Abstract. Keywords. 1. Introduction. Eric S. Sanches, José A. Santisteban

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1 Engineering, 2014, 6, Published Online October 2014 in SciRes. Comprtive Study of Conventionl, Fuzzy Logic nd Neurl PID Speed Controllers with Torque Ripple Minimiztion for n Axil Mgnetic Flux Switched Reluctnce Motor Eric S. Snches, José A. Sntistebn Electricl Engineering Deprtment, Mechnicl Engineering Postgrdute Progrm (PGMEC), Fluminense Federl University, Niterói, Brzil Emil: ericsnches@vm.uff.br, jsntistebn@vm.uff.br Received 31 July 2014; revised 25 August 2014; ccepted 8 September 2014 Copyright 2014 by uthors nd Scientific Reserch Publishing Inc. This work is licensed under the Cretive Commons Attribution Interntionl License (CC BY). Abstrct Three speed controllers for n xil mgnetic flux switched reluctnce motor with only one sttor, re described nd experimentlly tested. As it is known, when current pulses re imposed in their windings, high ripple torque is obtined. In order to reduce this ripple, control strtegy with modified current shpes is proposed. A workbench consisting of mchine prototype nd the control system bsed on microcontroller ws built. These controllers were: conventionl PID, fuzzy logic PID nd neurl PID type. From experimentl results, the effective reduction of the torque ripple ws confirmed nd the performnce of the controllers ws compred. Keywords Axil Flux SRM, PID Speed Controller, Fuzzy Logic PID Speed Controller, Neurl PID Speed Controller, Torque Ripple Minimiztion, Current Shpe Control Strtegy 1. Introduction The rdil mgnetic flux version of switched reluctnce motors (SRM) hs been widely used in mny vrible speed industril pplictions nd some dvntges hve been reported: high torque output, wide rnge of operting speed, geometricl simplicity, relibility nd robustness [1] [2]. In the cse of n xil flux SRM (AFSRM) the ir gp mgnetic flux is prllel to the rottion xis. As the AFSRM cn hve smller xis length thn the rdil mgnetic flux motor, it is believed tht it is good solution for use in pplictions where size is importnt, How to cite this pper: Snches, E.S. nd Sntistebn, J.A. (2014) Comprtive Study of Conventionl, Fuzzy Logic nd Neurl PID Speed Controllers with Torque Ripple Minimiztion for n Axil Mgnetic Flux Switched Reluctnce Motor. Engineering, 6,

2 E. S. Snches, J. A. Sntistebn s in electric crs, for instnce. The switched reluctnce motor (SRM) nlyses re complex becuse of their doubly slient pole structure nd nonliner mgnetic chrcteristics. The developed torque is nonliner function of the currents pplied to the sttor windings nd their inductnces, which depend on the rotor position. Nevertheless, with n pproprite control system, minimum ripple torque cn be obtined. From literture, it cn be observed tht mny works re relted to rdil flux SRM; however few works re relted to xil flux SRM [3]. Some of them refer to xil flux SRM with two sttors [4]-[6], but in this pper the motor hs only one sttor. With respect to the control strtegies, severl strtegies re reported [7]-[9]. For ordinry rdil flux SRM, the mutul inductnces of the sttor windings re considered smll [10] nd most reserchers do not tke them into ccount. For AFSRM this is not true becuse the mgnetic flux pths re quite different to those found in rdil flux SRM. In this work, the AFSRM self nd mutul inductnces were estimted bsed on the three-dimensionl finite element method nd then they were used in the motor electromechnicl model. When voltges or current pulses re imposed in the sttor windings, the level of torque ripple is high, if compred with other kind of motors, which is the primry disdvntge of SRM s it contributes to the vibrtion nd coustic noise. For this reson, the imposition of different current shpes to reduce the torque ripple ppers s n interesting solution. In this work, the procedure to obtin lterntives shpes is described nd the effectiveness of this strtegy is experimentlly tested in n AFSRM prototype. Even more, in order to evlute the performnce of different kinds of speed controllers, three PID types were implemented: conventionl, fuzzy logic nd neurl bsed pproch. Although in different levels the experimentl results confirm the reduction of torque ripple, there re lso differences with respect to the execution time nd the speed response. 2. The Axil Flux SRM Prototype The prototype hs six poles in the sttor, corresponding to three phses (, b nd c ), nd four poles in the rotor. It is 3-phse 6/4 poles AFSRM, shown in Figure 1. The chrcteristics of the 3-phse 6/4 AFSRM prototype re shown in Tble 1. Tble 1. The chrcteristics of the 3-phse 6/4 xil flux SRM. Prmeter Outer dimeter of rotor nd sttor Inner dimeter of rotor nd sttor poles Shft dimeter Air gp Sttor pole width Rotor pole width Sttor nd rotor poles rc Poles rdil length Sttor yoke thickness Vlue 126 mm 63 mm 40 mm 1.9 mm 34 mm 26 mm mm 5 mm Sttor pole re (xil cross-section) 1039 mm 2 Rotor yoke thickness 17 mm Number of turns per sttor pole 175 Turn wire Coil resistnce Sttor nd rotor cores mteril Motor shft mteril 24 AWG 2.3 Ω Steel SAE-1020 Stinless steel 656

