A NEURO FUZZY CONTROLLER FOR INDUCTION MACHINES DRIVES

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1 Jounal of Thotcal and Appld Infomaton Tchnology JATIT & LLS. All ghts svd. A NEURO FUZZY CONTROLLER FOR INDUCTION MACHINES DRIVES 1 SRINIVASA RAO JALLURI, 2 D.B.V. SANKER RAM 1 Asstt Pof., Dpatmnt of Elctcal and Elctoncs Engnng, VBCE, Hydabad, Inda Pofsso., Dpatmnt of Elctcal and Elctoncs Engnng, JNTU, Hydabad, Inda ABSTRACT Wth th advnt of cnt pow smconducto tchnologs and vaous ntllgnt contol algothms, an ffctv contol mthod basd on vcto contol tchnology can b fully mplmntd n al-tm applcaton. DC moto dvs bng th most wdly usd tchnqu s slowly bng placd by vctocontol basd hgh-pfomanc IM dvs. Ov th last two dca sachs hav bn wokng to apply AIC fo nducton moto dvs n od to contbut to ths novl dvlopmnt w psnt a nuo fuzzy contoll (NFC) fo th IM moto dv, whch has th advantags of both FLC and ANN, s psntd n ths pap. Kywo: Nfc, Im Dvs, Inducton Moto (Im), Low/Zo-Spd Opaton, Snsolss Contol. 1. INTRODUCTION Inducton motos (IM s) hav bn usd as th wokhos n ndusty fo a long tm du to th asy buld, hgh obustnss, and gnally satsfactoy ffcncy [1]. Th vcto contol tchnqu, whch s dvlopd upon th fld ontaton pncpl poposd by Haas n 1968 and Blaschk n 1970, dcoupls th flux and toqu contol n an IM [2]. Thus, t maks th contol task of IM dvs smla to a spaatly xctd dc moto whl mantanng th gnal advantags of ac ov dc motos and, hnc, sutabl fo hgh-pfomanc vaabl-spd dv applcatons. Wth th advnt of cnt pow smconducto tchnologs and vaous ntllgnt contol algothms, an ffctv contol mthod basd on vcto contol tchnology can b fully mplmntd n al-tm applcaton. Bcaus of ths faclts, nowadays, vcto-contolbasd hghpfomanc IM dvs hav occupd most of th postons that w pvously statond by dc moto dvs [2]. Among vaous ac motos, nducton moto (IM) occups almost 90% of th ndustal dvs du to ts smpl and obust constucton; howv, th contol of IM s complx du to ts nonlna natu and th paamts chang wth opatng condtons. Atfcal ntllgnt contoll (AIC) could b th bst canddat fo IM contol. Ov th last two dca sachs hav bn wokng to apply AIC fo nducton moto dvs [3-8]. Ths s bcaus that AIC posssss advantags as compad to th convntonal PI, PID and th adaptv vsons. Th man advantags a that th gns of ths contolls do not dpnd on accuat systm mathmatcal modl and th pfomancs a obust. In ths pap a nuofuzzy contoll (NFC), as an AIC, s consdd bcaus of lmtatons of th fuzzy logc o nual ntwok [8]. A smpl fuzzy contoll mplmntd n th moto dv spd contol has a naow spd opaton and n much mo manual adjustng by tal and o f hgh pfomanc s wantd [3]. On th oth hand, t s xtmly tough to cat a sal of tanng data fo ANN that can handl all th opatng mo [6]. Nuo-fuzzy contolls (NFCs), whch ovcom advantags of fuzzy logc contolls and nual ntwok contolls, hav bn utlzd by authos and oth sachs fo 102

