Torque Ripple Reduction in BLDC Motor Using Neural Network Controller

Transcription

1 Toque Ripple Reduction in BLDC Moto Using Neual Netwok Contolle K. Naga Sujatha 1, and K.Vaisakh 2 Associate Pofesso, Dept of EEE, JNTUHCEJ, Kaimnaga Dist. Pofesso, Dept of EE, AU EnggCollege,Visakapatnam. Abstact This pape pesents the design and implementation of neual netwok contolle fo educing toque ipples in bushlessdc (BLDC) moto dive with tapezoidal back-emf. The pefomances of the poposed neual netwokcontolle ae compaed with the coesponding fuzzy PI contolle and conventional PI contolle. Simulation esults ae used to show the abilities and shotcomings of the poposed speed egulation scheme fo bushless dc moto which is consideed as a highly nonlinea dynamic complex system. Matlab/Simulink softwae was used to simulate the poposed model. Keywods Bushless DCMoto Dive BLDC, Fuzzy Logic contolle, Neual Netwok contolle. 1.INTRODUCTION A bushless DC moto is one of a small-scale moto used in small electic devices such as CD playes, had disk dives, o even small electic cas. Its oto is mounted with pemanent magnet. Thee is no need fo exta field excitation. This moto is well-known and popula fo position and speed contol dive applications [1, 2]. The key advantage of this moto ove othe types in the same ating is highe atio of poduced toque pe weight, faste esponse, accuate position contol, lowe moment of inetia, less maintenance, etc [3, 4]. The constuction of moden bushless motos is vey simila to the ac moto, known as the pemanent magnet synchonous moto. The stato windings ae simila to those in a poly phase ac moto, and the oto is composed of one o moe pemanent magnets. Bushless dc motos ae diffeent fom ac synchonous motos in that the fome incopoates some means to detect the oto position (o magnetic poles) to poduce signals to contol the electonic switches as shown in Fig.1. The most common position/pole senso is the Hall element, but some motos use optical sensos. Fig.1 Bushless DC Moto Dive In vaiable speed opeations of BLDC moto, the PI contol is still the most used contol. This is because of its simplicity and ease of design. Howeve, it has disadvantages that the pefomance depends to popotional and integal gains. Theefoe, when the opeating condition changes such as distubances, load changes and moto's paametes vaiations, the etuning pocess of contol gains in necessay. Contolles using atificial intelligent tools, such as fuzzy logic and neual netwok can be applied to ovecome foegoing poblems. Diffeent intelligent contolles such as Fuzzy logic contolles (FLC) and neual netwok contolles have been exploed. They may contol the speed diectly o as indiectly adjust the gains of PI contolle. This pape pesents an implementation of neualnetwok contolle fo impoving the tansient esponses to toque distubance and speed efeence following of the BLDC moto dive. Simulation esults ae used to show the abilities and shotcomings of the poposed method as compaed with the conventional PI and fuzzy contolles. 2.BLDC MODELING A. Mathematical Model of BLDC Motos Modeling of a BLDC moto can be developed in the simila manne as a thee-phase synchonous machine [1,2]. Since its oto is mounted with a pemanent magnet, some dynamic chaacteistics ae diffeent. Flux linkage fom the oto is dependent upon the magnet. Theefoe, satuation of magnetic flux linkage is typical fo this kind of motos. As any typical thee- Page 18