3 E. S. Snches, J. A. Sntistebn Figure 1. The AFSRM prototype. Ech sttor pole hs one coil, so there re six coils nmed 1, 2, b1, b2, c1 nd c2. The sttor nd rotor cores were solid becuse the objective of this work ws the torque ripple minimiztion nd not the loss reduction. 3. Torque Ripple Minimiztion Strtegy Considering tht the motor core is operting in the liner region, the net electromgnetic torque T e for the three phse AFSRM prototype is found s: ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) L11 θ L12 θ L13 θ I θ 1 Te( θ, I, Ib, Ic) = I( θ) Ib( θ) Ic( θ) L21 θ L22 θ L23 θ Ib θ 2 θ L31 θ L32 θ L33 θ Ic θ L = + L + M + M + L (2) L = + M M M + M (3) 12 b 1 1 b21 b 1 2 b22 L = M + M + M M (4) 13 c 1 1 c21 c 1 2 c22 L = + M M M + M (5) 21 b 1 1 2b1 b 1 2 2b2 L = + L + M + M + L (6) 22 bb 1 1 b b2b1 b bb 1 2 b b2b2 b L = + M M M + M (7) 23 cb 1 1 b c2b1 b cb 1 2 b c2b2 b L = M + M + M M (8) 31 c 1 1 2c1 c 1 2 2c2 L = + M M M + M (9) 32 bc 1 1 b b2c1 b bc 1 2 b b2c2 b L = + L + M + M + L (10) 33 cc 1 1 c c2c1 c cc 1 2 c c2c2 c where: L nd M stnd for the self nd mutul inductnces. The rotor position ngle θ, for phse, is considered s 45 when the rotor pole ws completely overlpping with the sttor pole, s depicted in Figure 2, nd this ngle is mesured clockwise. The θ b nd θ c ngles correspond to rotor ngulr positions for phses b nd c, respectively. The reltionships between these ngles re: for θ 30 θ = θ + 30 b (1) (11) θ = θ + 60 c (12) 657