2 Jounal of Thotcal and Appld Infomaton Tchnology JATIT & LLS. All ghts svd. moto dv applcatons [5-9]. Dspt many advantags of NFCs, th ndusty has bn stll luctant to apply ths contolls fo commcal dvs du to hgh computatonal budn causd by lag numb of mmbshp functons, wghts and uls, spcally on slftunng condton. Hgh computaton budn la to low samplng fquncy, whch s not suffcnt fo mplmntaton. In [7] th authos found latvly hgh toqu ppl causd by low sampl at n a ct dct toqu contol basd on a nuo-fuzzy stuctu. In [5] only wghts w tund to low th computatonal budn, but th cost s pfomanc dcasng. In cnt yas, scntsts and sachs hav acqud sgnfcant dvlopmnt on vaous sots of contol thos and mtho. Among ths contol tchnologs, ntllgnt contol mtho, whch a gnally gadd as th agggaton of fuzzy logc contol, nual ntwok contol, gntc algothm, and xpt systm, hav xhbtd patcula supots. Th fuzzy logc contoll (FLC) mthod can b utlzd n systms that hav vagunss o unctanty. Mmbshp functons wth valus btwn 0 and 1 a usd n FLC to dal wth th contol puzzl, such as nonlnaty, load tubanc, and paamt tubanc. Th atfcal nual ntwok (ANN) s a computaton and nfomaton pocssng mthod that mmcs th pocss found n bologcal nuons. Th basc lmnt of a nual ntwok s th pcpton, whch s also calld th nuon. Th latonshp btwn two pcptons s dfnd as th wght, whch can b tund o tand offln, onln, o combnaton of both. Howv, th fuzzy logc contol o ANN has ts own dawbacks, whch cannot b avodd and nglctd. A smpl fuzzy contoll mplmntd n th moto dv spd contol has a naow spd opaton and n much manual adjustng by tal and o f hgh pfomanc s wantd. On th oth hand, t s xtmly tough to cat a sal of tanng data fo ANN that can handl all th opatng mo.a nuo-fuzzy contoll (NFC) fo th IM moto dv, whch has th advantags of both FLC and ANN, s psntd n ths pap. Ov th last dcad, th authos and oth sachs potd woks on th applcaton of NFC fo vaabl spd dvs. Howv, th convntonal NFCs utlzd n al woks hav a lag numb of mmbshp functons and uls. Ths caus hgh computatonal budn fo th convntonal NFC, whch s th majo lmtaton fo pactcal ndustal applcatons. In od to ovcom th hgh computatonal budn, a novl NFC schm fo th IM dv s poposd n ths pap. In ths contoll, only th mmbshp functons a usd fo ach nput, and th output dos not hav any mmbshp functon fo low computatonal budn, whch wll b sutabl fo al-tm mplmntaton. Futhmo, fo th poposd NFC, an mpovd slf-tunng mthod s dvlopd basd on th knowldg of ntllgnt algothms and moto contol qumnts. Th man task of th tunng mthod s to adjust th paamts of th FLC n od to mnmz th squa of th o btwn actual and fnc sp. In od to duc th computatonal budn and mnmz th squa of th o btwn d and actual outputs, only th output lay s paamts a tund onln basd on th back popagaton algothm. Mnmum tal and o s ndd n gnng th poposd NFC as on has to slct only fw mmbshp functons fo th nputs. Ths pap psnts a novl spd contol schm of th IM dv basd on a nwly dvlopd FC. A complt smulaton modl fo th ndct fld-ontd contol of IM ncopoatng th poposd slf-tund NFC s dvlopd n Matlab/Smulnk. Th pfomanc of th poposd slf-tund NFC-basd IM dv s nvstgatd at dffnt opatng condtons both n smulaton and n xpmnt. In od to pov th supoty of th poposd NFC, th pfomancs of th poposd contoll a also compad to thos obtand by a convntonal popotonal ntgal (PI) and FLC contoll. Th poposd NFC-basd IM dv s found to b mo obust as compad to th convntonal PI and FLC contolls. 103

