Modified Euler integration based control of a five-phase induction motor drive

Transcription

1 MultiCaft Intenational Jounal of Engineeing, Science an echnology Vol., No. 6, 00, pp INERNAIONAL JOURNAL OF ENGINEERING, SCIENCE AND ECHNOLOGY 00 MultiCaft Limite. All ights eseve Moifie Eule integation base contol of a five-phase inuction moto ive M. Rizwan Khan *, Atif Iqbal,, SK. Moin Ahme, Saifullah Payami * Depatment of Electical Engineeing, Aligah Muslim Univesity, Aligah, INDIA Depatment of Electical Engineeing, College of Engineeing, Qata Univesity, Doha, QAAR * Coesponing Autho: izwan.ee@gmail.com, el , Fax Abstact In pinciple, contol methos fo multi-phase machines ae the same as fo thee-phase machines. Vaiable spee inuction moto ives without mechanical spee sensos at the moto shaft have the attactions of low cost an high eliability. o eplace the spee senso, infomation of the oto spee is extacte fom measue stato cuents an voltages at moto teminals. Vecto-contolle ives equie estimating the magnitue an spatial oientation of the funamental magnetic flux in the stato o in the oto. Open-loop estimatos o close-loop obseves ae use fo this pupose. hey iffe with espect to accuacy, obustness, an sensitivity against moel paamete vaiations. his pape analyses opeation of a moifie Eule integationbase sensoless contol of vecto contolle five-phase inuction machine with cuent contol in the stationay efeence fame. A linea neual netwok has been then esigne an taine online by means of back popagation netwok (BPN) algoithm, iffeently fom that in the liteatue which employs a nonlinea back popagation netwok (BPN) algoithm. he Atificial Neual Netwok (ANN)-Moel Refeence Aaptive System (MRAS) base sensoless opeation of a thee-phase inuction machine is well establishe an the same pinciple is extene in this pape fo a five-phase inuction machine. Pefomance, obtainable with hysteesis cuent contol, is illustate fo a numbe of opeating conitions on the basis of simulation esults. Full ecoupling of oto flux contol an toque contol is ealise. Dynamics, achievable with a five-phase vecto contolle inuction machine, ae shown to be essentially ientical to those obtainable with a thee-phase inuction machine. Keywos: Multi-phase machine, MRAS, ANN, BPN, Eule Integation, Sensoless contol.. Intouction Vaiable spee electic ives peominately utilise the thee-phase machines. Howeve, since the vaiable spee ac ives equie a powe electonic convete fo thei supply (in vast majoity of cases an invete with a c link), the numbe of machine phases is essentially unlimite. his has le to an incease in the inteest in multiphase ac ive applications, since multiphase machines offe some inheent avantages ove thei thee-phase countepats. a numbe of inteesting eseach esults has been publishe ove the yeas an etaile eviews ae available in (Singh, 00, Jones et al., 00, oliyat et al., 000, u et al., 00, Pasa, 005). Majo avantages of using a multi-phase machine instea of a thee-phase machine ae etaile in (Singh, 00, Jones et al., 00, oliyat et al., 000, u et al., 00, Pasa, 005) an ae highe toque ensity, geate efficiency, euce toque pulsations, geate fault toleance, an euction in the equie ating pe invete leg (an theefoe simple an moe eliable powe conitioning equipment). Aitionally, noise chaacteistics of the ive impove as well. Sensoless vecto contol of thee-phase inuction machine has attacte wie attention in esent yeas (Pasa et al, 004, eien et al., 004, Holtz, 006, 00). Seveal attempts have been mae in the past to extact the spee signal of the inuction machine fom measue stato cuents an voltages. Initially, the sensoless techniques wee esticte to techniques which ae only vali in the steay-state an can only be use in low cost ive applications, not equiing high ynamic pefomance. Diffeent, moe sophisticate techniques ae equie fo high pefomance applications in vecto contolle ives (Holtz, 00). In a sensoless ive, spee infomation an contol shoul be povie with an accuacy of 0.5% o bette, fom zeo to the highest spee, fo all

2 9 Khan et al./ Intenational Jounal of Engineeing, Science an echnology, Vol., No. 6, 00, pp opeating conitions an inepenent of satuation levels an paamete vaiations. In oe to achieve goo pefomance of sensoless vecto contol, iffeent spee estimation schemes have been popose an a vaiety of spee estimatos exist nowaays. Sensoless opeation of a vecto contolle thee-phase inuction machine ive is extensively iscusse in the liteatue (Vas, 998, Rajashekaa et al, 996), but the same is not tue fo multi-phase inuction machine. Only few application specific sensoless opeation of multi-phase machine is elaboate in the liteatue. he poblem of using the position senso in moeelectic aicaft fuel pump fault toleant ive is highlighte in (Geen et al, 000). he ive utilises a 6 kw, 3000 pm sixphase pemanent magnet moto with six inepenent