Rotational Speed Control of Multirotor UAV's Propulsion Unit based on Fractional-order PI Controller

Size: px
Start display at page:

Download "Rotational Speed Control of Multirotor UAV's Propulsion Unit based on Fractional-order PI Controller"

Transcription

1 Roonl Speed Conol of Muloo UAV's opulson Un bsed on Fconl-ode Conolle Wocech Genck, Tl Sdll, Josłw Goślńsk, o ozesk,, João. Coelho, Sš Sldć oznn Unvesy of Technology, oowo 3 See, oznn, olnd, Fculy of Eleccl Engneeng, nsue of Conol nd nfomon Engneeng Fculy of Compung, Ch of Conol nd Sysems Engneeng, Dvson of Sgnl ocessng nd Eleconc Sysems nsuo olécnco de Bgnç, Cmpus de Sn Apolón, Apdo 34, Bgnç, ougl Fculy of Engneeng, Unvesy of Rek, Vukovsk 58, 5 Rek, Co E-ml: wocech.genck@pu.poznn.pl conolle ype. should be noed h hs s he fses conol loop n he checue of muloo UAVs, whch leds o he hghes me equemens nd suons o be me. Absc n hs ppe he synhess of oonl speed closed-loop conol sysem bsed on fconl-ode popoonl-negl (FO) conolle s pesened. n pcul, s poposed he use of he SCoMR-FO pocedue s he conolle unng mehod fo n unmnned el vehcle s populson un. n hs fmewok, boh he Heme-Behle nd onygn heoems e used o pedefne sbly egon fo he conolle. Sevel smulons wee conduced n ode o y o nswe he quesons s he FO conolle good enough o be n lenve o moe complex FOD conolles? n wh ccumsnces cn be dvngeous ove he ubquous D? How obus hs fconl-ode conolle s egdng he pmec unceny of consdeed populson un model?. eywods fconl-ode conolle; speed conolle; FO conolle; lne BDC moo model; populson un; moo-oo model; Heme-Behle nd onygn heoems. NTRODUCTON Thee e wo mn obecves when desgnng conolle sysem: o ensue he conol sysem sbly nd subsequenly o povde he hghes possble conol pecson n he pesence of dsubnces nd uncenes. Those subecs hve been ddessed by mny eseches wokng on unmnned el vehcles (UAVs) especlly whn sevel conexs such s he conol lgohms [],[9], opmzon of he UAV s consucon [3] o ensung ful-olen conol [2]. Mny of hose soluons e nsped on des used fo fxed-wng UAVs [7],[27]. n he ppe [4], he uho poposed conolle n he λdμ (FOD Fconl-Ode D) sucue fo he poblem descbed n Secons 2-3. The mn dffculy (bu especvely, s s shown, lso he possbly) n he poposed soluon s he conolle unng wh fve sepe degees of feedom (conolle ses). Accodng o he defned cos funcon by usng pcle swm opmzon lgohm (see [3]), s possble o ensue he ckng of efeence sgnl (oonl speed of moo-oo un model used n UAVs) n moe effcen wy hn fo he D nd CDM (Coeffcen Dgm Mehod) conolles. Resuls e pesened n []. Beng n mnd he cscde conol sucue used n UAVs, s mpossble o hnk bou msson plnnng [8] o flghs uonomy [6],[2] whou ensung ppope soluons n he lowe lyes of conol checue (poson nd oenon conol). A hs boom level one cn fnd he sysem known s Eleconc Speed Conol (ESC). Ths module s esponsble o dve he DC moo v ppopely fs chnges of ulse Wdh Modulon (WM) duy cycles, ledng o he geneed hus nd oque. Theefoe, s mpon o use ppope moo-oo uns [28], wh he pope szes [5], pope ngemens [2] nd ppope /7/$3. 27 EEE ROBEM STATEMENT The oonl speed conol s deeply nvesged poblem, bu s sll n open e egdng he pplcon of moden echnques bsed on conol heoy. Fo UAVs hee e myd of dsnc conol sysems ppoches, some moe complex nd ohes smple bu wh hghe effcency. n he leue bgge enon s gven o hs second ype due o sevel esons such s s poenl pplcbly n he lowes lye of oonl speed conol nd smplcy egdng s mhemcl fomulon. Regdng hs concep nd he cuenly used soluons, he mn de oses: why no o exend he hgh flexbly nd smplcy of opoonlnegl-devve (D) conol o fconl-ode s counep o mpove he conol quly by usng s ledng dvnge. Nmely he possbly of moe ccue shpe fng of closed loop sysem s fequency chcescs, no esced only o 2log(gn). Ths cn be ned by he noducon of fconl-ode n he noon of nego nd dffeeno polynomls ps of conolle. Thus, one obns wo ddonl desgn pmees (odes of he nego nd dffeeno: λ nd μ). The choce depends on he shpe of me nd fequency chcescs of he closed-loop conol sysem [3]. 993

2 The wo mn poblems obseved n he pevous soluons wee he need o une he fve conolle pmees nd he lck of cle poposls fo mehods of he sbly ssunce, nlyss nd ssessmen n he pocedue fo he conol sysem synhess wh he poposed conolle ype. n ode o mee hese poblems, n he pesen wok, smple conolle sucue s used: λ (o lenvely nmed FO), o vefy f by usng s dvnges, s possble o popose n effcen conolle, wh bee pefomnce hn D nd FOD. The second ssue s o nswe o he queson: how obus s hs conolle on pmec unceny? Such compve nlyss nd esech e poposed fo he fs me nd e he novely nd conbuon of hs ppe. The ppe s ognzed s follows n Secon, SCoMR- FO pocedue s defned nd explned. A synhec nfomon bou populson un model poposed fo ess s povded n Secon V. n Secons V nd V, heoy bou fconl-ode conolles nd Heme-Behle nd onygn Theoems, s pesened. Secon V descbes FO conolle synhess nd he sysem sbly nlyss. s wo secons povde nfomon bou conduced ess nd concluson.. SCOMR-FO ROCEDURE The mos genel fom of he pocedue/lgohm fo modelng moo-oo uns nd fo he closed-loop sysem synhess, hee nmed SCoMR-FO (Modelng nd Roonl Speed Conol of Moo-Roo Un) wh he FO ype conolle, ssumes he fom:. Recod he possble me chcescs of moo-oo un fo vous ypes of efeence/npu sgnls. 2. By usng pmec esmon mehods (.e. üpfmülle, Sec o gphcl mehod) defne/clcule he pmees vlues fo he pedefned pln model sucue (.e. nsfe funcon sucue) nd pefom he model vldon on ohe ecoded d ses fom es bed. 3. Fo he conolle n he FO sucue descbed by he nsfe funcon, use he Heme-Behle nd onygn heoems o fnd he conolle gns of, nd degee of nego p s polynoml λ, fo whch he closed-loop conol sysem s sble. 4. Fo he desgned sech spce (, nd λ) use he chosen lgohm o fnd he opmum vlue of he cos funcon (fo exmple: mnmum of he negl of Absolue Eo AE o mnmum of he negl of Squed Eo SE). 5. Genee me couses fo some of bes esuls (hose wh smll vlues of cos funcon). 6. Selec he soluon (, nd λ se vlue) fo whch he me couses mee he expecons (fo exmple: one h povdes smll/no oveshoo, sho lg/selng me, smll/no conol eo, ec.). NOTE: Becuse he conolle se sech s bsed on negl quly ndcos nd hey do no ke decly no ccoun he shpe of he geneed me couses of closed-loop sysem (only descbe he numecl devon beween he oupu sgnl nd he efeence one), hee s song need fo use he seps 5 nd 6 of he SCoMR-FO lgohm. n he followng secons, moe dels on ech lgohm sep, e pesened. V. MODE OF ROUSON UNT n ode o fulfl he needs of oonl speed conol n el ESC sysem, specl es bed ws conduced he nsue of Conol nd nfomon Engneeng of he oznn Unvesy of Technology. Bsed on he ecoded me couses (elon beween he moo ngul speed nd he ppled volge []), one cn ssume he exsence of moo-oo un mhemcl model h descbes well enough he devce dynmcs. Regdng pevous sudes nd expeences, numbe of dffeened models wee poposed, subsequenly condonng he conol lw nd he conolle ype, whch cn be used o buld he conol sysem. Exmples cn be found n sevel woks. n [] n ppoxmon of moo-oo un dynmcs by lne second-ode nel model ws poposed. Auhos of efeences [4-6] desgned fs-ode ne model wh pue me dely, whch cn be ppoxmed by he second-ode nel model. n [24] he second-ode nel pln model wh me dely ws developed. n [2] fuzzy model of coxl populson un (fs-ode nel elemen wh he vyng me consn) ws defned. ws decded o ecod chcescs of he AX 284/2 GOD NE BDC moo fom T-Model Moos compny wh hee-blded popelle GWS-HD95x3-SW 9x5. Moe dels bou he used es bed, dedced DYNO Temnl sofwe nd cquson woks, e povded n []. Also, n [3], compehensve physcl chcesc nd usfcon fo he choce of h pcul moo-oo un, e povded. Fom he ess pefomed o obn he nsfe funcon of he moo-oo model (elons beween ngul speed Ω nd ppled volge V), one decded o use fs-ode nel model wh nspo dely : G () s () s () s Ω b s = = e, () V s + nd wo ppoxmon ppoches wh he use of: - DENT lby of MATAB sofwe, - d-hoc gphcl mehod (üpfmülle) nd by selecon of he model pmees. Fom vldon expemens, bee cuve fng nd, s esul, pmees of moo-oo un model s nsfe funcon, povded he second mehod. V. FO CONTROER THEORETCA BACGROUND Theoecl bscs of fconl clculus e pesened n [] nd [9]. Exmples of fconl-ode conol pplcons n elon o poson/oenon conol of muloo UAVs cn be found n [26] nd moe exmples of such conolles synhess n he wok []. n he cles [22] nd [23], nfomon bou me nd fequency domn nlyss e, especvely, povded. 994