2 phase motos, one stuctue of the BLDC moto is fed by a thee-phase voltage souce. The souce is not necessay to be sinusoidal. Squae wave o othe wave shape can be applied as long as the peak voltage is not exceeded the maximum voltage limit of the moto. Similaly the typical mathematical model of a theephase is descibed The voltage equation of the BLDC moto can be witten as: v R 0 0 L L L i e a a a ab ac a a v 0 R 0 p L L L i e b b ba b bc b b v 0 0 R L L L i e c c ca cb c c c (1) Ra Rb Rc R amatue esistance cuent contol and geneates the switching signals fo Invete. In Invete block, phase voltages ae obtained. The invete topology is six-switch voltagesouce configuation with constant DC-Link voltage (VMA). The PWM thee-phase invete opeation can be divided into six modes accoding to the cuent conduction states. The thee phase cuents ae contolled to take a fom of quasi-squae wavefom in ode to synchonize with the tapezoidal back-emf to poduce the constant toque. In each time only two phases ae excited, so it is possible to use only one cuent senso which is placed in DC-link voltage. va, vb, vc ia, ib, ic teminal phase voltage[v] moto input cuent[a] ea, eb, e c :moto back emf [V] The electic powe can be shown as P e i e i e i (2) e a a b b c c The electomagnetic toque of the moto can be expessed as T P ( e i e i e i ) / (3) e m a a b b c c and the motion equation can be witten as p ( T T ) / j (4) e l m whee L a,l b, L cae the self-inductance of thee phases windings, L ab,l ba,l bc,l cb,l ca,lac ae the mutual inductance by diffeent windings, e a,e b, e cdenote the inducedelecto-motive foces, P nis the numbe of pais of BLDC moto, ω denote the angula velocity, T lis the load toque, J m is the otational inetia The oveall system configuation of the 3-phase BLDC moto dives is shown in Figue 2.It compises of six functional blocks Speed contolle block geneates the cuent demand to maintain the speed at efeence value. Back-EMF voltage block calculates the phase back-emf voltages accoding to oto position. Phase cuent block calculates the phase cuent. Cuent contol block contols the phase cuent via hysteesis Fig.2 BLDC Moto Dive with Speed Contolle 3.SPEED REGULATION SCHEMES Human abilities in contolling the complex systems, has encouaged scientists to patten fom human neual netwok and decision making systems. Fistly the eseaches began in two sepaate fields and esulted in establishment of the fuzzy systems and atificial neual netwoks. Thee ae pimaily thee concepts pevailing ove the intelligent contol: Fuzzy Logic Contol Neual Netwok based Contol A) Fuzzy Logic Contolle In the fist concept, the contolle is epesented as a set of ules, which accepts/gives the inputs/outputs in the fom of linguistic vaiables. The main advantages of such a contolle ae: (1) Appoximate knowledge of plant is equied (2) Knowledge epesentation and infeence is simple. (3) Implementation is faily easy. Page 19

3 defuzzification. The knowledge base is composed of adata base and a ule base. The data base, consisting of input and output membeship functions, povides infomation fo the appopiate opeation of fuzzification, infeence mechanism, and defuzzification The ule base is made up of a set of linguistic ules elating the fuzzy input vaiables to the desied fuzzy contol actions. Fuzzification convets acisp input signal into fuzzified signals that can be identified by its level of membeship into the fuzzy sets. e NB NS ZE PS PB e o/p NB NB NB NS NS ZE NS NB NS NS ZE PS ZE NS NS ZE PS PS PS NS ZE PS PS PB PB ZE PS PS PB PB Table I: Linguistic Rule Table Figue 3 shows the geneal model of a fuzzy system, withtoque ( T e ) as output of the contolle. The two input vaiables e (k) (speed eo) and ce (k) (change in eo) ae calculated at evey sampling instant as e (k) = k) (k) ; ( ce (k) = e (k )- e ( k-1 ) ; (6) whee (k) is the efeence speed and actual oto speed. (5) (k) is the The functional diagam of the fuzzy logic contolle includes fou majo blocks: knowledge base, fuzzification, infeence mechanism, and In this pape, the fuzzy sets Z, S, M, L, P, N, PS, PM, PL, NS, NM and NL ae defined ove the domain of input vaiables (eo and eo change) and output vaiable ( T e ).The opeation of fuzzy logic is based on the contol ules in Table 1. The output of FLC should be a cisp value. The defuzzification pocess is used to detemine a cisp value accoding to the fuzzy output fom infeence mechanism. The cente-of aea method is used as a defuzzification stategy in this pape. B) Poposed Neual Netwok Contolle In this second concept, the contolle is epesented as a nonlinea map between the inputs and outputs. Depending on a specific plant, the map (in the fom of a netwok) can be tained to implement any kind of contol stategy. A neuo-contolle (neual netwoks based contol system) pefoms a specific fom of the adaptive contol with the contolle taking the fom of a multi laye netwok and the adaptable paametes being defined as the adjustable weights. The main advantages ae: (1) Paallel achitectue (2) Any kind of nonlinea mapping is possible Page 20