single-phase invetes supplying each of the six-phases. he authos popose an altenative sensoless ive scheme. he popose technique makes use of flux linkage-cuent-angle moel to estimate the oto position. Although seveal schemes ae available fo sensoless opeation of a vecto contolle ive, but the most popula is the MRAS because of ease of thei implementation (Elbulk et al, 00, Kim et al, 995). An attempt is mae in this pape to exten the MRAS-base technique of a thee-phase machine to an iniect fiel oiente five-phase inuction moto ive. It has been shown in (White, 959) that multi-phase machine moels can be tansfome into a system of ecouple equations in othogonal efeence fames. he -q axis efeence fame cuents contibute towas toque an flux pouction, wheeas the emaining x-y components plus the zeo sequence components o not. his allows a simple extension of the oto flux oiente contol(rfoc) pinciple in that the oto flux linkage is maintaine entiely in the -axis, esulting in the q-axis component of oto flux being maintaine at zeo. his euces the electomagnetic toque equation to the same fom as that of a c machine o a oto flux oiente thee-phase machine. hus the electomagnetic toque an the oto flux can be contolle inepenently, by contolling the an q components of stato cuent inepenently. he ecouple contol of toque an flux using oto flux oiente contol fo a five-phase inuction machine is illustate in (u et al, 00). Ben et al. (993) an Elloumi et al. (998) pesent an MRAS spee obseve which is an evolution of Shaue (99) an minimizes the eo between oto fluxes estimate espectively with a efeence an an aaptive flux moel, an then they apply it to an fiel oiente contol(foc). Like in Shaue (99), it employs, as a efeence moel, the voltage moel of the inuction machine an the open-loop integation is pefome by an LP filte. Howeve, it uses the aaptive moel, by eaanging the oto equations of the machine so that a multilaye pecepton can be employe. On this basis, these aticles exploit the classical back popagation netwok (BPN) algoithm fo the online taining of the neual netwok to estimate the oto spee. In Ben et al. (999) the obseve is veifie also expeimentally, even if neithe the lowest spee limit of the obseve no the zeo-spee opeations, at no loa an at loa, ae pesente. his pape poposes an impovement of the MRAS atificial-neual-netwok (ANN)-base spee obseve pesente in (Ben et al, 999), fo basically two easons. Fist it oes not use the BPN neual netwok but an Aaptive Linea neual Netwok (ADALINE), since the poblem to be solve is linea: it is in fact questionable to use a nonlinea metho like the BPN algoithm which causes local minima, paalysis of the neual netwok, nee of two heuistically chosen paametes, initialization poblems, an convegence poblems. In (Ben et al, 999) this lineaity poblem has been ecognize, but the minimization has been pefome with a gaient-escent epenent also fom the momentum, which is not necessay. Secon, the aaptive moel in (Ben et al, 999) is use in simulation moe, which means that its outputs ae fee back ecusively. In this pape, in contast to this, a moifie aaptive moel is use as a peicto, without feebacks, no nee of filteing the estimate signal, an esulting in highe accuacy both in tansient an steay-state opeation. Moeove, iffeently fom (Ben et al, 999), a stable behavio in fiel weakening is achieve. In this pape the impovements achieve with the MRAS-OLS obseve ae emphasize. he analysis is hee esticte to ANN-MRAS-base sensoless contol of a five-phase inuction machine, with cuent contol in the stationay efeence fame. he oinay least squae (OLS) algoithm fo the online taining of the neual netwok is use to estimate the oto spee. Phase cuents ae contolle using hysteesis cuent contol metho. A simulation stuy is pefome fo spee moe of opeation, fo a numbe of tansients, an the esults ae epote in the pape. A etaile moelling of a five-phase inuction machine an it vecto contol pinciple is epote in (Jones et al, 00, u et al, 00). he evelope moel of a five-phase inuction moto inicates that an ANN-MRAS technique use fo thee-phase machines can be easily extene to multi-phase machines. Fo multi-phase machines ANN-MRAS-base spee estimato equies only an q components of stato voltages an cuents. he moel of a five-phase inuction machine (Jones et al, 00, u et al, 00), it has been shown that the stato an oto an q axis flux linkages ae function of magnetising inuctance Lm an stato an oto an q axis cuents, whee as the x an y axis flux linkages ae function of only thei espective cuents. heefoe in spee estimation fo multi-phase machine the x an y components of voltages an cuents ae not equie. he spee can be estimate using only an q components of stato voltages an cuents. he popose ANN-MRAS-base five-phase vecto contolle inuction moto ive stuctue with cuent contol in the stationay efeence fame is shown in Figue.