3 Accodng o [] fconl clculus s genelzon of dffeenon nd negon o non-nege ode fundmenl (connuous nego-dffeenl) opeo D defned s: D = d R() d R() ( dτ ) R( ) > =, < whee nd e opeon lms nd s he opeon ode (usully s el vlue). Fom he Remnn-ouvlle defnon of he fconl dffeo-negl: f ( τ ) ( τ ) n D () = ( n ) + Γ (2) d d τ (3) n α d fo n < < n whee Γ () s he Eule s Gmm funcon, n nlogy o nege-ode sysems, fo non-nege ode sysems, one my use he plce nsfom of equon (3), whch s defned s: s n k k () d = s F () s s D f () e D f (4) k = = fo n < < n, whee s denoes he plce nsfom vble nd s=. Fom he equon (4), s hence possble o se he sucue of FO conolle ype o he fom of nsfe funcon: C λ () s = + s, (5) whee s he popoonl gn, negon gn nd λ s posve el numbe. The qus-polynoml (s), whch descbes he closed-loop chcesc equon of he sysem fom Fg. s gven by: λ s () s = ( b + b s ) e + s. (6) + n ode o fnd he conolle pmees ses, Heme-Behle nd onygn heoems e used. V. HERMTE-BEHER AND ONTRYAGN THEOREM Theoem. Heme-Behle Theoem ([8],[7]). e be complex funcon of descbed by equon: ( ) ( ) + ( ), = (7) whee ( ) nd ( ) ps of ( ). The ( ) ) ( ) nd ( ) e nelced; epesen he el nd mgny s sble f: only hve smple el oos nd hese ' 2) ( ) ( ) ( ) ( ) > ' n (,+ ),, fo some = ' Whee ' ( ) nd ( ) e he devves of ( ) nd ( ) wh espec o. An mpon sep s o ensue h ( ) nd ( ) only hve el oos. Ths cn be cheved by pplyng he onygn Theoem. Theoem 2. onygn Theoem e () s be descbed by he equon (7) ssumng s=. To ssue h ( ) = nd ( ) = only hve el oos, mus be ssued h n nevls 2 lπ + η 2lπ + η l =,2,3,..., (8) ( ) nd ( ) hve excly 4lN+M oos. Fo suons whee chcesc equon s of fconl ode, mus hve 4l([N]+)+[M]+ oos, he ( ) nd ( ) whee [ ] epesens he nege p, nd N nd M e ken s degee of he numeo nd denomno polynomls of he nege p. oofs cn be found n [8]. As s shown n [24], s necessy o ewe he (s) qus-polynoml s: λ s () s b s + b + ( s ) e s. = (9) λ + Assumng h g=s nd λ=/b: g / ( g ) = b ( g / ) + b + ( g / + ) e ( g / ). () b Fg.. Block dgm of closed-loop conol sysem wh he FO conolle ype nd moo-oo model Thus, fo g=, ( ) becomes: + ( ) = b ( / ) + b ( / + ) e ( / ). () Replcng he e wh cos()+sn(), he el ( ) nd mgny ( ), ps of ( ) cn be descbed by:, 995

4 Re m / ( ) = b + cos ( ) ( ) ( ) + b cos ( ) + sn ( ) b m sn ( ) sgn ( ), ( ) = b + cos ( ) Re( ). sn ( ) ( ) sgn ( ) cos ( ) + sn ( ) (2) (3) Accodng o he onygn Theoem ( ) nd ( ) =. The pmee cn be descbed by: = V. CONTROER SYNTHESS AND SYSTEM STABTY ANAYSS n ode o deemne he pemssble spce of conolle ses (, nd λ) fo whch he closed-loop conol sysem wh FO conolle s sble, s poposed o use he negl quly ndces (AE nd SE) nd, especvely, equon (4) nd nequly (8) o deemne he nge of nd pmees. The sysem s sble n ccodnce wh Bounded npu Bounded Oupu (BBO) ceon, when he condons e me:. The duon of smulon mus be he sme s he desed smulon me se he pocess begnnng. 2. Only successfully conduced smulons e consdeed: one needs o vefy f he consecuve peks of he oupu sgnl y() e decesng by mesung he dffeence beween hem. n ffmve cse, he sysem s ssumed o be sble. cos b = b b cos ( ) + sn ( ) b ( ) + sn ( ) Re m ( ) ( ) + sgn ( ). (4) One cn ewe he ( ) s: ( ) b m( ) b( ), = (5) m( ) = Re ( ), (6) b( ) = cos ( ) + sn ( ) Re( ) / b (7) sn ( ) + cos ( ) m( ) sgn ( ). Fg. 2. Sbly egons of pmees, fo chnge of λ vlues fom. o fo closed-loop conol sysem wh pln model (): vlue fom -2 o 2 (sep: 4 d/s). The sech of conolle ses fom Fg. 2 n he desgned spce (fo whch he closed-loop conol sysem s sble), o fnd he bes ckng quly (, nd λ ses whch ensue he possbly fs ckng nd sgnl wh mnml o no oveshoo), my be bsed on ecoded vlues of quly ndcos (n hs ppe he AE), o on nohe cos funcon, n ccodnce wh seleced opmzon mehods. n ccodnce wh [4], he nge of pmees h ssues closed-loop sbly mus me he condons: mx < mn Snce ( ) ( m ( ) b ( )) m ( ) b ( ) ( ) <,. =,,2,... (8) s n odd funcon, hs he oo =. Thus, fo = =: ( ) = b. (9) + To ensue he nelce popey beween ( ) nd ( ) one mus mpose: Fg. 3. Refeence sgnl (SET) ckng n dsubed (DST) sysems (wh CDM, D, FOD nd FO conolles) conol sgnl consns (u mx=±6). ( ) > => b + > => > / b. (2) 996

5 Fg. 4. AE vlues s funcon of λ fo FO conolle ype. Fg. 8. AE nd SE vlues due o he chnge of nd populson un model pmees. Fg. 5. vlues s funcon of λ fo FO conolle ype. Fg. 6. Sbly egons of pmees, fo chnge of λ vlues fom. o fo closed-loop conol sysem wh nomnl pln model (): vlue fom -π o π (sep: 2π/). Fg. 7. Compson of ckng effecveness fo wo FO conolles: FO ( =32.27, =.9, λ=.49, AE=.3) nd FO2 ( =2.86, =4.4, λ=., AE=.3). V. COMARATVE TESTS RESUTS n hs ppe, esuls e pesened fo he model () fom [], n whch b =, =, =.4, =.35. Tes Bsed on eve sech n sbly egon fom Fg. 2, ecoded ckng me couses nd AE vlues fo he poblem llused n Fg. 3, FO conolle ses wee seleced ( =32.27, =.9, λ=.49), fulfllng he ssumpons fom he pevous secon. The FO conolle effecveness ws comped wh ohes fom [] nd [4] s depced n Fg. 3. The mn m ws cheved: bee ckng quly ws obned (n he pesence of sep ype dsubnces nd conol sgnl suon) fo he bes unes of D (dels n [4]) nd ype conolles. As dsdvnge one my egd ppeng oscllons. f he conolle ses sech eled solely on nlyss of AE vlues, one my conclude h smple conolle ype s enough fo ckng conol puposes (83 fom bes AE vlues wee obned fo = nd λ fom. o ). Howeve, me couses show h oveshoo s no decesed o zeo. n he emnng 7 vns, lso he use of he nego does no gunee he elmnon of sedy-se eo ( should be emembeed h one mus del hee wh fconl-ode fo nego p of conolle). Bsed on Fg. 4 nd Fg. 5, fo sml nge of vlues, n lowe nge of λ, s possble o enfoce he mpovemen (decese) of he AE (by he ncese of ). n pcce, n he conolle ses sech, useful nge of vlues ncluded: fom 24 o 33, fom o 4 nd λ fom.49 o.79. Tes Relve o Tes, nge of vlues ws chnged fom π o π (sep: 2π/) [25]. ws evlued whehe he decese of vlue (nd heeby spce of ses fo whch closed-loop sysem s sble), wll cuse dcl deeoon n he efeence sgnl ckng quly. The bes ckng pefomnce nd lowes vlue of AE, wee obned fo ses: =2.86, =4.4 nd λ=.. Despe he educon on he sech spce sze fo FO conolle ses (see Fg. 6), hee ws no loss of ckng quly (see Fg. 7). Tes The conolle obned n Tes ws vlded n conex of obusness on pmec unceny (see Fg. 8). Model pmees nd wee chnged up o 25% 997