4 E. S. Snches, J. A. Sntistebn STATOR 90 ROTOR STATOR STATOR ROTOR SHAFT ROTOR STATOR ROTOR STATOR STATOR for 30 < θ 60 for 60 < θ 90 Figure 2. Position of rotor pole 45 reltive to sttor pole of the AFSRM prototype. θ = θ + 30 b θ = θ 30 c θ = θ 60 b (13) (14) (15) θ = θ 30 c The reltionship mong the three phses self nd mutul inductnces re: L 22 (θ ) = L 11 (θ ); L b1b1 (θ b ) = L 11 (θ b ); L b2b2 (θ b ) = L b1b1 (θ b ); L c1c1 (θ c ) = L 11 (θ c ); L c2c2 (θ c ) = L c1c1 (θ c ); M 22 (θ ) = M 12 (θ ); M 2b1 (θ ) = M 1b2 (θ ); M 2b2 (θ ) = M 1b1 (θ ); M 2c1 (θ ) = M 1c2 (θ ); M 2c2 (θ ) = M 1c1 (θ ), M b11 (θ ) = M 1b1 (θ ); M b12 (θ ) = M 2b1 (θ ); M b1b2 (θ b ) = M 12 (θ b ); M b1c1 (θ b ) = M 1b1 (θ b ); M b1c2 (θ b ) = M 1b2 (θ b ); M b21 (θ ) = M 1b2 (θ ); M b22 (θ ) = M 2b2 (θ ); M b2b1 (θ b ) = M b1b2 (θ b ); M b2c1 (θ b ) = M b1c2 (θ b ); M b2c2 (θ b ) = M b1c1 (θ b ); M c11 (θ ) = M 1c1 (θ ); M c12 (θ ) = M 2c1 (θ ); M b2b1 (θ b ) = M b1b2 (θ b ); M c1b1 (θ b ) = M b1c1 (θ b ); M c1b2 (θ b ) = M b2c1 (θ b ); M c1c2 (θ c ) = M 12 (θ c ); M c21 (θ ) = M 1c2 (θ ); M c22 (θ ) = M 2c2 (θ ); M c2b1 (θ b ) = M b1c2 (θ b ); M c2b2 (θ b ) = M b2c2 (θ b ); nd M c2c1 (θ c ) = M c1c2 (θ c ). The self nd mutul inductnces were estimted bsed on simultion model using three dimensionl finite element method of the ANSYS Multiphysics softwre [11] with mgneto sttic nlysis. The 96 type solid elements were used in the simultion softwre. In Figure 3, for eleven rotor positions, the self nd mutul inductnces estimted, for phse, re shown. The self-inductnce is represented by L 11 nd the mutul inductnces re nmed M 12, M 1b1, M 1b2, M 1c1 nd M 1c2, respectively. As shown in Figure 3, the self-inductnce hs similr profile to the rdil flux SRM cse, which mens tht the minimum inductnce corresponds to the unligned position (no overlp between rotor nd sttor poles) while the mximum inductnce corresponds to the full lignment position between rotor nd sttor poles. The inductnces profiles repet every 90. From Figure 3, it cn be noted tht the mutul inductnces between the coil 1 nd the other five coils re not negligible. For instnce, the mximum reltionship between them (M 1b1 /L 11 ) is round 0.25 ner 20. In this wy, in order to provide constnt electromgnetic torque for ll rotor positions, pproprited reference currents should be designed. From previous tests in open loop [12], the best current feed strtegy consists of the following sequence of energizing the windings: (16) 658

5 E. S. Snches, J. A. Sntistebn Figure 3. AFSRM self nd mutul inductnces. phses nd b from rotor position 0 to 15 ; only phse from rotor position 15 to 30 ; phses nd c from rotor position 30 to 45 ; only phse c from rotor position 45 to 60 ; phses b nd c from rotor position 60 to 75 ; only phse b from rotor position 75 to 90. This cycle repets ech 90. On the other hnd, to define reference torque without hrmonics, it ws considered s tht generted when current of 3A is imposed in phse, while the rotor position ws 30. In this sitution net electromgnetic torque of Nm ws clculted. Next, for every one degree, the current vlues of the phse were clculted s: from rotor position 15 to 30 I ( θ ) = L + θ ( θ ) L ( θ ) from rotor position 0 to 15 function tht strts in zero nd it then ssumes the vlue clculted with (17) in the rotor position of 15, ws used ( θ ) I θ ( θ 4) (17) = e (18) from rotor position 30 to 45 the I current vlues re clculted from qudrtic Eqution (19) considering tht I c ssumes the vlues of I currents obtined from (18). For exmple, the I c vlue for 35 is equl to the I vlue for 5 ( ) ( ) ( θ ) L ( θ ) ( ) ( ) L θ L θ 2 L θ 2 L θ ( ) ( ) ( ) c 11 c 12 + I θ + + Ic θ I θ θ θ θ θ Lcc 11 cc Ic ( θ) = 0 θ θ The reference currents of phses c nd b re shifted by 30 nd 60 reltive to phse current. All these reference currents re shown in Figure Controllers Description In order to evlute the performnce of different kinds of speed controllers, three PID types were implemented: conventionl, fuzzy logic nd neurl bsed pproch. (19) 659

6 E. S. Snches, J. A. Sntistebn In Figure 5, the conventionl PID structure is shown. As noted, the current references re obtined multiplying the controller output by tble with three outputs, which depend on the ngulr position of the rotor. In our experiments, two tbles were evluted. In the first one, the outputs hve pulsed shpes. The finl effect is torque with high ripple components. In the second cse, the outputs hve modified shpes ccording to Figure 4. As the experimentl results show, the reduction of torque ripple is importnt. In this cse, the PID gins were djusted by simultions using MtLb Simulink softwre, resulting in gins proportionl, integrl nd derivtive, of 16, 3 nd 1, respectively. The controller output ws limited to the intervl of [0, 1]. In Figure 6, the fuzzy or neurl control structure is shown. As noted, the outputs of the controller re directly the current references for the AFSRM. Figure 4. Reference currents wveforms. +. θ REF -. θ PID CONTROLLER CURRENT WAVEFORM TABLE Reference Currents POWER CONVERTER CIRCUIT Current Sensor ω d/dt θ POSITION SENSOR Figure 5. Block digrm of the PID speed control system. Figure 6. Block digrm of the fuzzy or neurl PID speed control system. 660