4 (3) Taining is possible fo vaious opeating conditions, so it can be adapted to any desied situation. The simple fuzzy contolle epesents a good nonlinea contolle; howeve, it cannot adapt its stuctue wheneve the situation demands. Sometimes the fuzzy contolles with fix stuctues fail to stabilize the plant unde wide vaiations in the opeating conditions. These types of contolles also lack the paallelism of neual contolles. On the othe hand the neual netwoks ae vey much adaptive to situations by adjusting thei weightsaccodingly. The paallel achitectue enables faste implementation of the contol algoithm. Howeve in the pesence of noise and othe uncetainties the pefomance may deteioate. Some times in cetain neual contolle stuctues the model of the plant is equied. Figue 4 shows the stuctue of the poposed neual netwok contolle. The impoved BP netwok contains the input laye, the hidden laye, the output laye, and the connected weight between the input node and the hidden node is wij, the weight between the hidden node and the output node is Tli, θ denotes the theshold. x j isthe input laye neual node, yiis the hidden laye neual node, Olis the output of the neual netwok, the desied output of output node is tl. all these simulations the initial conditions ae zeo. In BLDC using fuzzy logic, speed eo and change of speed eoae taken as inputs and toque as the output. As descibed ealie, membeship functions wee chosen and ules wee fomed.figue 5show the compaison of speed esponses between conventional PI and FLC and Figue6 shows the compaison of speed esponses between FLC and poposed neual netwok contolle. Figue 7 shows the compaison of speed esponses between conventional PI, FLC and poposed neual netwok contolle. Fom this esult, it is obseved that, withpoposed neual netwok contolle, speed easily attains steady state value at the ealie stage itself when compaed to othe contolles. The simulation esults shows that speed and toque esponses ae vey good dynamic esponses fo poposed neual netwok contolle. Figue 8shows the toque ipple eduction and is compaed with the conventional PI and FLC. Fom this esult, it is obseved that, the toque esponse in the conventional PI contolle pesented with the high ipples, wheeas in the FLC the ipple content is educed to some extent. Bythe poposed neual netwok contolle, thee ae futhe educed ipples in toque esponse. Fig 5.Speed esponses of PI and FLC Figue 4Poposed Neual Netwok Contolle 4. SIMULATION RESULTS To veify the technique poposed in this pape, simulations based on Matlab / Simulink have been implemented. The Typical simulation esults fo the conventional PI contolle, Fuzzy PI contolle and poposed neual netwok contolle ae shown in Figue 5 to8 fo the toque and speed esponses. Fo Fig 6.Speed esponses of FLC and Neual netwok Contolle Page 21

5 Electonics, COMPEL The 7 th Wokshop on, pp , July [2] Lei Hao and Hamid A. Toliyat, BLDC Moto Full Speed Range Opeation Including the Flux Weakening Region, Industy Applications Confeence, th IAS Annual Meeting.Confeence Recod of the, vol. 1, pp , Octobe [3]48531 EMS Chapte 12. Bushless DC Motos Fig 7.Speed esponses of PI, FLC and Neual netwok Contolle [4]S. M.M.Mitalaei, J.S.Moghani, K.Malekian, B.Ab A Novel Sensoless Contol Stategy fo BLDC Moto Dives Using a Fuzzy Logic-based Neual Netwok Obseve. di /08/$ IEEE [5]. Depenbock, Diect self-contol (DSC) of invete-fed induction machine, IEEE Tans. PoweElecton., vol.3, pp , Oct [6]D. Casadie, G.Sea and A.Tani (2000) Implementation Of ADiect Toque Contol Algoithm fo Induction Motos Based On Discete Space Vecto Modulation, Powe Electonics IEEE Tansaction On Powe Electonics, Vol 15No 4. Fig 8.Toque Responses of PI, FLC and Neual netwok Contolle 5. CONCLUSIONS In this pape, the neual netwoks based contolle has been poposed and esults have been compaed with the conventional PI and fuzzy PI contolles. Among all these contolles, the neual netwok shows bette esponse. By using this contolle, its output is updating in the PI contolle gains based on a set of ules to maintain excellent contol pefomance even in the pesence of paamete vaiation and dive nonlineaity. This simple scheme has significantly impoved the pefomance of the BLDC system while at the same time maintaining the simple contol stuctue of the BLDC. Refeences [1] Y. S. Jeon, H. S. Mok, G. H. Choe, D. K. Kim, and J. S. Ryu, A New Simulation Model of BLDC Moto With Real Back EMF Wavefom,Computes in Powe [7]Isao Takashi, Toshishiko Noguchi (1997. Take a look back upon the past decade of diect toque contol.iecon 97 [8]C.G.Mei, S.K. Panda, J.X.Xu And K.W.Lim.(1999).Diect Toque Contol of induction Moto-Vaiable switching sectos. Poc.IEEE PEDS. [9] BOSE, B. K. : Powe Electonics and Vaiable Fequency Dives, IEEE Pess, New Yok, [10] YONG, L. ZHUB, Z. Q. HOWE, D. : Diect Toque Contol of Bushless DC Dives with ReducedToque Ripple, IEEE Tans. on Industy Applications 41 No. 2 (2005), [11] ASTROM, K. J. WITTENMARK, B. : Adaptive Contol, 2 nd Edition, Peason Education, [12] B. K. Lee, B. Fahimi, M. Ehsani; "Dynamic Modeling of Bushless DC Moto ives", Euopean Confeence on Powe Electonics and Applications (EPE'2001), Austia. Page 22

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