3 0 Khan et al./ Intenational Jounal of Engineeing, Science an echnology, Vol., No. 6, 00, pp Phase AC Supply Dioe Bige Rectifie C PWM Invete 5-phase Inuction Moto Hysteesis Cuent Contolle i s = i sn ω ω PI e K i qs j e φ i αs i βs 5 i a i b i c i i e i a i b i c i i e K φ 3. BPN Algoithm base Spee Estimato ω sl /s θ BPN-MRAS base spee contolle vs, v qs i s, i qs Figue. ANN MRAS BPN base five-phase inuction moto ive stuctue. (A) Using Simple Eule Integation Metho A linea neual netwok has been esigne an taine online by means of BPN algoithm. It is clea fom Figue, that the aaptive moel is chaacteize by the feeback of elaye estimate oto flux components to the input of the neual netwok, which means that the aaptive moel employe is in simulation moe. Moeove, the aaptive moel is tune online (taining) by means of a BPN algoithm, which is, howeve, nonlinea in its natue with the consequent awbacks (local minima, heuistics in the choice of the netwok paametes, paalysis, convegence poblems, an so on). In Figue, the aaptive moel employs an ADLINE an the values of the oto flux-linkage components at the input of the ANN come fom the efeence moel, an not fom the aaptive one; this means that the ANN is employe in peiction moe. v s v qs i s i qs Refeence Moel + ε _ v s v qs i s i qs Refeence Moel + ε _ Aaptive Moel(ANN) Aaptive Moel(ANN) ω BPN Algoithm ω BPN Algoithm Figue. Schematic block iagam of Recuent Neual Netwok spee estimato using BPN algoithm in Simulation moe an Peiction moe. Figue an Figue show the block iagams of MRAS-base spee estimation schemes, which contain an ANN. his netwok has fou inputs an two outputs. It follows fom these figues that the inputs to the efeence moel ae the monitoe stato voltages an cuents of the inuction machine. he outputs of the efeence moel ae the oto flux-linkage components in the stationay efeence fame ( = L m, ). hese ae obtaine by consieing the following equations (Vas, 998): q [ ( Vs Rsis ) t Ls ' is ] L () L = L m [ ( V R i ) t L ' i ] () qs s qs s qs hese two equations o not contain the oto spee an escibe the efeence moel. Howeve, when the oto voltage equations of the inuction machine ae expesse in the stationay efeence fame, they contain the oto flux linkages an the oto spee as well. hese ae the equations of the aaptive moel an ae given as: [ ( Lmis ω t] = (3) )

4 Khan et al./ Intenational Jounal of Engineeing, Science an echnology, Vol., No. 6, 00, pp [ ( Lmiqs ω t] = + (4) ) In these equations an ae the oto flux linkages estimate by the aaptive moel. Equations (3) an (4) contain the oto spee, which in geneal is changing, an it is ou pupose to estimate this spee by using an ANN. Fo this pupose, Equations (3) an (4) can be implemente by a two-laye ANN which contains vaiable weights, an the vaiable weights ae popotional to the oto spee Fo given stato voltages an cuents an inuction machine paametes, the actual oto spee ω must be the same as the spee estimate by the ANN ( ω ), when the outputs of the efeence moel an the aaptive moel ae equal. In this case the eos ε = an ε q = ae zeo. When thee is any mismatch between the oto spee estimate by the ANN an the actual oto spee, then these eos ae not zeo, an they ae use to ajust the weights of the ANN (o in othe wos the estimate spee). he weight ajustment is pefome in such a way that the eo shoul convege fast to zeo. o obtain the equie weight ajustments in the ANN, the sample ata foms of equations (3) an (4) ae consiee. Using the backwa iffeence metho, e.g. consieing the ate of change of an estimate oto flux linkage = (5) t s Whee is the sampling time, the sample ata foms of the equations fo the oto flux linkages can be witten as: s ( ) ( ) ( ) k k k ω Lm = + is (6) s s ω Lm = + + iqs (7) s s hus the oto flux linkages at the k th sampling instant can be obtaine fom the pevious (k -) th values as Lms = ( ) ( ) k ws + is (8) Lms = ( ) ( ) + k ws + iqs (9) By intoucing c = s / an assuming that the oto time constant ( ) is constant, the following weights ae intouce: w = c, w = ω s s, w 3 = clm an c = (0) L Whee =, ε = an ε q = () R It can be seen thatω, an ω ae constant weights, but 3 ω is a vaiable weight, an is popotional to the spee. hus equations (8) an (9) take the following foms: = w w + w i ( k ) () 3 s = w w + w3 iqs (3) hese equations can be visualize by the vey simple two-laye ANN shown in Figue,. his contains fou input noes. he input signals to these input noes ae the past values of the estimate oto flux-linkage components expesse in the stationay efeence fame [, ], an also the past values of the stato cuent components expesse in the stationay efeence fame [ i s, i qs ]. hee ae two output noes which output the pesent values of the estimate oto flux-