7 E. S. Snches, J. A. Sntistebn In the cse of the fuzzy controller, the rules were bsed on the observtion of the simultion results of the PID controller tht use the modified current shpes. The inputs of the fuzzy logic controller were speed error, derivtive of speed error, integrl of speed error nd ngulr rotor position. The output vribles re the three phse s reference currents. In the ctul implementtion, this strtegy ws trnslted to tble. The fuzzy logic chrcteristics used in MtLb Simulink simultions re: minimum And Method, mximum Or Method, minimum Impliction, mximum Aggregtion nd centroid Defuzzifiction. The input vrible speed error ( E ) hs three linguistic vlues: negtive, zero nd positive. The corresponding membership functions re: trpezoidl type [ ] for negtive ( N ); tringulr type [ 1 0 1] zero ( Z ); trpezoidl type [ ] for positive ( P ). The input vrible derivtive of speed error ( CE ) hs three linguistic vlues: negtive, zero nd positive. The corresponding membership functions re: tringulr type [ ] for negtive ( N ); tringulr type [ ] for zero ( Z ); trpezoidl type [ ] for positive ( P ). The input vrible integrl of speed error ( IE ) hs three linguistic vlues: negtive, zero nd positive. The corresponding membership functions re: tringulr type [ ] for negtive ( N ); for zero ( Z ); tringulr type [ ] tringulr type [ ] for positive ( P ). The input vrible ngulr rotor position ( Pos ) hs ten linguistic vlues: P1, P2, P3, P4, P5, P6, P7, P8, P9 nd P10, whose corresponding membership functions re shown in Figure 7. The output vribles re the three phse s reference currents. They hve four linguistic vlues: zero ( Z ), low ( L ), medium ( M ) nd high ( H ). The corresponding membership functions for phse current re shown in Figure 8. Tke into ccount the number of membership functions, there re 270 ( ) fuzzy rules. Its structure is similr to: if (E is P ) nd (CE is P ) nd (IE is N ) nd (Pos is P5 ) then (I is M ) (I b is Z ) (I c is H ). Figure 7. Membership functions of input vribles of the fuzzy speed controller. 661

8 E. S. Snches, J. A. Sntistebn Figure 8. Membership functions of output vribles of the fuzzy speed controller. For the neurl PID controller design, the usul procedure of off-line trining ws dopted. This ws bsed in the dt, with smpling frequency of 1 khz, from the simultion results of the PID controller tht use the modified current shpes. The simultion with MtLb Simulink used 12,000 input dt vlues (speed error, derivtive of speed error, integrl of speed error nd ngulr rotor position) distributed s 6000 for trining, 3000 for test nd 3000 for vlidtion. On the other hnd, 12,000 output dt vlues (currents in three phses) were used, obtined with the simultion of the PID conventionl controller. For neurl network trining the MtLb softwre ws used ( nntool ). The neurl network properties were: feed-forwrd bck propgtion network type, network trining function tht updtes weight nd bis vlues ccording to Levenberg-Mrqurdt optimiztion (TRAINLM), grdient descent with momentum weight nd bis dption lerning function (LEARNGDM), men squred error performnce function (MSE), two lyers: lyer 1 using 36 neurons with hyperbolic tngent sigmoid trnsfer function (TANSIG) nd lyer 2 using 3 neurons with liner trnsfer function (PURELIN). Figure 9 shows the neurl rchitecture nd Figure 10 shows the performnce of the neurl network trining used in the simultion. The trining generted weight nd bis vlues of the two lyers tht were used in the neurl PID controller to clculte the references currents of the simultion. In the ctul implementtion, correspondent tble ws prepred. 5. Controllers Implementtion The hrdwre to control the AFSRM consists of controller circuit, three power converter circuits, one for ech phse, position sensor circuit, three Hll Effect current mesurement circuits, lso one for ech phse, torque meter connected between the AFSRM shft nd the mechnicl lod shft. The shft of DC mchine ws used s n inertil lod. These components re rrnged s shown in the block digrm of Figure 11. The experimentl hrdwre is shown in Figure 12, including the AFSRM. In this photo the prts of the hrdwre used in the experiments cn be identified: the controller circuit (1), the power converter circuits (2), the position sensor circuit (3), Hll Effect current mesurement circuits (4), torque sensor nd disply (5), the AFSRM (6) nd the DC mchine (7). The position sensor consists of n infrred opticl circuit nd n luminum dish with 180 holes, fixed to the rotor structure. The signl from the sensor is trnsformed into rectngulr pulse strem with mplitude of 5 V, 662