3 Jounal of Thotcal and Appld Infomaton Tchnology JATIT & LLS. All ghts svd FUZZY LOGIC In ths contxt, FL s a poblm-solvng contol systm mthodology that ln tslf to mplmntaton n systms angng fom smpl, small, mbddd mco-contolls to lag, ntwokd, mult-channl PC o wokstatonbasd data acquston and contol systms. It can b mplmntd n hadwa, softwa, o a combnaton of both. FL pov a smpl way to av at a dfnt concluson basd upon vagu, ambguous, mpcs, nosy, o mssng nput nfomaton. FL's appoach to contol poblms mmcs how a pson would mak dcsons, only much fast. FL qus som numcal paamts n od to opat such as what s consdd sgnfcant o and sgnfcant at-of-changof-o, but xact valus of ths numbs a usually not ctcal unlss vy sponsv pfomanc s qud n whch cas mpcal tunng would dtmn thm. Fo xampl, a smpl tmpatu contol systm could us a sngl tmpatu fdback snso whos data s subtactd fom th command sgnal to comput "o" and thn tm-dffntatd to yld th o slop o at-of-chang-of-o, haft calld "o-dot". Eo mght hav unts of dgs F and a small o consdd to b 2F whl a lag o s 5F. Th "o-dot" mght thn hav unts of dgs/mn wth a small o-dot bng 5F/mn and a lag on bng 15F/mn. Ths valus don't hav to b symmtcal and can b "twakd" onc th systm s opatng n od to optmz pfomanc. Gnally, FL s so fogvng that th systm wll pobably wok th fst tm wthout any twakng. 3. ARTIFICIAL NEURAL NETOWRK Atfcal nual ntwoks mgd aft th ntoducton of smplfd nuons by McCulloch and Ptts n 1943 (McCulloch & Ptts, 1943). Ths nuons w psntd as modls of bologcal nuons and as concptual componnts fo ccuts that could pfom computatonal tasks. Th basc modl of th nuon s foundd upon th functonalty of a bologcal nuon. "Nuons a th basc sgnalng unts of th nvous systm" and "ach nuon s a ct cll whos sval pocsss as fom ts cll body". Fg 1. Stuctu of Nuon Th nuon has fou man gons to ts stuctu. Th cll body, o soma, has two offshoots fom t, th dndts, and th axon, whch nd n psynaptc tmnals. Th cll body s th hat of th cll, contanng th nuclus and mantanng potn synthss. A nuon may hav many dndts, whch banch out n a tlk stuctu, and cv sgnals fom oth nuons. A nuon usually only has on axon whch gows out fom a pat of th cll body calld th axon hllock. Th axon conducts lctc sgnals gnatd at th axon hllock down ts lngth. Ths lctc sgnals a calld acton potntals. Th oth nd of th axon may splt nto sval banchs, whch nd n a psynaptc tmnal. Acton potntals a th lctc sgnals that nuons us to convy nfomaton to th ban. All ths sgnals a dntcal. Thfo, th ban dtmns what typ of nfomaton s bng cvd basd on th path that th sgnal took. Th ban analyzs th pattns of sgnals bng snt and fom that nfomaton t can ntpt th typ of nfomaton bng cvd. Myln s th fatty tssu that suoun and nsulats th axon. Oftn shot axons do not nd ths nsulaton. Th a unnsulatd pats of th axon. Ths aas a calld No of Ranv. At ths no, th sgnal tavlng down th axon s gnatd. Ths nsus that th sgnal tavlng down th axon tavls fast and mans constant (.. vy shot popagaton dlay and no 104

4 Jounal of Thotcal and Appld Infomaton Tchnology JATIT & LLS. All ghts svd. waknng of th sgnal). Th synaps s th aa of contact btwn two nuons. Th nuons do not actually physcally touch. Thy a spaatd by th synaptc clft, and lctc sgnals a snt though chmcal 13 ntacton. Th nuon sndng th sgnal s calld th psynaptc cll and th nuon cvng th sgnal s calld th postsynaptc cll. Th sgnals a gnatd by th mmban potntal, whch s basd on th dffncs n concntaton of sodum and potassum ons nsd and outsd th cll mmban. Nuons can b classfd by th numb of pocsss (o appndags), o by th functon. If thy a classfd by th numb of pocsss, thy fall nto th catgos. Unpola nuons hav a sngl pocss (dndts and axon a locatd on th sam stm), and a most common n nvtbats. In bpola nuons, th dndt and axon a th nuon's two spaat pocsss. Bpola nuons hav a subclass calld psudo-bpola nuons, whch a usd to snd snsoy nfomaton to th spnal cod. Fnally, multpola nuons a most common n mammals. Exampls of ths nuons a spnal moto nuons, pyamdal clls and Puknj clls (n th cbllum). If classfd by functon, nuons agan fall nto th spaat catgos. Th fst goup s snsoy, o affnt, nuons, whch povd nfomaton fo pcpton and moto coodnaton. Th scond goup pov nfomaton (o nstuctons) to muscls and glan and s thfo calld moto nuons. Th last goup, ntnuonal, contans all oth nuons and has two subclasss. On goup calld lay o pojcton ntnuons hav long axons and connct dffnt pats of th ban. Th oth goup calld local ntnuons a only usd n local ccuts. 4. MATHEMATICAL MODELING Whn catng a functonal modl of th bologcal nuon, th a th basc componnts of mpotanc. Fst, th synapss of th nuon a modld as wghts. Th stngth of th conncton btwn an nput and a nuon s notd by th valu of th wght. Ngatv wght valus flct nhbtoy connctons, whl postv valus gnat xctatoy connctons [Haykn]. Th nxt two componnts modl th actual actvty wthn th nuon cll. An add sums up all th nputs modfd by th spctv wghts. Ths actvty s fd to as lna combnaton. Fnally, an actvaton functon contols th ampltud of th output of th nuon. An accptabl ang of output s usually btwn 0 and 1, o -1 and 1. Mathmatcally, ths pocss s cbd n fgu blow, Fg 2. Block dagam of Mathmatcal modlng 5. DYNAMICS AND CONTROL STRUCTURE Equatons (1) (4), whch a shown at th bottom of th pag, dnot th mathmatcal modl n a synchonously otatng fnc fam fo a th-phas squl-cag IM, wh V and v qs a th d q-axs stato voltags, spctvly;, qs, d, and q a th d q-axs stato cunts and d qaxs oto cunts, spctvly; Rs and R a th stato and oto sstancs p phas, spctvly; Ls, L, and Lm a th slf nductancs of th stato and oto, and th mutual nductanc, spctvly; P s th numb of pols; p s th dffntaton opato (d/dt); ω and ω a th spd of th otatng magntc fld and th oto spd, spctvly; T and TL a th lctomagntc dvlopd toqu and th load toqu, spctvly; Jm s th oto nta; Bm s th oto dampng coffcnt; and θ s th oto 105

