociey, Novembe -6, Buan, Koea, 4, [15] C. A. Hudon, N. S. Lobo, and R. Kihnan, Senole Conol of Single Swich-Baed Swiched Relucance Moo Dive Uing Neual Newok, IEEE Tanacion On Induial Eleconic, vol. 55, no. 1, Januay 8, [16] O. Uun, Meauemen and eal-ime modeling of inducance and flu linkage in wiched elucance moo, IEEE Tanacion on Magneic, In e. [17] O. Uun, A nonlinea full model of wiched elucance moo wih aificial neual newok, Enegy Conveion and Managemen, doi:1.116/.enconman Oguz Uun (M 7) and eceived hi BSc, MSc, and PhD degee in he Elecical Technologie Educaion fom he Gazi Univeiy. He woked a a eeach aian a he Gazi Univeiy beween 1997 and 7. He i cuenly aian ofeo a he Deamen of Elecical and Eleconic Engineeing, Faculy of Engineeing and Achiecue, Aban Izze Bayal Univeiy. Hi eeach inee ae aificial neual newok, geneic algoihm, digial ignal oceo, dive and conol of elecical machine. Edal Bekioglu (M 8) eceived hi BSc, MSc, and PhD degee in he Elecical Technologie Educaion fom he Gazi Univeiy. He woked a a eeach aian a he Gazi Univeiy beween 1996 and 3. He i cuenly aian ofeo a he Deamen of Elecical and Eleconic Engineeing, Faculy of Engineeing and Achiecue, Aban Izze Bayal Univeiy. Hi eeach inee ae comue-conolled yem, digial ignal oceo, ecial elecical moo, dive and conol of elecical machine. 34