9 E. S. Snches, J. A. Sntistebn Figure 9. Neurl rchitecture generted by nntool of the MtLb softwre. Figure 10. Neurl network trining of the MtLb softwre. MEASURED CURRENTS REFERENCE SPEED CONTROLLER REFERENCE CURRENTS POWER CONVERTER AFSRM CONTROLLER REAL SPEED Lod DC MACHINE POSITION SENSOR Figure 11. AFSRM drive block digrm. which is sent to the controller circuit. The ctul phse currents re mesured using commercil Hll Effect circuits. Their gin nd zero djustments were done in order to obtin 1 V for 1 A of phse current. The power circuits consist of three symmetric bridge converters nd uxiliry circuits. In Figure 13, one of the power circuits is depicted. As illustrted, the ctul mesured current is compred with the reference current coming from the controller circuit. If the rel current is greter thn the reference, the power circuit switches off the Mosfets of this phse in order to decrese the current in the coils. The controller circuit consists of one microcontroller PIC 18F4680, progrmmed using the C lnguge, tht receives the rectngulr pulses from the position sensor nd clcultes the reference currents of the three phses 663

10 E. S. Snches, J. A. Sntistebn Figure 12. Experimentl hrdwre nd AFSRM prototype. Power Converter Circuit Reference Current Clock +v Controller Circuit Q Isoltor Mesurement Current Circuit Comprtor _ Q Isoltor SRM Phse Coil Actul Current Figure 13. Power converter block digrm for one phse. in ccordnce with the controller type used, sending them to the power converter. Due to the 180 holes in the luminum dish, the controller imposed the reference currents every Experimentl Results In order to evlute the torque ripple minimiztion strtegy, four experiments were performed: current pulses were imposed nd conventionl PID speed controller ws used; proposed current wveforms, shown in Figure 4, were imposed nd conventionl PID speed controller ws used; fuzzy logic PID speed controller ws used; neurl PID speed controller ws used Imposing Current Pulses In this cse the current pulses were pplied in the following sequence: phse from rotor position 0 to 30 ; phse c from rotor position 30 to 60 ; phse b from rotor position 60 to 90. The Figure 14 shows the reference current imposed by the controller nd the ctul current in the coils of one phse. The Figure 15 shows the speed response nd the Figure 16 shows the torque response, when current pulses re imposed nd conventionl PID speed controller is used. The reference speed is 350 rpm. In this cse, the torque ripple in stedy stte ws round 17.1% of the verge torque. 664

11 E. S. Snches, J. A. Sntistebn Figure 14. Reference pulsed current nd rel current. Figure 15. Speed response for current pulses nd PID conventionl speed controller. Figure 16. Torque response for current pulses nd conventionl PID speed controller Imposing Proposed Current Wveforms The current wveform proposed s reference nd the ctul current in phse re shown in Figure 17. Note tht the ctul nd reference currents re prcticlly overlpping. The Figure 18 shows the speed response nd Figure 19 shows the torque response for current wveforms proposed nd conventionl PID speed controller. In this cse, the torque ripple in stedy stte ws round 2.1% of the verge torque. 665

12 E. S. Snches, J. A. Sntistebn Figure 17. Proposed current reference nd ctul current. Figure 18. Speed response for current wveforms proposed nd conventionl PID speed controller. Figure 19. Torque response for current wveforms proposed nd conventionl PID speed controller Using Fuzzy Logic PID Speed Controller The ctul currents in two phses of the AFSRM re shown in Figure 20. These were very close to their references. Figure 21 shows the speed response nd Figure 22 shows the torque response for the fuzzy logic PID controller. In this cse, the torque ripple in stedy stte ws round 6.5% of the verge torque. 666

13 E. S. Snches, J. A. Sntistebn Figure 20. Actul currents of two phses using the fuzzy logic PID controller. Figure 21. Speed response for the fuzzy logic PID controller. Figure 22. Torque response for the fuzzy logic PID controller Using Neurl PID Speed Controller The ctul currents in two phses of the AFSRM re shown in Figure 23. The Figure 24 shows the speed response nd the Figure 25 shows the torque response for neurl controller. In this cse, the torque ripple in stedy stte ws round 2.0% of the verge torque. 7. Conclusions In this work, prticulr reference wveforms for the currents of n ASFRM in closed loop speed control 667