5 Jounal of Thotcal and Appld Infomaton Tchnology JATIT & LLS. All ghts svd. poston. Th paamts of th two dffnt moto modls that hav bn utlzd n smulatons a gvn n th Appndx. v qs R v = 0 pl 0 s + pls ωls plm ωlm ωls Rs + pl3 ωlm plm m ( ω ω ) Lm R + pl ( ω ω ) ( ω ω ) L pl ( ω ω ) L R + pl dω dt T = Jm + Bmω + 3 P T = L 2 2 m m T L ( ) m qs d d θ dt q (1) (2) (3) = ω (4) L Th two axs stato voltags and cunts a latd to th th-phas psntatons by X X qs snωt = cosω t qs q d cosω t snω 1 1 t (5) T R ω sl qs = L (6) L m qs = q (7) L 3 2 P L = m λdq 2 L.. (8) wh sl s th slp spd and d s th d-axs oto flux lnkag. Equatons (1)-(8) a usd to smulat th whol dv systm. Th schmatc dagam of th poposd NFC-basd ndct fld ontd contol of nducton moto s shown n Fg.1. Th basc confguaton of th dv systm conssts of an nducton moto fd by a cunt contolld voltag souc nvt. Th nomalzd spd o pcntag s pocssd by th nuo-fuzzy contoll to gnat th fnc toqu T* (n). Th command cunt. q(n) s calculatd fom quaton (8) as followng: * * 2 2 L 1 q ( n) T ( n) * 3 P Lm λd = (9) wh x may psnt th cunt o voltag. 6. CONTROL STRUCTURE Th ky fatu of th fld-ontd contol s to kp th magntzng cunt at a constant atd valu by sttng d = 0. So, th toqupoducng cunt componnt can b adjustd accodng to th toqu dmand. Wth ths assumpton, th mathmatcal fomulatons can b wttn as 7. DESIGN OF NEURO-FUZZY CONTROLLER Th poposd NFC ncopoats fuzzy logc and a lanng algothm wth a fou-lay atfcal nual ntwok (ANN) stuctu as dpctd n Fgu blow. Th lanng algothm modfs th NFC to closly match th d systm pfomanc. 106

6 Jounal of Thotcal and Appld Infomaton Tchnology JATIT & LLS. All ghts svd. Fg 3. Stuctu of No Fuzzy Contoll 8. RESULT OBSERVATION Fg 6. A smulatd spd spons of th dv wth FLC fo a snusod spd fnc th actual spd s ndcatd by gn ln and contol spd s dpctd by blu ln. 9. CONCLUSION Fg 4. Smulatd spd sponss of th dv wth NFC fo a snusod spd fnc. Th pfomanc of th poposd NFC-basd IM dv has bn xtnsvly nvstgatd both n smulatons and xpmntally at dffnt dynamc opatng condtons It s found that th NFC basd IM dv has a small sttlng tm wthout any ovshoot/unhoot and stadystat o. Th tunng mthod has bn dvlopd basd on th backpopagaton algothm. Th pfomanc of th poposd NFC-basd IM dv has bn nvstgatd both n smulaton and xpmntally at vaous opatng condtons. A pfomanc compason of th poposd NFC wth convntonal PI and FLC contolls has also bn povdd. Th sults show that th poposd NFC-basd IM dv s supo to convntonal PI and FLC contolls. Fg 5. Smulatd spd sponss wth doubld magntzng nductanc showng spd wth spct to tm and stablty of th spd. REFERENCES: [1] P. L. Cochan, Polyphas Inducton Motos: Analyss, Dsgn, and Applcatons. Nw Yok: Macl Dkk, [2] A. M. Tzynadlowsk, Th Fld Ontaton Pncpl n Contol of Inducton Motos. Nowll, MA: Kluw, [3] M. N. Uddn, T. S. Radwan and M. A. Rahman, Pfomancs of Fuzzy-Logc- Basd Indct Vcto Contol fo Inducton Moto Dv, IEEE Tans. Ind. 107