6 of nomnl vlues. The obusness s smlle hn fo nomnl model, only fo smulneously bgge vlues of nd, h s, AE nd SE vlues gow. X. CONCUSON n hs ppe, he SCoMR-FO pocedue fo conol sysem synhess wh he FO conolle nd model of UAV s populson un s poposed, by usng he Heme-Behle nd onygn heoems. Ths mehod povdes he bee ckng quly hn clsscl D nd CDM conolles. Howeve, s pefomnce s less effcen hn he fconl ode D conol. The educon of he conolle pmees numbe fom fve n FOD ype conolle (,, D, λ, μ) o hee n FO, hs pos nd cons. One my use Heme- Behle nd onygn heoems o pedefne sbly egon fo conolle ses sech. The possbly o use wo moe ses (degees of feedom: D, μ) on FOD conolle genees ncesed compuonl complexy. n hs feld, FO conolle my be n lenve. n fc, povdes hgh obusness nd my be used o conol populson un model, whch pmees vy fom el pln pmees. Fuhe esech wll nclude dscee veson of he poposed FO conolle by Ousloup ppoxmon nd opmzon echnques o shoen he unng me. REFERENCES [] V.S. Akknpll, G.. Flcon, nd F. Holzpfel, Aude conol of mulcope usng ugmened quenon bsed bckseppng, 24 EEE ne. Conf. on Aeospce Eleconcs nd Remoe Sensng Technology (CARES), pp. 7-78, Yogyk, ndones 24. [2] D. Aleksndov nd. enkov, Opmzon Mn Unmnned Helcope Enegy Consumpon by Chngng Geomecl mees of Coxl Roo s, Topcl oblems n he Feld of Eleccl nd owe Engneeng, onlne, pp. 39-4, 22. [3] V.M. Aellno-Qunn, E.A. oll-floes, E.A. Mechn-Cuz, nd.a. Nno-Suez, Muloo Desgn Opmzon Usng Genec Algohm, n 26 nenonl Confeence on Unmnned Acf Sysems (CUAS), pp , Alngon, USA 26. [4] R. Bellmn nd.. Cooke, Dffeenl-Dffeence Equons, Acdemc ess, vol. 45, no. 6 DO:.2/zmm , 963. [5] A. Bondy, S. Gdeck,. Gąso, nd W. Genck, efomnce of coxl populson n desgn of mul-oo UAVs, Advnces n nellgen Sysems nd Compung, Spnge, pp , 26, DO:.7/ _46. [6] A.S. Bndão, F.N. Mns, nd H.B. Sonegue, A Vson-bsed ne Followng Segy fo n Auonomous UAV, 25 2h nenonl Confeence on nfomcs n Conol, Auomon nd Robocs (CNCO), pp , Colm, Fnce 25. [7] A.-C. Bezoescu, T. Espnoz,. Csllo, nd R. ozno, Adpve Tecoy Followng fo Fxed-Wng UAV n esence of Cosswnd, Jounl of nellgen nd Robocs Sysems, vol. 69, ssue -4, pp , 23. [8] R. Cponeo, G. Dongol,. Foun, nd. es, Fconl Ode Sysems Modelng nd Conol Applcons, Wold Scenfc Sees on Nonlne Scence: Sngpoe, Sees A, no. 72, 2. [9]. Csllo, R. ozno, nd A.E. Dzul, Modellng nd Conol of Mn- Flyng Mchnes, Spnge, ondon, 25. [] YQ. Chen,. es, nd D. Xue, Fconl Ode Conol A Tuol, Amecn Conol Confeence, pp , S. ous, USA 29. [] S. Gdeck, W. Genck, nd J. Goślńsk, Speed Conol of Dve Un n Fou-Roo Flyng Robo, n oc. of he 23 h nenonl Confeence on nfomcs n Conol, Auomon nd Robocs (CNCO), pp , Reykvk, celnd 23, DO:.522/ [2]. Gąso, A. Bondy, S. Gdeck, W. Genck, nd A. sńsk, Thus esmon by fuzzy modelng of coxl populson un fo muloo UAVs, n oceedngs of he 26 EEE nenonl Confeence on Mulsenso Fuson nd negon fo nellgen Sysems (MF), pp , Bden-Bden, Gemny 26, DO:.9/MF [3] W. Genck nd J.. Coelho, Effecve unng ppoches of D fconl-ode speed conolle fo muloo UAV s moo-oo. [4] W. Genck, Ne o opml desgn of λ D μ fconl-ode speed conolle (FOD) fo muloo moo-oo smplfed model, n oc. of he 26 nenonl Confeence on Unmnned Acf Sysems (CUAS), pp , Alngon, USA 26, DO:.9/CUAS [5] W. Genck, D. Hol, T. Sdll, nd J.. Coelho, Robus CDM nd ole lcemen D Bsed Thus Conolles fo Muloo Moo- Roo Smpled Model, 26 nenonl Sben Confeence on Conol nd Communcons (SBCON), pp. -5, Moscow, Russ 26, DO:.9/SBCON [6] W. Genck nd T. Sdll, Compson of ckng pefomnce nd obusness of he smpled model of muloo el obo wh CDM nd D (wh n-wndup compenson) conolles, Jounl of Conol Engneeng nd Appled nfomcs. [7] S. Hfs,. bd, nd R. Fkh, Synhess of fconl conolle fo fs-ode me dely sysem, Tns. of he nsue of Mesuemen nd Conol, vol. 35, no. 8, pp , 23. [8]. Mhe,. Busonu,. Bbs,. Mcle, J. Bbnd, nd C. ug, Vson-Bsed Conol of Qudoo fo n Obec nspecon Sceno, n oc. of he 26 nenonl Confeence on Unmnned Acf Sysems (CUAS), pp , Alngon, USA 26. [9] C.A. Mone, YQ. Chen, B.M. Vnge, D. Xue, nd V. Felu, Fconlode Sysems nd Conols. Fundmenls nd Applcons, Spnge, ondon, 2. [2] M. Muhlegg,. Nemye, G.. Flcon, nd F. Holzpfel, Ful Tolen Adpve Conol of Hexcope wh Conol Degdon, n oc. of he 25 EEE Confeence on Conol Applcons (CCA), pp , Sydney, Ausl 25, NSW. [2] M. Neuwenhusen, D. Doeschel, M. Beul, nd S. Behnke, Auonomous Nvgon fo Mco Ael Vehcles n Complex GNSSdened Envonmens, Jounl of nellgen nd Robocs Sysems, pp. -8, 25, DO:.7/s [22]. eáš, The fconl-ode conolles: mehods fo he synhess nd pplcon, Jounl of Eleccl Engneeng, vol. 5, no. 9-, pp , 999. [23]. odlubny, Fconl-ode sysems nd λ D μ -conolles, EEE Tnscons on Auomc Conol, vol. 44, no., pp , 999. [24] T. Sdll, D. Hol, W. Genck, nd. ozesk, nfluence of me dely n fconl-ode conolle fo second-ode osclloy sysem wh me-dely, n evew. [25] T. Sdll, D. Hol, W. Genck, nd. ozesk, Sbly Anlyss nd Tckng efomnce of Fconl-Ode Conolle fo Second-Ode Osclloy Sysem wh Tme-Dely, 2h nenonl Confeence on Mehods nd Models n Auomon nd Robocs (MMAR), pp , Mędzyzdoe, olnd 26, DO:.9/MMAR [26] H. Sbs nd S. hvecoglu, Conol of Qudoo usng cle Swm Opmzon uned Fconl Ode D Conolle, 8 h Ank nenonl Aeospce Confeence, Ank, Tukey 25. [27] J. Smh, C. u, nd W.H. Chen, Dsubnce Obseve Bsed Conol fo Gus Allevon of Smll Fxed-Wng UAS, n oc. of he 26 nenonl Confeence on Unmnned Acf Sysems (CUAS), pp. 97-6, Alngon, USA 26. [28] H. Won m nd R.E. Bown, A Compson of Coxl nd Convenonl Roo efomnce, Jounl of he Amecn Helcope Socey, vol. 55, 29, DO:.45/JAHS

HERMITE SERIES SOLUTIONS OF LINEAR FREDHOLM INTEGRAL EQUATIONS

HERMITE SERIES SOLUTIONS OF LINEAR FREDHOLM INTEGRAL EQUATIONS Mhemcl nd Compuonl Applcons, Vol 6, o, pp 97-56, Assocon fo Scenfc Resech ERMITE SERIES SOLUTIOS OF LIEAR FREDOLM ITEGRAL EQUATIOS Slh Ylçınbş nd Müge Angül Depmen of Mhemcs, Fcul of Scence nd As, Cell

More information

Rotations.