5 Khan et al./ Intenational Jounal of Engineeing, Science an echnology, Vol., No. 6, 00, pp linkage components [, ]. hus all the noes ae well efine. he connections between the noes ae epesente by weights (synapses), an a weight shows the stength of the connection consiee. In geneal a weight can be positive o negative, coesponing to excitatoy an inhibitoy weights. w w i s ) w 3 i qs ( k w 3 Figue 3. ANN epesentation of estimate oto flux linkages. w w In the ANN shown in Figue 3, the aaptive w weights ae shown with thick soli lines an, as note above, these ae popotional to the spee ( w = ω s )whee the popotionality facto is the sampling time. he aaptive weights ae ajuste so that E = (/ ) ε shoul be a minimum, whee, ε =, ( k ) = [, ] an ( k ) = [, ] hus the weight ajustments to give minimum squae eo have to be popotional to the negative of the gaient of the eo with espect to the weight, E / w since in this way it is possible to move pogessively towas the optimum solution, whee the squae eo is minimal. he popotionality facto is the so-calle leaning ate, η. which is a positive constant an lage leaning ates yiel lage changes in the weights. In pactice as lage a value is chosen fo the leaning ate as possible, since this gives the fastest leaning, but a lage leaning ate can yiel oscillations in the output of the ANN. It follows fom the above that the mathematical expession fo the weight ajustment has to be Δw = η E / w (4) his afte simplification gives the following expession: Δ w ( ) [ ( ) ( ) ( ) k = η ε k k + ε q k ( k )] (5) Whee ε =, an ε q =. Equation (5) is a well known type of expession in neual netwoks using the metho of steepest & gaient fo weight ajustment an it can be seen that the appopiate eos ae multiplie by the appopiate inputs of the neual netwok shown in Figue 3. hus in Figue 3, the weight ajustments can be obtaine fom w = w + Δw (6) It has been iscusse above that fo api leaning, the leaning ate (η) has to be selecte to be lage, but this can lea to oscillations in the outputs of the ANN. Howeve, to ovecome this ifficulty, a so-calle momentum tem is ae to Equation (6). Which takes into account the past [(k-l) th ] weight changes on the pesent [k th ] weight his ensues acceleate convegence of the algoithm. hus the cuent weight ajustment Δ w ( k ) escibe by Equation (6) is supplemente by a faction of the most ecent weight ajustment, Δw : w = w + Δw + α Δw (7) Whee α is a positive constant calle the momentum constant. he tem α. Δw is calle the momentum tem, an is a scale value of the most ecent weight ajustment. Usually, α is in the ange between 0. an 0.8. he inclusion of the momentum tem into the weight ajustment mechanism can significantly incease the convegence, which is extemely useful when the ANN shown in Figue 3, is use to estimate in eal-time the spee of the inuction machine. Since it follows fom equation w = ω, that the weight ω is popotional to the spee, finally the estimate oto spee can be obtaine fom w s ω = (8) s 4. Simulation Results an Discussion he aaptation algoithm escibe above can be implemente in two ways (i) ANN MRAS BPN Moel (aaptive moel in Simulation moe), an (ii) ANN MRAS BPN Moel (aaptive moel in Peiction moe). It is clea fom the Figue,

6 3 Khan et al./ Intenational Jounal of Engineeing, Science an echnology, Vol., No. 6, 00, pp that the aaptive moel is chaacteize by the feeback of elaye estimate oto flux components to the input of the neual netwok, which means that the aaptive moel employe is in simulation moe. Moeove, the aaptive moel is tune online (taining) by means of a BPN algoithm, which is nonlinea in natue. In the secon moe Figue, the values of the oto flux-linkage components at the input of the ANN come fom the efeence moel, an not fom the aaptive one; this means that the ANN is employe in peiction an not in simulation moe Loaing 400 Loaing Spee(.p.m.) Actual Estimate Eo Spee(.p.m.) Actual Estimate Eo ime(secs) ime(secs) Figue 4. Estimate Spee of the ANN-MRAS-BPN scheme aaptive moel in Simulation moe aaptive moel in peiction moe Loaing actual estimate eo Loaing Actual Estimate Eo Spee(.p.m) Spee(.p.m.) ime(secs) ime(secs) Figue 5. Spee esponse with vecto contolle of the ANN-MRAS-BPN scheme aaptive moel in Simulation moe aaptive moel in peiction moe. It is obseve fom the simulation esults (Figues 4 an Figue 5) that much bette esponse is obtaine if it is implemente in the peiction moe the stating ipples which ae the poblem of ANN spee estimato can be eliminate & the tacking capability futhe impoves in the peiction moe. he neual aaptive moel employe in peiction moe, has the avantages that it gives quicke convegence of the spee estimation, highe banwith of the spee loop, lowe estimation eos both in tansient an steay-state opeation, bette behaviou in zeo-spee opeation at no loa, an stable behaviou in fiel weakening. Figue 6. Actual an efeence oto flux fo Simulation moe Peiction moe.