Jounal of Thotcal and Appld Infomaton Tchnology 2005-2010 JATIT & LLS. All ghts svd. www.jatt.og Applcatons, Sp/Oct, 2002, pp. 1219-1225 [4] T. Chn, T. T. Shu, Modl fnc nual ntwok contoll fo nducton moto spd contol, IEEE Tansactons on Engy Convson, Jun, 2002, pp.

Blaabjg, Dct toqu nuo-fuzzy contol of nducton moto dv, DSP mplmntaton, IEEE IECON Pocdngs, 1998, pp. 657-662. [7] M. N. Uddn, M. A.

7 Jounal of Thotcal and Appld Infomaton Tchnology JATIT & LLS. All ghts svd. Applcatons, Sp/Oct, 2002, pp [4] T. Chn, T. T. Shu, Modl fnc nual ntwok contoll fo nducton moto spd contol, IEEE Tansactons on Engy Convson, Jun, 2002, pp [5] M. N. Uddn, H. Wn, Dvlopmnt of a slf-tund nuo-fuzzy contoll fo nducton moto dvs, Confnc Rcod of th 2004 IEEE IAS Ann. Mtng, pp [6] P. Gabowsk, F. Blaabjg, Dct toqu nuo-fuzzy contol of nducton moto dv, DSP mplmntaton, IEEE IECON Pocdngs, 1998, pp [7] M. N. Uddn, M. A. Abdo and M. A. Rahman, Dvlopmnt and Implmntaton of a Hybd Intllgnt Contoll fo Into Pmannt Magnt Synchonous Moto Dv IEEE Tansactons on Industy Applcatons fo publcaton, Jan./Fb. 2004, pp [8] G. Buja, M. P. Kazmkowsk, Dct toqu contol of PWM nvt-fd AC motos - A suvy, IEEE Tansactons on Industal Elctoncs, August, 2004, pp [9] F. Rashd, Snsolss spd contol of nducton moto dvs usng a obust and adaptv nuo-fuzzy basd ntllgnt contoll, Pocdngs of th 2004 IEEE Intnatonal Confnc on Industal Tchnology, ICIT, 2004, pp [10] A. Rubaa, D. Rckatts and M. D. Kankam, Dvlopmnt and Implmntaton of an Adaptv Fuzzy-Nual Ntwok Contoll fo Bushlss Dvs, IEEE Tansactons on Industy Applcatons, vol. 38, no.2, Mach/Apl 2002, pp [11] C. T. Ln, C. S. G. L, Nual fuzzy systms: a nuo-fuzzy syngsm to ntllgnt systms, Pntc Hall, AUTHOR PROFILES: SRINIVASA RAO JALLURI cvd th dg n lctcal & lctoncs ngnng fom Jawahalal nhu tchnologcal unvsty., n H s a sach studnt of Jawahalal nhu tchnologcal unvsty, Hydabad. Cuntly, h s an Assstant Pofsso at VBCE,Hydabad. Hs ntsts a n pow lctoncs and, nducton machns. D. B.V. SANKER RAM cvd th M.Tch. dg n lctcal ngnng fom th Osmana unvsty, n Pow systms. H cvd th Ph.D. dg n lctcal ngnng fom th Jawahalal nhu tchnologcal unvsty, Hydabad. Cuntly, h s a pofsso at Jawahalal nhu tchnologcal unvsty, Hydabad,Inda. Hs sach ntsts nclud FACTS, Pow lctoncs and Pow Systm Dynamcs. 108

Design and Implementation of Speed Controller with Anti-Windup Scheme for Three Phase Induction Motor Used in Electric Vehicle

Design and Implementation of Speed Controller with Anti-Windup Scheme for Three Phase Induction Motor Used in Electric Vehicle Intnatonal Jounal of Comput Applcatons (0975 8887 Volum 89 No 9, Mach 2014 Dsgn and Implmntaton of Spd Contoll wth Ant-Wndup Schm fo Th Phas Inducton Moto Usd n Elctc Vhcl Pasun Msha QHS (T CSIR-CMERI,