Rotations. oons j.lbb@phscs.o.c.uk To s summ Fmes of efeence Invnce une nsfomons oon of wve funcon: -funcons Eule s ngles Emple: e e - - Angul momenum s oon geneo Genec nslons n Noehe s heoem Fmes of efeence Conse

More information

Available online Journal of Scientific and Engineering Research, 2017, 4(2): Research Article

Available online   Journal of Scientific and Engineering Research, 2017, 4(2): Research Article Avlble onlne www.jse.com Jonl of Scenfc nd Engneeng Resech, 7, 4():5- Resech Acle SSN: 394-63 CODEN(USA): JSERBR Exc Solons of Qselsc Poblems of Lne Theoy of Vscoelscy nd Nonlne Theoy Vscoelscy fo echnclly

More information

Calculus 241, section 12.2 Limits/Continuity & 12.3 Derivatives/Integrals notes by Tim Pilachowski r r r =, with a domain of real ( )

Calculus 241, section 12.2 Limits/Continuity & 12.3 Derivatives/Integrals notes by Tim Pilachowski r r r =, with a domain of real ( ) Clculu 4, econ Lm/Connuy & Devve/Inel noe y Tm Plchow, wh domn o el Wh we hve o : veco-vlued uncon, ( ) ( ) ( ) j ( ) nume nd ne o veco The uncon, nd A w done wh eul uncon ( x) nd connuy e he componen

More information

Lecture 5 Single factor design and analysis

Lecture 5 Single factor design and analysis Lectue 5 Sngle fcto desgn nd nlss Completel ndomzed desgn (CRD Completel ndomzed desgn In the desgn of expements, completel ndomzed desgns e fo studng the effects of one pm fcto wthout the need to tke

More information

Heat conduction in a composite sphere - the effect of fractional derivative order on temperature distribution

Heat conduction in a composite sphere - the effect of fractional derivative order on temperature distribution MATEC We of Confeence 57, 88 (8) MMS 7 hp://do.og/.5/mecconf/85788 He conducon n compoe phee - he effec of fconl devve ode on empeue duon Uzul Sedlec,*, Snłw Kul Inue of Mhemc, Czeochow Unvey of Technology,

More information

Go over vector and vector algebra Displacement and position in 2-D Average and instantaneous velocity in 2-D Average and instantaneous acceleration

Go over vector and vector algebra Displacement and position in 2-D Average and instantaneous velocity in 2-D Average and instantaneous acceleration Mh Csquee Go oe eco nd eco lgeb Dsplcemen nd poson n -D Aege nd nsnneous eloc n -D Aege nd nsnneous cceleon n -D Poecle moon Unfom ccle moon Rele eloc* The componens e he legs of he gh ngle whose hpoenuse

More information

Synthesis of an Assigned Structure Generator of Binary Sequence Sets

Synthesis of an Assigned Structure Generator of Binary Sequence Sets Inenonl Jounl of Appled Enneen Resech ISSN 97-5 Volume Numbe 5 (8) pp - Resech Ind Publcons hp://wwwpublconcom Synhess of n Assned Sucue Geneo of Bny Sequence Ses Eveny F Beezkn Nonl Resech Nucle Unvesy

More information

5-1. We apply Newton s second law (specifically, Eq. 5-2). F = ma = ma sin 20.0 = 1.0 kg 2.00 m/s sin 20.0 = 0.684N. ( ) ( )

5-1. We apply Newton s second law (specifically, Eq. 5-2). F = ma = ma sin 20.0 = 1.0 kg 2.00 m/s sin 20.0 = 0.684N. ( ) ( ) 5-1. We apply Newon s second law (specfcally, Eq. 5-). (a) We fnd he componen of he foce s ( ) ( ) F = ma = ma cos 0.0 = 1.00kg.00m/s cos 0.0 = 1.88N. (b) The y componen of he foce s ( ) ( ) F = ma = ma

More information

Advanced Electromechanical Systems (ELE 847)

Advanced Electromechanical Systems (ELE 847) (ELE 847) Dr. Smr ouro-rener Topc 1.4: DC moor speed conrol Torono, 2009 Moor Speed Conrol (open loop conrol) Consder he followng crcu dgrm n V n V bn T1 T 5 T3 V dc r L AA e r f L FF f o V f V cn T 4

More information

Reinforcement learning

Reinforcement learning CS 75 Mchine Lening Lecue b einfocemen lening Milos Huskech milos@cs.pi.edu 539 Senno Sque einfocemen lening We wn o len conol policy: : X A We see emples of bu oupus e no given Insed of we ge feedbck

More information

Fast Algorithm for Walsh Hadamard Transform on Sliding Windows

Fast Algorithm for Walsh Hadamard Transform on Sliding Windows Fs Algohm fo Wlsh Hdmd Tnsfom on Sldng Wndows Wnl Oung W.K. Chm Asc Ths ppe poposes fs lgohm fo Wlsh Hdmd Tnsfom on sldng wndows whch cn e used o mplemen pen mchng mos effcenl. The compuonl equemen of

More information

Numerical Analysis of Freeway Traffic Flow Dynamics under Multiclass Drivers

Numerical Analysis of Freeway Traffic Flow Dynamics under Multiclass Drivers Zuojn Zhu, Gng-len Chng nd Tongqng Wu Numecl Anlyss of Feewy Tffc Flow Dynmcs unde Mulclss Dves Zuojn Zhu, Gng-len Chng nd Tongqng Wu Depmen of Theml Scence nd Enegy Engneeng, Unvesy of Scence nd Technology

More information

Chebyshev Polynomial Solution of Nonlinear Fredholm-Volterra Integro- Differential Equations

Chebyshev Polynomial Solution of Nonlinear Fredholm-Volterra Integro- Differential Equations Çny Ünvee Fen-Edeby Füle Jounl of A nd Scence Sy : 5 y 6 Chebyhev Polynol Soluon of onlne Fedhol-Vole Inego- Dffeenl Equon Hndn ÇERDİK-YASA nd Ayşegül AKYÜZ-DAŞCIOĞU Abc In h ppe Chebyhev collocon ehod

More information

Supporting information How to concatenate the local attractors of subnetworks in the HPFP

Supporting information How to concatenate the local attractors of subnetworks in the HPFP n Effcen lgorh for Idenfyng Prry Phenoype rcors of Lrge-Scle Boolen Newor Sng-Mo Choo nd Kwng-Hyun Cho Depren of Mhecs Unversy of Ulsn Ulsn 446 Republc of Kore Depren of Bo nd Brn Engneerng Kore dvnced

More information

6.6 The Marquardt Algorithm

6.6 The Marquardt Algorithm 6.6 The Mqudt Algothm lmttons of the gdent nd Tylo expnson methods ecstng the Tylo expnson n tems of ch-sque devtves ecstng the gdent sech nto n tetve mtx fomlsm Mqudt's lgothm utomtclly combnes the gdent

More information

Name of the Student:

Name of the Student: Engneeng Mahemacs 05 SUBJEC NAME : Pobably & Random Pocess SUBJEC CODE : MA645 MAERIAL NAME : Fomula Maeal MAERIAL CODE : JM08AM007 REGULAION : R03 UPDAED ON : Febuay 05 (Scan he above QR code fo he dec

More information

1 Constant Real Rate C 1

1 Constant Real Rate C 1 Consan Real Rae. Real Rae of Inees Suppose you ae equally happy wh uns of he consumpon good oday o 5 uns of he consumpon good n peod s me. C 5 Tha means you ll be pepaed o gve up uns oday n eun fo 5 uns

More information

_ J.. C C A 551NED. - n R ' ' t i :. t ; . b c c : : I I .., I AS IEC. r '2 5? 9

_ J.. C C A 551NED. - n R ' ' t i :. t ; . b c c : : I I .., I AS IEC. r '2 5? 9 C C A 55NED n R 5 0 9 b c c \ { s AS EC 2 5? 9 Con 0 \ 0265 o + s ^! 4 y!! {! w Y n < R > s s = ~ C c [ + * c n j R c C / e A / = + j ) d /! Y 6 ] s v * ^ / ) v } > { ± n S = S w c s y c C { ~! > R = n

More information

SIMPLIFIED ROTATING TIRE MODELS BASED ON CYLINDRICAL SHELLS WITH FREE BOUNDARY CONDITIONS

SIMPLIFIED ROTATING TIRE MODELS BASED ON CYLINDRICAL SHELLS WITH FREE BOUNDARY CONDITIONS F1-NVH-8 SIMPLIFIED ROTATING TIRE MODELS BASED ON CYLINDRICAL SHELLS WITH FREE BOUNDARY CONDITIONS 1 Alujevc Neven * ; Cmpllo-Dvo Nu; 3 Knd Pee; 1 Pluymes Be; 1 Ss Pul; 1 Desme Wm; 1 KU Leuven PMA Dvson

More information

THE EXISTENCE OF SOLUTIONS FOR A CLASS OF IMPULSIVE FRACTIONAL Q-DIFFERENCE EQUATIONS

THE EXISTENCE OF SOLUTIONS FOR A CLASS OF IMPULSIVE FRACTIONAL Q-DIFFERENCE EQUATIONS Europen Journl of Mhemcs nd Compuer Scence Vol 4 No, 7 SSN 59-995 THE EXSTENCE OF SOLUTONS FOR A CLASS OF MPULSVE FRACTONAL Q-DFFERENCE EQUATONS Shuyun Wn, Yu Tng, Q GE Deprmen of Mhemcs, Ynbn Unversy,

More information

Previously. Extensions to backstepping controller designs. Tracking using backstepping Suppose we consider the general system

Previously. Extensions to backstepping controller designs. Tracking using backstepping Suppose we consider the general system 436-459 Advnced contol nd utomtion Extensions to bckstepping contolle designs Tcking Obseves (nonline dmping) Peviously Lst lectue we looked t designing nonline contolles using the bckstepping technique

More information

Circuits 24/08/2010. Question. Question. Practice Questions QV CV. Review Formula s RC R R R V IR ... Charging P IV I R ... E Pt.