7 4 Khan et al./ Intenational Jounal of Engineeing, Science an echnology, Vol., No. 6, 00, pp Figue 7. he toque, spee an phase a cuent of a vecto contolle five-phase inuction machine: excitation an acceleation tansient fo simulation moe an peiction moe. he ive is opeate in spee moe with spee feeback is taken fom the BPN-MRAS spee estimato. Figue 6 isplays esults fo efeence an actual oto flux in simulation moe an peiction moe. Afte the initial tansient oto flux settles to the efeence value an thee is a change of flux of 0.5Wb in simulation moe an 0.3Wb in peiction moe. It is ue to loss of ecouple contol o paamete vaiation effect o lack of pope tuning. Figue 7 isplays esults fo efeence an actual toque, spee, stato phase a efeence an actual cuent an stato phase a phase-to-neutal voltage fo both moes. It can be seen fom Figue 7 that the flux an toque contol ae fully ecouple. Acceleation takes place with the maximum allowe value of the moto toque. Actual moto phase cuent tacks the efeence vey well. Consequently, toque esponse closely follows toque efeence an a small eviation appeas only at the en of the tansient. No viable conclusion can be awn because of PWM natue of voltages. In simulation moe, the ipples in the toque ae of 4 N-m an spikes in spee ae of 80 pm. hese toque an spee ipples ae vey small in peiction moe. Distubance ejection popeties of the ive ae investigate next. Pevious steay state is the one of Figue 7 (no-loa opeation at 00 pm) an a loa toque equal to the moto ate toque is applie in a step-wise manne at t = s. Responses ae shown in Figue 8, fo simulation moe an peiction moe. Application of the loa toque causes an inevitable ip in spee, of the oe of 0 pm in this peio. Moto toque quickly follows the toque efeence an enables api compensation of the spee ip (in less than 00 ms). he moto toque settles at the value equal to the loa toque afte aoun 00 ms an the moto cuent becomes ate at the en of the tansient. he maximum ipples in the toque an spee uing this peio in simulation moe ae 6 N-m an 3 pm an in peiction moe ae 0.4 N-m an pm. Due to pesence of high ipples in toque an spee, the machine pouces moe noise; moe losses, moe heating an theefoe eating of machine will take place.

8 5 Khan et al./ Intenational Jounal of Engineeing, Science an echnology, Vol., No. 6, 00, pp Figue 8. he toque, spee an phase a cuent of a vecto contolle five-phase inuction machine: istubance ejection behaviou fo simulation moe an peiction moe. Finally, evesing tansient is examine as well. Pevious steay state is the one of Figue 8, (ate loa toque opeation at 00 pm) an the comman fo spee evesal is given at t =. s. Responses, obtaine fo this tansient, ae shown in Figue 9, fo simulation moe an peiction moe. Once moe, actual toque closely follows the efeence, leaing to the spee evesal, with toque in the limit, in the shotest possible time inteval (appoximately 350 ms). Duing this peio, in simulation moe, the ipple in the toque is 4 N-m an a spike in the spee is 00 pm. he toque an spee ipples ae vey small in peiction moe. he spee feeback signal is the estimate one obtaine fom BPN-MRAS-base spee estimato fist fom simulation moe an then fom peiction moe. he attainable pefomances ae examine by simulation in both moes an compae. It is conclue an shown that the pefomance achieve with peiction moe ae bette than simulation moe. (B) Using Moifie Eule Integation Metho his is the impovement of the atificial-neual-netwok (ANN)-base spee estimato MRAS ANN BPN pesente in pevious section. In this moifie scheme the numbe of inputs to the aaptive moel is incease with a consequent quicke convegence of the spee estimation. his moifie ANN MRAS BPN spee estimato uses the cuent moel as an aaptive moel iscetize with the moifie Eule integation metho. A neual netwok has been then esigne an taine online by means of a nonlinea back popagation netwok (BPN) algoithm. Moeove, the neual aaptive moel is employe hee both in simulation an peiction moe. he quick convegence of the spee estimation & lowe estimation eos both in tansient an steay-state opeation is obtaine in the peiction moe.