14 E. S. Snches, J. A. Sntistebn Figure 23. Actul currents of two phses using the neurl PID controller. Figure 24. Speed response for neurl PID controller. Figure 25. Torque response for neurl PID controller. system hve been proposed nd experimentlly tested. Compring the performnce of conventionl PID speed controller using current pulses with conventionl PID speed controller, using the current wveforms proposed, it is confirmed tht the level of torque ripple is reduced. All the controllers were djusted through simultions, using motor model tht is composed by self nd mutul inductnces obtined through 3D FEM simultions. Compring the performnce of conventionl PID speed controller using the proposed current wveforms with fuzzy logic PID speed controller, it ws noted tht the torque ripple for the first one is lower, which cn be explined becuse the currents obtined with fuzzy logic controller re not exctly similr to those tht would 668

15 E. S. Snches, J. A. Sntistebn produce constnt torque. Nevertheless, in respect of the speed response, the fuzzy logic PID controller reches the stedy stte in less time thn the conventionl PID controller. Even more, with respect to the implementtion, the execution time of the fuzzy logic PID is lower thn tht used with the conventionl PID controller but similr to tht spent by the neurl PID controller. Finlly, with respect to the neurl PID controller, it notes similr torque ripple to the conventionl PID controller but lower thn tht obtined using the fuzzy logic pproch, which is expected s this ws obtined from trining bsed on the conventionl PID controller results. However, this hs cost, which is the time spent in off-line trining. References [1] Krishnn, R. (2001) Switched Reluctnce Motor Drives: Modeling, Simultion, Anlysis, Design nd Applictions. CRC Press, Boc Rton. [2] Miller, T.J.E. (1993) Switched Reluctnce Motors nd Their Control. Oxford Science, Oxford. [3] Vijykumr, K., Krthikeyn, R., Prmsivm, S., Arumugm, R. nd Srinivs, K.N. (2008) Switched Reluctnce Motor Modeling, Design, Simultion, nd Anlysis: A Comprehensive Review. IEEE Trnsctions on Mgnetics, 44, [4] Hung, S., Luo, J., Leonrdi, F. nd Lipo, T.A. (2000) A Comprison of Power Density for Axil Flux Mchines Bsed on Generl Purpose Sizing Equtions. IEEE Trnsctions on Energy Conversion, 14, [5] Mdhvn, R. nd Fernndes, B.G. (2013) Axil Flux Segmented SRM with Higher Number of Rotor Segments for Electric Vehicles. IEEE Trnsctions on Energy Conversion, 28, [6] Mdhvn, R. nd Fernndes, B.G. (2012) Comprtive Anlysis of Axil Flux SRM Topologies for Electric Vehicle Appliction. IEEE Interntionl Conference on Power Electronics, Drives nd Energy Systems, Bengluru, December 2012, 1-6. [7] Asghr, K. (2013) Anlysis of Switched Reluctnce Motor Drives for Reduced Torque Ripple Using FPGA Bsed Simultion Technique. Americn Journl of Informtion Sciences, 6, [8] Wdnerkr, V.S., Bhskr, M.M., Ds, T.R. nd RjKumr, A.D. (2010) A New Fuzzy Logic Bsed Modeling nd Simultion of Switched Reluctnce Motor. Journl of Electricl Engineering & Technology, 5, [9] Rj, E.F.I. nd Kmrj, V. (2013) Neurl Network Bsed Control for Switched Reluctnce Motor Drive. IEEE Interntionl Conference on Emerging Trends in Computing, Communiction nd Nnotechnology, [10] Pul, P.P., Silv, W.M., Crdoso, J.R. nd Nbet, S.I. (2003) Assessment of the Influences of the Mutul Inductnces on Switched Reluctnce Mchines Performnce. Interntionl Electric Mchine nd Drives Conference, 3, [11] ANSYS Inc. (2005) Low-Frequency Electromgnetics Anlysis Guide: Relese ANSYS Inc., Cnonsburg. [12] Sss, F., Sntistebn, J.A. nd Snches, E. (2009) Design nd Implementtion of Digitl Control System for n Axil Flux Switched Reluctnce Motor. Brzilin Power Electronics Conference, Bonito, 27 September-1 October 2009,

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