Circuits 24/08/2010. Question. Question. Practice Questions QV CV. Review Formula s RC R R R V IR ... Charging P IV I R ... E Pt. 4/08/00 eview Fomul s icuis cice s BL B A B I I I I E...... s n n hging Q Q 0 e... n... Q Q n 0 e Q I I0e Dischging Q U Q A wie mde of bss nd nohe wie mde of silve hve he sme lengh, bu he dimee of he bss

More information

CITY OF TIMMINS BY-LAW NO

CITY OF TIMMINS BY-LAW NO CITY OF TIMMINS BEING A BY-LAW o uhoze he Copoon of he Cy of Tmmns o mend By- lw No. 2014-7561wh Rvesde Emeld ( Tmmns) Popey Holdngs Inc. nd he benefcl owne Rvesde Emeld ( Tmmns) Lmed Pneshp s epesened

More information

Generalisation on the Zeros of a Family of Complex Polynomials

Generalisation on the Zeros of a Family of Complex Polynomials Ieol Joul of hemcs esech. ISSN 976-584 Volume 6 Numbe 4. 93-97 Ieol esech Publco House h://www.house.com Geelso o he Zeos of Fmly of Comlex Polyomls Aee sgh Neh d S.K.Shu Deme of hemcs Lgys Uvesy Fdbd-

More information

ScienceDirect. Behavior of Integral Curves of the Quasilinear Second Order Differential Equations. Alma Omerspahic *

ScienceDirect. Behavior of Integral Curves of the Quasilinear Second Order Differential Equations. Alma Omerspahic * Avalable onlne a wwwscencedeccom ScenceDec oceda Engneeng 69 4 85 86 4h DAAAM Inenaonal Smposum on Inellgen Manufacung and Auomaon Behavo of Inegal Cuves of he uaslnea Second Ode Dffeenal Equaons Alma

More information

Calculation of Thermal Neutron Flux in Two. Dimensional Structures with Periodic Moderators

Calculation of Thermal Neutron Flux in Two. Dimensional Structures with Periodic Moderators Apple Mhemcl Scences Vol. 8 no. 9 99-98 Clculon of Theml Neuon Flu n Two mensonl Sucues wh Peoc Moeos S. N. Hossenmolgh S. A. Agh L. Monzen S. Bsn In Unvesy of Scence n Technology Tehn In epmen of Nucle

More information

Technical Appendix for Inventory Management for an Assembly System with Product or Component Returns, DeCroix and Zipkin, Management Science 2005.

Technical Appendix for Inventory Management for an Assembly System with Product or Component Returns, DeCroix and Zipkin, Management Science 2005. Techc Appedx fo Iveoy geme fo Assemy Sysem wh Poduc o Compoe eus ecox d Zp geme Scece 2005 Lemm µ µ s c Poof If J d µ > µ he ˆ 0 µ µ µ µ µ µ µ µ Sm gumes essh he esu f µ ˆ > µ > µ > µ o K ˆ If J he so

More information

Lecture 3 summary. C4 Lecture 3 - Jim Libby 1

Lecture 3 summary. C4 Lecture 3 - Jim Libby 1 Lecue su Fes of efeece Ivce ude sfoos oo of H wve fuco: d-fucos Eple: e e - µ µ - Agul oeu s oo geeo Eule gles Geec slos cosevo lws d Noehe s heoe C4 Lecue - Lbb Fes of efeece Cosde fe of efeece O whch

More information

FIRMS IN THE TWO-PERIOD FRAMEWORK (CONTINUED)

FIRMS IN THE TWO-PERIOD FRAMEWORK (CONTINUED) FIRMS IN THE TWO-ERIO FRAMEWORK (CONTINUE) OCTOBER 26, 2 Model Sucue BASICS Tmelne of evens Sa of economc plannng hozon End of economc plannng hozon Noaon : capal used fo poducon n peod (decded upon n

More information

Modern Energy Functional for Nuclei and Nuclear Matter. By: Alberto Hinojosa, Texas A&M University REU Cyclotron 2008 Mentor: Dr.

Modern Energy Functional for Nuclei and Nuclear Matter. By: Alberto Hinojosa, Texas A&M University REU Cyclotron 2008 Mentor: Dr. Moden Enegy Funconal fo Nucle and Nuclea Mae By: lbeo noosa Teas &M Unvesy REU Cycloon 008 Meno: D. Shalom Shlomo Oulne. Inoducon.. The many-body poblem and he aee-fock mehod. 3. Skyme neacon. 4. aee-fock

More information

f(x) dx with An integral having either an infinite limit of integration or an unbounded integrand is called improper. Here are two examples dx x x 2

f(x) dx with An integral having either an infinite limit of integration or an unbounded integrand is called improper. Here are two examples dx x x 2 Impope Inegls To his poin we hve only consideed inegls f() wih he is of inegion nd b finie nd he inegnd f() bounded (nd in fc coninuous ecep possibly fo finiely mny jump disconinuiies) An inegl hving eihe

More information

ME 141. Engineering Mechanics

ME 141. Engineering Mechanics ME 141 Engineeing Mechnics Lecue 13: Kinemics of igid bodies hmd Shhedi Shkil Lecue, ep. of Mechnicl Engg, UET E-mil: sshkil@me.bue.c.bd, shkil6791@gmil.com Websie: eche.bue.c.bd/sshkil Couesy: Veco Mechnics

More information

Parameter Reestimation of HMM and HSMM (Draft) I. Introduction

Parameter Reestimation of HMM and HSMM (Draft) I. Introduction mee eesmon of HMM nd HSMM (Df Yng Wng Eml: yngwng@nlp..c.cn Absc: hs echncl epo summzes he pmee eesmon fomule fo Hdden Mkov Model (HMM nd Hdden Sem-Mkov Model (HSMM ncludng hes defnons fowd nd bckwd vbles

More information

Chapter 4: Motion in Two Dimensions Part-1

Chapter 4: Motion in Two Dimensions Part-1 Lecue 4: Moon n Two Dmensons Chpe 4: Moon n Two Dmensons P- In hs lesson we wll dscuss moon n wo dmensons. In wo dmensons, s necess o use eco noon o descbe phscl qunes wh boh mnude nd decon. In hs chpe,

More information

Real-coded Quantum Evolutionary Algorithm for Global Numerical Optimization with Continuous Variables

Real-coded Quantum Evolutionary Algorithm for Global Numerical Optimization with Continuous Variables Chnese Jounal of Eleconcs Vol.20, No.3, July 2011 Real-coded Quanum Evoluonay Algohm fo Global Numecal Opmzaon wh Connuous Vaables GAO Hu 1 and ZHANG Ru 2 (1.School of Taffc and Tanspoaon, Souhwes Jaoong

More information

EE 410/510: Electromechanical Systems Chapter 3

EE 410/510: Electromechanical Systems Chapter 3 EE 4/5: Eleomehnl Syem hpe 3 hpe 3. Inoon o Powe Eleon Moelng n Applon of Op. Amp. Powe Amplfe Powe onvee Powe Amp n Anlog onolle Swhng onvee Boo onvee onvee Flyb n Fow onvee eonn n Swhng onvee 5// All

More information

CHAPTER 10: LINEAR DISCRIMINATION

CHAPTER 10: LINEAR DISCRIMINATION HAPER : LINEAR DISRIMINAION Dscmnan-based lassfcaon 3 In classfcaon h K classes ( k ) We defned dsmnan funcon g () = K hen gven an es eample e chose (pedced) s class label as f g () as he mamum among g