9 6 Khan et al./ Intenational Jounal of Engineeing, Science an echnology, Vol., No. 6, 00, pp Figue 9. he toque, spee an phase a cuent of a vecto contolle five-phase inuction machine: evesing tansient fo simulation moe an peiction moe. A moe efficient integation metho is use by the so-calle moifie Eule integation, which also takes into consieation the values of the vaiables in two pevious time steps. [ ( Lmis ω t] = ) (9) = [ ( L i m qs ) t] + ω (0) Fom equations (9) & (0) iscete-time equations () can be obtaine, as given below: ( k + ) = ω ω + ω3is + ω4 + ω5 ω6is () ( k + ) = ( ) ( ) ( ) ( ) ω k + ω k + ω3iqs k + ω4 k ω5 ω6iqs whee ω, ω, ω 3, ω 4, ω 5, ω 6 ae the weights of the neual netwoks efine as: ω = 3 /, ω = 3ω /, ω 3 = 3Lm /, ω = 4 /, ω 5 = ω /, ω 6 = Lm /. An the est of the equations ae same as use in the pevious ANN MRAS BPN scheme i.e. ε ε = () = q

10 7 Khan et al./ Intenational Jounal of Engineeing, Science an echnology, Vol., No. 6, 00, pp Δ w = + η ε ( k ) ε q (3) w k) = w + Δw + α Δw ( k ) (4) ( w = s v s + ε v qs Refeence _ i s i qs Moel An the spee is obtaine as ω (5) v s v qs i s i qs Refeence Moel + _ ε Aaptive Moel (ANN) Aaptive Moel (ANN) ω BPN Algoithm ω BPN Algoithm Figue 0. Schematic block iagam of Recuent Neual Netwok spee estimato using moifie Eule BPN algoithm in Simulation moe an Peiction moe Figue 0 shows the block iagam of the coesponing MRAS spee obseve fo simulation an peiction moe. he moifie Eule has eight inputs an two outputs with a consequent quicke convegence of the spee estimation. he simple Eule causes an eo at stating of tansient. his poblem can be avoie eithe by using a simple Eule integation in peiction moe o by using a moifie Eule integation eithe in simulation o in peiction moe. In this last case, howeve, the use of the peiction moe esults in bette accuacy in oto spee estimation an a bette pefomance at zeo spee as shown in the Figue, an Figue. Figue. Spee chaacteistics of RNN spee estimato using moifie Eule BPN algoithm fo fixe voltage an fixe fequency supply fe in simulation moe peiction moe. Figue. Spee chaacteistics of RNN spee estimato using moifie Eule BPN algoithm fo vecto contol in simulation moe peiction moe. As in the pevious BPN scheme (MRAS-ANN-BPN scheme) aaptation algoithm escibe above is implemente in two ways viz aaptive moel in Simulation moe,(ii) aaptive moel in peiction moe.

11 8 Khan et al./ Intenational Jounal of Engineeing, Science an echnology, Vol., No. 6, 00, pp Figue shows the spee esponse of the moifie ANN MRAS BPN scheme with aaptive moel in simulation & peiction moe an Figue shows the Spee esponse in pesence of a vecto contolle of the moifie ANN-MRAS- BPN scheme with aaptive moel in simulation an peiction moe. It is clea fom the simulation esults that much bette esponse is obtaine by inceasing the numbe of inputs to the aoptive moel. Futhemoe the tacking capability futhe impoves. In the simulation moe ipples ae foun fo a peio less than 0. secons. Afte this peio the estimato no ipples ae thee an the estimato closely tacks the actual spee. As shown in Figue, these stating ipples can be completely eliminate in the peiction moe besies the tacking capability which is much bette than with the simulation moe. 5. Conjugate Gaient Algoithm base spee estimato he Conjugate Gaient metho is an effective metho fo symmetic positive efinite systems. It is the olest an best known of the non-stationay methos iscusse hee. he metho pocees by geneating vecto sequences of iteates (i.e., successive appoximations to the solution), esiuals coesponing to the iteation, an seach iections use in upating the iteates an esiuals. Although the length of these sequences can become lage, only a small numbe of vectos nee to be kept in memoy. In each iteation of the metho, two inne poucts ae pefome in oe to compute upate scalas that ae efine to make the sequences satisfy cetain othogonality conitions. On a symmetic positive efinite linea system these conitions imply that the istance to the tue solution is minimize in some nom. he bi-conjugate gaient metho povies a genealization to non-symmetic matices. Vaious nonlinea conjugate gaient methos seek minima of nonlinea equations. It makes the leaning algoithm faste. his metho implies that the momentum factoα is change uing leaning time accoing to the following fomula: g = eα iα + eβ iβ (6) Whee, e = u i an α = g / g (7) Figue 3 shows the spee esponse of the ANN-MRAS-Conjugate Gaient scheme. Small eo is pesent in the tansient peio but the eo is completely omitte in the steay-state egion. he conjugate gaient metho is faste as compae to the BPN scheme, because the leaning ate is moifie uing leaning, thus making the leaning algoithm faste. Figue 3. Spee esponse of the ANN-MRAS-Conjugate Gaient scheme fo fixe voltage an fixe fequency supply with vecto contolle. 6. Conclusion he pape eals with ANN-MRAS- base sensoless vecto contol of a five-phase inuction machine, utilising an iniect machine is at fist eviewe an it is shown that the esulting moel is the same as fo a thee-phase machine oto flux oiente contolle an cuent contol in the stationay efeence fame. Hence the same vecto contol pinciples an spee estimation technique ae applicable fo five-phase machine. Opeation in the spee moe is futhe stuie, utilising the hysteesis cuent contol. he spee feeback signal is the estimate one obtaine fom ANN-MRAS-base spee estimato. he attainable pefomance is examine by simulation. It is shown that the ynamic behaviou, obtainable with the iniect vecto contol, is the same as it woul have been ha a thee-phase machine been use. Roto flux an toque contol ae fully ecouple, enabling the fastest possible acceleations an eceleations with the given toque limit.

12 9 Khan et al./ Intenational Jounal of Engineeing, Science an echnology, Vol., No. 6, 00, pp Nomenclatue V s, V qs - an q-axis stato voltages i s, i qs - an q-axis stato cuents R s ' s, Ls Stato wining esistance L Stato wining self an leakage inuctances L L m Roto wining self inuctance Machine mutual inuctance, - an q-axis oto fluxes - an q-axis estimate oto fluxes, w, w Actual an estimate oto spee Roto time constant Sampling time constant s ε, - an q-axis oto fluxes eo ε q (k) kth instant flux w, w, w3 ANN weights Δ w Weight eo η Leaning ate Refeences Ben-Bahim L. an R. Kuosawa, 993. Ientification of inuction moto spee using neual netwoks. in Poc. PCC 93,Yokohama, Japan, 993, pp Ben-Bahim L., S. aakuma, an A. Akag, 999. Spee contol of inuction moto without otational tansuces. IEEE ans. In. Appl., Vol. 35, No. 4, pp , Jul./Aug. Elbulk M. E., L. ong an I. Husain, 00. Neual Netwok base Moel Refeence Aaptive systems fo high pefomance moto ives an motion contols. IEEE ans. In. Appticat. Vol. 38. May/June. Elloumi M., L. Ben-Bahim, an M. Al-Hamai, 998. Suvey of spee sensoless