More information

A Design Configuration and Optimization for a Multi Rotor UAV

A Design Configuration and Optimization for a Multi Rotor UAV UNCLSSIFIED/UNLIITED Desgn Confguon n Opmzon fo ul oo UV Els Cpello, Gogo Gugle, Fulv Quglo olecnco Tono DIS Coso Duc egl buzz 4 9 Tono (Ily) els.cpello@polo. -fulv.quglo@polo. - gogo.gugle@polo. STCT

More information

INTERHARMONICS ANALYSIS OF A 7.5KW AIR COMPRESSOR MOTOR

INTERHARMONICS ANALYSIS OF A 7.5KW AIR COMPRESSOR MOTOR INTERHRMONIS NYSIS OF 7.5KW IR OMPRESSOR MOTOR M Zhyun Mo Wen Xong un e Xu Zhong Elecc Powe Te Elecc Powe Te Elecc Powe Te Elecc Powe Te & Reech Inue & Reech Inue & Reech Inue & Reech Inue of Gungzhou

More information

Parameter Estimation and Hypothesis Testing of Two Negative Binomial Distribution Population with Missing Data

Parameter Estimation and Hypothesis Testing of Two Negative Binomial Distribution Population with Missing Data Avlble ole wwwsceceeccom Physcs Poce 0 475 480 0 Ieol Cofeece o Mecl Physcs Bomecl ee Pmee smo Hyohess es of wo Neve Boml Dsbuo Poulo wh Mss D Zhwe Zho Collee of MhemcsJl Noml UvesyS Ch zhozhwe@6com Absc

More information

On Fractional Operational Calculus pertaining to the product of H- functions

On Fractional Operational Calculus pertaining to the product of H- functions nenonl eh ounl of Enneen n ehnolo RE e-ssn: 2395-56 Volume: 2 ue: 3 une-25 wwwene -SSN: 2395-72 On Fonl Oeonl Clulu enn o he ou of - funon D VBL Chu, C A 2 Demen of hem, Unve of Rhn, u-3255, n E-ml : vl@hooom

More information

Hidden Markov Model. a ij. Observation : O1,O2,... States in time : q1, q2,... All states : s1, s2,..., sn

Hidden Markov Model. a ij. Observation : O1,O2,... States in time : q1, q2,... All states : s1, s2,..., sn Hdden Mrkov Model S S servon : 2... Ses n me : 2... All ses : s s2... s 2 3 2 3 2 Hdden Mrkov Model Con d Dscree Mrkov Model 2 z k s s s s s s Degree Mrkov Model Hdden Mrkov Model Con d : rnson roly from

More information

s = rθ Chapter 10: Rotation 10.1: What is physics?

s = rθ Chapter 10: Rotation 10.1: What is physics? Chape : oaon Angula poson, velocy, acceleaon Consan angula acceleaon Angula and lnea quanes oaonal knec enegy oaonal nea Toque Newon s nd law o oaon Wok and oaonal knec enegy.: Wha s physcs? In pevous

More information

Handling Fuzzy Constraints in Flow Shop Problem

Handling Fuzzy Constraints in Flow Shop Problem Handlng Fuzzy Consans n Flow Shop Poblem Xueyan Song and Sanja Peovc School of Compue Scence & IT, Unvesy of Nongham, UK E-mal: {s sp}@cs.no.ac.uk Absac In hs pape, we pesen an appoach o deal wh fuzzy

More information

Homework 5 for BST 631: Statistical Theory I Solutions, 09/21/2006

Homework 5 for BST 631: Statistical Theory I Solutions, 09/21/2006 Homewok 5 fo BST 63: Sisicl Theoy I Soluions, 9//6 Due Time: 5:PM Thusy, on 9/8/6. Polem ( oins). Book olem.8. Soluion: E = x f ( x) = ( x) f ( x) + ( x ) f ( x) = xf ( x) + xf ( x) + f ( x) f ( x) Accoing

More information

New Stability Condition of T-S Fuzzy Systems and Design of Robust Flight Control Principle

New Stability Condition of T-S Fuzzy Systems and Design of Robust Flight Control Principle 96 JOURNAL O ELECRONIC SCIENCE AND ECHNOLOGY, VOL., NO., MARCH 3 New Sably Conon of -S uzzy Sysems an Desgn of Robus lgh Conol Pncple Chun-Nng Yang, Ya-Zhou Yue, an Hu L Absac Unlke he pevous eseach woks

More information

Chapter 6 Plane Motion of Rigid Bodies

Chapter 6 Plane Motion of Rigid Bodies Chpe 6 Pne oon of Rd ode 6. Equon of oon fo Rd bod. 6., 6., 6.3 Conde d bod ced upon b ee een foce,, 3,. We cn ume h he bod mde of e numbe n of pce of m Δm (,,, n). Conden f he moon of he m cene of he

More information

Uniform Circular Motion

Uniform Circular Motion Unfom Ccul Moton Unfom ccul Moton An object mong t constnt sped n ccle The ntude of the eloct emns constnt The decton of the eloct chnges contnuousl!!!! Snce cceleton s te of chnge of eloct:!! Δ Δt The

More information

Chapter 3: Vectors and Two-Dimensional Motion

Chapter 3: Vectors and Two-Dimensional Motion Chape 3: Vecos and Two-Dmensonal Moon Vecos: magnude and decon Negae o a eco: eese s decon Mulplng o ddng a eco b a scala Vecos n he same decon (eaed lke numbes) Geneal Veco Addon: Tangle mehod o addon

More information

MODEL SOLUTIONS TO IIT JEE ADVANCED 2014

MODEL SOLUTIONS TO IIT JEE ADVANCED 2014 MODEL SOLUTIONS TO IIT JEE ADVANCED Pper II Code PART I 6 7 8 9 B A A C D B D C C B 6 C B D D C A 7 8 9 C A B D. Rhc(Z ). Cu M. ZM Secon I K Z 8 Cu hc W mu hc 8 W + KE hc W + KE W + KE W + KE W + KE (KE

More information

Caputo Equations in the frame of fractional operators with Mittag-Leffler kernels

Caputo Equations in the frame of fractional operators with Mittag-Leffler kernels nvenon Jounl o Reseh Tehnoloy n nneen & Mnemen JRTM SSN: 455-689 wwwjemom Volume ssue 0 ǁ Ooe 08 ǁ PP 9-45 Cuo uons n he me o onl oeos wh M-ele enels on Qn Chenmn Hou* Ynn Unvesy Jln Ynj 00 ASTRACT: n

More information

Active Model Based Predictive Control for Unmanned Helicopter in Full Flight Envelope

Active Model Based Predictive Control for Unmanned Helicopter in Full Flight Envelope he 2 IEEE/RSJ Inernonl Conference on Inellgen Robos nd Sysems Ocober 8-22, 2, pe, wn Acve Model Bsed Predcve Conrol for Unmnned Helcoper n Full Flgh Envelope Dle Song, Junong Q, Jnd Hn, nd Gungjun Lu Absrc-

More information

The Shape of the Pair Distribution Function.

The Shape of the Pair Distribution Function. The Shpe of the P Dstbuton Functon. Vlentn Levshov nd.f. Thope Deptment of Phscs & stonom nd Cente fo Fundmentl tels Resech chgn Stte Unvest Sgnfcnt pogess n hgh-esoluton dffcton epements on powde smples

More information

Physics 207, Lecture 3

Physics 207, Lecture 3 Physcs 7 Lecue 3 Physcs 7, Lecue 3 l Tody (Fnsh Ch. & s Ch. 3) Emne sysems wh non-zeo cceleon (ofen consn) Sole D poblems wh zeo nd consn cceleon (ncludng fee-fll nd moon on n nclne) Use Cesn nd pol coodne

More information

PHYS 2421 Fields and Waves

PHYS 2421 Fields and Waves PHYS 242 Felds nd Wves Instucto: Joge A. López Offce: PSCI 29 A, Phone: 747-7528 Textook: Unvesty Physcs e, Young nd Feedmn 23. Electc potentl enegy 23.2 Electc potentl 23.3 Clcultng electc potentl 23.4

More information

Chapter I Vector Analysis

Chapter I Vector Analysis . Chpte I Vecto nlss . Vecto lgeb j It s well-nown tht n vecto cn be wtten s Vectos obe the followng lgebc ules: scl s ) ( j v v cos ) ( e Commuttv ) ( ssoctve C C ) ( ) ( v j ) ( ) ( ) ( ) ( (v) he lw

More information

Research Article Oscillatory Criteria for Higher Order Functional Differential Equations with Damping

Research Article Oscillatory Criteria for Higher Order Functional Differential Equations with Damping Journl of Funcon Spces nd Applcons Volume 2013, Arcle ID 968356, 5 pges hp://dx.do.org/10.1155/2013/968356 Reserch Arcle Oscllory Crer for Hgher Order Funconl Dfferenl Equons wh Dmpng Pegung Wng 1 nd H

More information

I-POLYA PROCESS AND APPLICATIONS Leda D. Minkova

I-POLYA PROCESS AND APPLICATIONS Leda D. Minkova The XIII Inenaonal Confeence Appled Sochasc Models and Daa Analyss (ASMDA-009) Jne 30-Jly 3, 009, Vlns, LITHUANIA ISBN 978-9955-8-463-5 L Sakalaskas, C Skadas and E K Zavadskas (Eds): ASMDA-009 Seleced