contols fo IM ives. in Poc. IEEE IECON 98, Vol., 998, pp Geen S., A.G.Atkinson, B.C.Mecow an A.King, 000. Sensoless Opeation of a Fault oleant PM Dives. IEE Poc. Elect. Powe application, 000, Vol.50, No., pp.7-5. Holtz J., 006. Sensoless Contol of Inuction Machines With o Without Signal Injection?. IEEE ansactions on Inustial Electonics, Vol. 53, No., Feb 006. Holtz J., 00. Sensoless contol of inuction motos. Poc. IEEE, vol. 90, no. 8, pp , Aug. Iqbal A., S.N. Vukosavi an E.Levi, 003. Vecto contol of a five-phase inuction moto ive. Poc. 38 th UPEC, hessoloniki, Geece, CD-ROM pape No. EMDII, pp Jones M. an Levi E., 00. A liteatue suvey of state-of-the-at in multiphase ac ives. Poc. 37 th Int. Univesities Powe Eng. Conf. UPEC, Staffo, UK, pp Kim K. H., S. M. Chung, G. W. Moon, I.C. Baik an M.J. Youn, 995. Paamete estimation an contol fo PMSM ive using MRAS. Poc. of st IEEE IECON, Vol., pp , 995. Matlab/Simulink efeence guie Pasa L., 005. On Avantages of Multiphase Machines. IECON 005 Pasa L. an H. oliyat, 004. Sensoless Diect oque Contol of Five-Phase Inteio Pemanent Magnet Moto Dives. IEEE Inusty Applications Confeence, IEEE-IAS 004, Annual Meeting,Oct 3-7. Rajashekaa K., A. Kawamua, an K. Matsuse, 996. Sensoless Contol of AC Motos, Es. Piscataway. NJ: IEEE Pess, 996. Shaue C., 99. Aaptive spee ientification fo vecto contol of inuction motos without otational tansuces. IEEE ans. In. Appl., Vol. 8, No. 5, pp , Sep./Oct. Singh G.K., 00. Multi-phase inuction machine ive eseach a suvey. Electic Powe System Reseach, Vol. 6, 00, pp

13 30 Khan et al./ Intenational Jounal of Engineeing, Science an echnology, Vol., No. 6, 00, pp eien F., S.Siala an P.Noy, 004. Multiphase Inuction Moto Sensoless Contol fo Electic ship Populsion. Poc. PEMD 004. oliyat H.A. an u H., 000. DSP-base iect toque contol (DC) fo five-phase inuction machines. Poc. Int. Powe Elec. Conf. IPEC, okyo, Japan, pp Vas P., 998. Sensoless Vecto an Diect oque Contol. Oxfo Univesity Pess. White D.C., H.H. Wooson, 959. Electomechanical Enegy Convesion. New Yok, John Wiley & Sons. u H., oliyat H.A. an Petesen L.J., 00. Five-phase inuction motos ives with DSP-base contol system. IEEE ans. On Powe Electonics, Vol. 7, No. 4, pp u H., H.A. oliyat an L.J. Petesen, 00. Resilient cuent contol of five-phase inuction moto une asymmetical fault conitions. Poc. IEEE Applie powe Elec. Conf. APEC, Dallas, exas, pp Biogaphical notes D. M. Rizwan Khan eceive his B.Sc. Engineeing, M.ech. (Electical) an Ph.D. egees in 998, 00 an 008 espectively, fom the Aligah Muslim Univesity, Aligah, Inia. He is an Asstt. Pofesso in the Depatment of Electical Engineeing, Aligah Muslim Univesity, Aligah since 00. His pincipal aea of eseach inteest is Powe Electonics, Atificial Intelligence an Multi-phase moto ives. D. Atif Iqbal eceive his B.Sc. an M.Sc. Engineeing (Electical) egees in 99 an 996, espectively, fom the Aligah Muslim Univesity, Aligah, Inia an PhD in 005 fom Livepool John Mooes Univesity, Livepool, UK. He has been employe as Lectue in the Depatment of Electical Engineeing, Aligah Muslim Univesity, Aligah since 99 an is cuently woking as a Reae in the same univesity. He is on acaemic assignment an woking at Qata Univesity, Qata, He is ecipient of Maulana ufail Ahma Gol Meal fo staning fist at B.Sc. Engg. Exams in 99, AMU an eseach fellowship fom EPSRC,UK fo pusuing Ph.D. stuies. His pincipal aea of eseach inteest is Powe Electonics an Multi-phase machine ives. Sk. Moin Ahme was bon in Hooghly, West Bengal, Inia, in 983. He eceive the B.ech an M.ech. egees fom Aligah Muslim Univesity (AMU), Aligah, Inia, in 006 an 008, espectively, whee he is cuently pusuing the Ph.D. egee. He is also pusuing a eseach assignment at exas A&M Univesity at Qata. His pincipal aeas of eseach ae moeling, simulation, an contol of multi-phase powe electonic convetes an fault iagnosis using Atificial intelligence. M. Ahme was a Gol Mealist in eaning the M.ech egee. He is a ecipient of oonto Fellowship, fune by AMU. Saifullah Payami eceive his B.ech (Electical) an M.ech (Powe System & Dives) in 007 an 00, espectively, fom Aligah Muslim Univesity, Aligah, Inia. Cuently he is woking as Junio Reseach Fellow in a CSIR fune poject at Depatment of Electical Engineeing, AMU. His aea of eseach inteest is Powe Electonics, Multi-phase Machine Dives an Renewable Enegy Systems Receive August 00 Accepte Octobe 00 Final acceptance in evise fom Novembe 00