More information

II The Z Transform. Topics to be covered. 1. Introduction. 2. The Z transform. 3. Z transforms of elementary functions

II The Z Transform. Topics to be covered. 1. Introduction. 2. The Z transform. 3. Z transforms of elementary functions II The Z Trnsfor Tocs o e covered. Inroducon. The Z rnsfor 3. Z rnsfors of eleenry funcons 4. Proeres nd Theory of rnsfor 5. The nverse rnsfor 6. Z rnsfor for solvng dfference equons II. Inroducon The

More information

Hidden Markov Models

Hidden Markov Models Hdden Mkov Model Ronld J. Wllm CSG220 Spng 2007 Conn evel lde dped fom n Andew Mooe uol on h opc nd few fgue fom Ruell & ovg AIMA e nd Alpydn Inoducon o Mchne Lenng e. A Smple Mkov Chn /2 /3 /3 /3 3 2

More information

114 Consulting Group. Inc.

114 Consulting Group. Inc. 0 4 Consulng Goup. nc. ENGNEERS PLANNER S DESGNERS Memondum SAF No. 06937 To: Fom: Pul Oehme, PE Publc Woks Deco/ Cy Engnee Cy of Chnhssen M Pcyn, PE, Seno Assoce Tom Sch, ET, Engnee De: Sepembe 5, 206

More information

Physics 201, Lecture 5

Physics 201, Lecture 5 Phsics 1 Lecue 5 Tod s Topics n Moion in D (Chp 4.1-4.3): n D Kinemicl Quniies (sec. 4.1) n D Kinemics wih Consn Acceleion (sec. 4.) n D Pojecile (Sec 4.3) n Epeced fom Peiew: n Displcemen eloci cceleion

More information

Mapping task graphs to the CELL BE processor

Mapping task graphs to the CELL BE processor Mppng s gps o e CELL BE pocesso Mno uggeo mno.uggeo@unbo. Luc Benn luc.benn@unbo. Unvesy of Bologn Ily Oulne Inoducon Tge H cecue Tge Applcon & Modelng Ou ppoc Exmenl esuls esouce Mngemen on Mul Pocesso

More information

D zone schemes

D zone schemes Ch. 5. Enegy Bnds in Cysls 5.. -D zone schemes Fee elecons E k m h Fee elecons in cysl sinα P + cosα cosk α cos α cos k cos( k + π n α k + πn mv ob P 0 h cos α cos k n α k + π m h k E Enegy is peiodic

More information

() t. () t r () t or v. ( t) () () ( ) = ( ) or ( ) () () () t or dv () () Section 10.4 Motion in Space: Velocity and Acceleration

() t. () t r () t or v. ( t) () () ( ) = ( ) or ( ) () () () t or dv () () Section 10.4 Motion in Space: Velocity and Acceleration Secion 1.4 Moion in Spce: Velociy nd Acceleion We e going o dive lile deepe ino somehing we ve ledy inoduced, nmely () nd (). Discuss wih you neighbo he elionships beween posiion, velociy nd cceleion you

More information

( ) ( ) ( ) ( ) ( ) ( ) j ( ) A. b) Theorem

( ) ( ) ( ) ( ) ( ) ( ) j ( ) A. b) Theorem b) Theoe The u of he eco pojecon of eco n ll uull pependcul (n he ene of he cl poduc) decon equl o he eco. ( ) n e e o The pojecon conue he eco coponen of he eco. poof. n e ( ) ( ) ( ) e e e e e e e e

More information

4.8 Improper Integrals

4.8 Improper Integrals 4.8 Improper Inegrls Well you ve mde i hrough ll he inegrion echniques. Congrs! Unforunely for us, we sill need o cover one more inegrl. They re clled Improper Inegrls. A his poin, we ve only del wih inegrls

More information

L4:4. motion from the accelerometer. to recover the simple flutter. Later, we will work out how. readings L4:3

L4:4. motion from the accelerometer. to recover the simple flutter. Later, we will work out how. readings L4:3 elave moon L4:1 To appl Newon's laws we need measuemens made fom a 'fed,' neal efeence fame (unacceleaed, non-oang) n man applcaons, measuemens ae made moe smpl fom movng efeence fames We hen need a wa

More information

Mechanics Physics 151

Mechanics Physics 151 Mechancs Physcs 5 Lecure 0 Canoncal Transformaons (Chaper 9) Wha We Dd Las Tme Hamlon s Prncple n he Hamlonan formalsm Dervaon was smple δi δ Addonal end-pon consrans pq H( q, p, ) d 0 δ q ( ) δq ( ) δ

More information

Hamiltonian Representation of Higher Order Partial Differential Equations with Boundary Energy Flows

Hamiltonian Representation of Higher Order Partial Differential Equations with Boundary Energy Flows ounl of Aled Mhemcs nd Physcs 05 3 47-490 Publshed Onlne Novembe 05 n ScRes. h://www.sc.og/jounl/jm h://dx.do.og/0.436/jm.05.374 Hmlonn Reesenon of Hghe Ode Pl Dffeenl Euons wh Boundy Enegy Flows Gou Nshd

More information

THIS PAGE DECLASSIFIED IAW EO IRIS u blic Record. Key I fo mation. Ma n: AIR MATERIEL COMM ND. Adm ni trative Mar ings.

THIS PAGE DECLASSIFIED IAW EO IRIS u blic Record. Key I fo mation. Ma n: AIR MATERIEL COMM ND. Adm ni trative Mar ings. T H S PA G E D E CLA SSFED AW E O 2958 RS u blc Recod Key fo maon Ma n AR MATEREL COMM ND D cumen Type Call N u b e 03 V 7 Rcvd Rel 98 / 0 ndexe D 38 Eneed Dae RS l umbe 0 0 4 2 3 5 6 C D QC d Dac A cesson

More information

Electric Potential. and Equipotentials

Electric Potential. and Equipotentials Electic Potentil nd Euipotentils U Electicl Potentil Review: W wok done y foce in going fom to long pth. l d E dl F W dl F θ Δ l d E W U U U Δ Δ l d E W U U U U potentil enegy electic potentil Potentil

More information

The Characterization of Jones Polynomial. for Some Knots

The Characterization of Jones Polynomial. for Some Knots Inernon Mhemc Forum,, 8, no, 9 - The Chrceron of Jones Poynom for Some Knos Mur Cncn Yuuncu Y Ünversy, Fcuy of rs nd Scences Mhemcs Deprmen, 8, n, Turkey m_cencen@yhoocom İsm Yr Non Educon Mnsry, 8, n,

More information

STRAIGHT LINES IN LINEAR ARRAY SCANNER IMAGERY

STRAIGHT LINES IN LINEAR ARRAY SCANNER IMAGERY Devn Kelle STRIGHT LINES IN LINER RR SCNNER IMGER mn Hbb, Devn Kelle, ndne smmw Depmen of Cvl nd Envonmenl Engneeng nd Geode Sene The ho Se Unves hbb.1@osu.edu, kelle.83@osu.edu, smmw.1@osu.edu ISPRS Commsson

More information

2/20/2013. EE 101 Midterm 2 Review

2/20/2013. EE 101 Midterm 2 Review //3 EE Mderm eew //3 Volage-mplfer Model The npu ressance s he equalen ressance see when lookng no he npu ermnals of he amplfer. o s he oupu ressance. I causes he oupu olage o decrease as he load ressance

More information

Faraday s Law. To be able to find. motional emf transformer and motional emf. Motional emf

Faraday s Law. To be able to find. motional emf transformer and motional emf. Motional emf Objecie F s w Tnsfome Moionl To be ble o fin nsfome. moionl nsfome n moionl. 331 1 331 Mwell s quion: ic Fiel D: Guss lw :KV : Guss lw H: Ampee s w Poin Fom Inegl Fom D D Q sufce loop H sufce H I enclose

More information

STABILITY CRITERIA FOR A CLASS OF NEUTRAL SYSTEMS VIA THE LMI APPROACH

STABILITY CRITERIA FOR A CLASS OF NEUTRAL SYSTEMS VIA THE LMI APPROACH Asan Jounal of Conol, Vol. 6, No., pp. 3-9, Mach 00 3 Bef Pape SABILIY CRIERIA FOR A CLASS OF NEURAL SYSEMS VIA HE LMI APPROACH Chang-Hua Len and Jen-De Chen ABSRAC In hs pape, he asypoc sably fo a class

More information

Lecture 5. Plane Wave Reflection and Transmission

Lecture 5. Plane Wave Reflection and Transmission Lecue 5 Plane Wave Reflecon and Tansmsson Incden wave: 1z E ( z) xˆ E (0) e 1 H ( z) yˆ E (0) e 1 Nomal Incdence (Revew) z 1 (,, ) E H S y (,, ) 1 1 1 Refleced wave: 1z E ( z) xˆ E E (0) e S H 1 1z H (

More information

An Optimal Calibration Method for a MEMS Inertial Measurement Unit

An Optimal Calibration Method for a MEMS Inertial Measurement Unit Inenonl Jounl of Advnced Rooc Ssems ARTICLE An Opml Clon Mehod fo MEMS Inel Mesuemen Un Reul Ppe Bn Fn,,*, Wushen Chou, nd L Dn Se Ke Loo of Vul Rel Technolo nd Ssems, Behn Unves, P.R. Chn Roocs Insue

More information

DESIGN OF A SPLIT HOPKINSON PRESSURE BAR

DESIGN OF A SPLIT HOPKINSON PRESSURE BAR DESGN OF A SPT HOPKNSON PESSUE BA Felpe Glln Goup of Sold Mechnc nd Sucul mpc Unvey of São Pulo São Pulo SP - Bzl felpe.glln@pol.up..s. Bch mpc eech Cene Unvey of vepool UK 123@lv.c.uk Mcílo Alve Goup

More information

Suppose we have observed values t 1, t 2, t n of a random variable T.

Suppose we have observed values t 1, t 2, t n of a random variable T. Sppose we have obseved vales, 2, of a adom vaable T. The dsbo of T s ow o belog o a cea ype (e.g., expoeal, omal, ec.) b he veco θ ( θ, θ2, θp ) of ow paamees assocaed wh s ow (whee p s he mbe of ow paamees).

More information

Discrete Model Parametrization

Discrete Model Parametrization Poceedings of Intentionl cientific Confeence of FME ession 4: Automtion Contol nd Applied Infomtics Ppe 9 Discete Model Pmetition NOKIEVIČ, Pet Doc,Ing,Cc Deptment of Contol ystems nd Instumenttion, Fculty

More information

MCTDH Approach to Strong Field Dynamics

MCTDH Approach to Strong Field Dynamics MCTDH ppoach o Song Feld Dynamcs Suen Sukasyan Thomas Babec and Msha Ivanov Unvesy o Oawa Canada Impeal College ondon UK KITP Sana Babaa. May 8 009 Movaon Song eld dynamcs Role o elecon coelaon Tunnel

More information

Energy Dissipation Gravitational Potential Energy Power

Energy Dissipation Gravitational Potential Energy Power Lectue 4 Chpte 8 Physics I 0.8.03 negy Dissiption Gvittionl Potentil negy Powe Couse wesite: http://fculty.uml.edu/andiy_dnylov/teching/physicsi Lectue Cptue: http://echo360.uml.edu/dnylov03/physicsfll.html

More information

Today - Lecture 13. Today s lecture continue with rotations, torque, Note that chapters 11, 12, 13 all involve rotations

Today - Lecture 13. Today s lecture continue with rotations, torque, Note that chapters 11, 12, 13 all involve rotations Today - Lecue 13 Today s lecue coninue wih oaions, oque, Noe ha chapes 11, 1, 13 all inole oaions slide 1 eiew Roaions Chapes 11 & 1 Viewed fom aboe (+z) Roaional, o angula elociy, gies angenial elociy

More information

Variants of Pegasos. December 11, 2009

Variants of Pegasos. December 11, 2009 Inroducon Varans of Pegasos SooWoong Ryu bshboy@sanford.edu December, 009 Youngsoo Cho yc344@sanford.edu Developng a new SVM algorhm s ongong research opc. Among many exng SVM algorhms, we wll focus on

More information

Online Supplement for Dynamic Multi-Technology. Production-Inventory Problem with Emissions Trading

Online Supplement for Dynamic Multi-Technology. Production-Inventory Problem with Emissions Trading Onlne Supplemen for Dynamc Mul-Technology Producon-Invenory Problem wh Emssons Tradng by We Zhang Zhongsheng Hua Yu Xa and Baofeng Huo Proof of Lemma For any ( qr ) Θ s easy o verfy ha he lnear programmng

More information

USING LOWER CLASS WEIGHTS TO CORRECT AND CHECK THE NONLINEARITY OF BALANCES

USING LOWER CLASS WEIGHTS TO CORRECT AND CHECK THE NONLINEARITY OF BALANCES USING OWER CSS WEIGHTS TO CORRECT ND CHECK THE NONINERITY OF BNCES Tiohy Chnglin Wng, Qiho Yun, hu Reichuh Mele-Toledo Insuens Shnghi Co. d, Shnghi, P R Chin Mele-Toledo GH, Geifensee, Swizelnd BSTRCT

More information

Outline. GW approximation. Electrons in solids. The Green Function. Total energy---well solved Single particle excitation---under developing

Outline. GW approximation. Electrons in solids. The Green Function. Total energy---well solved Single particle excitation---under developing Peenaon fo Theoecal Condened Mae Phyc n TU Beln Geen-Funcon and GW appoxmaon Xnzheng L Theoy Depamen FHI May.8h 2005 Elecon n old Oulne Toal enegy---well olved Sngle pacle excaon---unde developng The Geen

More information

N 1. Time points are determined by the

N 1. Time points are determined by the upplemena Mehods Geneaon of scan sgnals In hs secon we descbe n deal how scan sgnals fo 3D scannng wee geneaed. can geneaon was done n hee seps: Fs, he dve sgnal fo he peo-focusng elemen was geneaed o

More information

Chapter 6: AC Circuits

Chapter 6: AC Circuits Chaper 6: AC Crcus Chaper 6: Oulne Phasors and he AC Seady Sae AC Crcus A sable, lnear crcu operang n he seady sae wh snusodal excaon (.e., snusodal seady sae. Complee response forced response naural response.

More information

e t dt e t dt = lim e t dt T (1 e T ) = 1

e t dt e t dt = lim e t dt T (1 e T ) = 1 Improper Inegrls There re wo ypes of improper inegrls - hose wih infinie limis of inegrion, nd hose wih inegrnds h pproch some poin wihin he limis of inegrion. Firs we will consider inegrls wih infinie

More information

Radial geodesics in Schwarzschild spacetime

Radial geodesics in Schwarzschild spacetime Rdil geodesics in Schwzschild spcetime Spheiclly symmetic solutions to the Einstein eqution tke the fom ds dt d dθ sin θdϕ whee is constnt. We lso hve the connection components, which now tke the fom using

More information

Cubic Bezier Homotopy Function for Solving Exponential Equations

Cubic Bezier Homotopy Function for Solving Exponential Equations Penerb Journal of Advanced Research n Compung and Applcaons ISSN (onlne: 46-97 Vol. 4, No.. Pages -8, 6 omoopy Funcon for Solvng Eponenal Equaons S. S. Raml *,,. Mohamad Nor,a, N. S. Saharzan,b and M.

More information

CptS 570 Machine Learning School of EECS Washington State University. CptS Machine Learning 1

CptS 570 Machine Learning School of EECS Washington State University. CptS Machine Learning 1 ps 57 Machne Leann School of EES Washnon Sae Unves ps 57 - Machne Leann Assume nsances of classes ae lneal sepaable Esmae paamees of lnea dscmnan If ( - -) > hen + Else - ps 57 - Machne Leann lassfcaon

More information

Answers to test yourself questions

Answers to test yourself questions Answes to test youself questions opic Descibing fields Gm Gm Gm Gm he net field t is: g ( d / ) ( 4d / ) d d Gm Gm Gm Gm Gm Gm b he net potentil t is: V d / 4d / d 4d d d V e 4 7 9 49 J kg 7 7 Gm d b E

More information

CH.3. COMPATIBILITY EQUATIONS. Continuum Mechanics Course (MMC) - ETSECCPB - UPC

CH.3. COMPATIBILITY EQUATIONS. Continuum Mechanics Course (MMC) - ETSECCPB - UPC CH.3. COMPATIBILITY EQUATIONS Connuum Mechancs Course (MMC) - ETSECCPB - UPC Overvew Compably Condons Compably Equaons of a Poenal Vecor Feld Compably Condons for Infnesmal Srans Inegraon of he Infnesmal

More information

Fault Detection and Classification Using Kalman Filter and Genetic Neuro-Fuzzy Systems

Fault Detection and Classification Using Kalman Filter and Genetic Neuro-Fuzzy Systems Fl Deecon nd Clssfcon Usng Klmn Fle nd Genec Neo-Fzzy Sysems Hs M. Khld Sysems Engg. Depmen K.F.U.P.M Dhhn, Sd Ab Eml: mhskh@kfpm.ed.s Am Khokh Sysems Engg. Depmen K.F.U.P.M Dhhn, Sd Ab Eml: m@kfpm.ed.s

More information

UNIT10 PLANE OF REGRESSION

UNIT10 PLANE OF REGRESSION UIT0 PLAE OF REGRESSIO Plane of Regesson Stuctue 0. Intoducton Ojectves 0. Yule s otaton 0. Plane of Regesson fo thee Vaales 0.4 Popetes of Resduals 0.5 Vaance of the Resduals 0.6 Summay 0.7 Solutons /

More information