Italo A. Souza-D-Assis, Rnan Olivia, Maclo A. C. Fnans Sp Fuzzy Contol Appli to Autonomous Elctic Vhicls ÍTALO A. SOUZA-DE-ASSIS, RENAN OLIVEIRA, MARCELO A. C. FERNANDES Fal Univsity of Rio Gan o Not (UFRN) Dpatmnt of Comput Engining an Automation (DCA) 5978-97, Natal, RN BRAZIL Cosponing autho: mfnans@ca.ufn.b Abstact: A cuis contol systm fo autonomous lctic vhicls (AEVs) is psnt, bas on fuzzy logic. Th popos tchniqu uss th fuzzy systms that act in paalll uing th kintic stats of th vhicl: acclation, moving, an baking. Valiation of th pocu us longituinal simulations of a vhicl pow by a pmannt magnt ict cunt moto. Th sults inicat that th contol systm pfom satisfactoily, an coul b us in AEV applications. Ky Wos:Fuzzy Logic, Autonomous Elctic Vhicl, Cuis Contol Intouction Rsach has shown that th pfomanc achiv using intllignt contolls xcs that of taitional contolls. Contol algoithms bas on atificial nual ntwoks (ANNs) an/o fuzzy logic off substantial gains ov convntional tchniqus such as th PID [, 2], as a sult of which th is incasing intst in th vlopmnt of intllignt contol systms. In paticula, th is gowing commcial awanss of th possibl application of ths systms in autonomous vhicls, wh thy coul hlp to uc accints an impov th comfot of th occupants [3, 4]. A futh consiation lats to th capacity of highways, sinc with liabl snsos an automation, impovmnts coul b ma ov human action tims an saf istancs btwn vhicls coul b shotn [5]. An impotant point is that intllignt contol systms fo AEVs coul b apily implmnt without quiing majo invstmnts in infastuctu [6 9]. Pocsss bas on fuzzy logic a amongst th most fficint intllignt contol systms, nabling th api vlopmnt of contolls fo tmpoally vaiabl nonlina systms []. An impotant avantag of fuzzy contol is that th a many cass wh binay valus (tu o fals, connct o isconnct, tc.) a unabl to povi a goo sciption of th situation. Ths cass qui a scal whby th vaiabls can b assign intmiat valus []. This can b achiv using fuzzy logic in contolls [, 3]. Fuzzy contolls hav alay bn us fo sp contol of autonomous vhicls, an hav bn shown to povi pfomanc supio to that of convntional PID tchniqus, spcially concning os, vibation, an obustnss [4]. A fuzzy statgy was foun to off avantags ov a nuo-fuzzy appoach o PI contolls appli to autonomous vhicls [5]. Sval stuis hav scib th vlopmnt of autonomous vhicl sp contolls bas on fuzzy logic [6 9]. Th a two main poblms to b ass in th vlopmnt of autonomous vhicls: (i) lan kping, an (ii) longituinal haway [2]. Th latt has bn th subjct of sach fo at last 4 yas, an th a many thotical stuis pot in th litatu [2 24]. Th objctiv of th psnt wok was to sign a longituinal cuis contol systm fo AEVs, bas on fuzzy logic. Diffnt to th wok that has bn publish pviously, th popos systm uss th sts of fuzzy uls that act in paalll fo th kintic stats of th vhicl: acclation, moving, an baking. Th goal of th systm was to b abl to smoothly acclat th vhicl until it ach a ptmin cuising sp (th fnc sp) within a st tim (th fnc tim), an thn maintain this sp uing movmnt of th vhicl. Th fuzzy contoll shoul also b abl to uc th sp of th vhicl without any abupt changs, so that th vhicl halts at a ptmin istanc fom th stating point. This typ of systm coul b us in autonomous vhicls fo tanspotation of poucts snsitiv to abupt movmnts, wh th out is known in avanc, with pvious pogamming of acclation, cuis sp, an baking. E-ISSN: 2224-2856 64 Volum 9, 24
Dtails of th lctic vhicl mol us a povi in Sction 2. A sciption of th contol statgy us in ach stag of th vhicl kintics is givn in Sction 3. A sciption of th spcific chaactistics of th simulation is givn in Sction 4, incluing th out, th valus slct fo th iffnt paamts, an th sults obtain. Finally, an valuation of th popos schm an its pfomanc is povi in Sction 5. 2 Moling of th AEV Th lctic vhicl us in th simulations was psnt by a longituinal ynamics mol with a pmannt magnt ict cunt (PMDC) moto [25 27]. Th objctiv of th contoll was to ajust th voltag in o to maintain th sp of th vhicl within th givn spcifications. Th ynamics of th PMDC moto (Figu ) w mol by an quation psnting th lctical aspcts an anoth quation psnting th mchanical aspcts, as scib pviously [27]. Th iffntial quation us to mol th lctical pat can b scib by v a (t) = R a i a (t) + L a i a (t) t + v i (t), () wh v a (t), i a (t), R a an L a a th voltag in volts (V), th cunt in amps (A), th sistanc in ohms (Ω), an th inuctanc in hnys (H), spctivly, in th amatu of th PMDC moto, an v i (t) is th voltag inuc in th oto tminals (V). Th mchanical pat was mol using th xpssion J m ω m (t) t = τ m (t) B m ω m (t) τ c (t), (2) wh J m is th momnt of intia of th oto (Kg.m 2 ), B m is th viscosity constant (N.m.s), ω m (t) is th angula vlocity of th oto (a/s), τ m (t) is th toqu gnat by th moto (also known as th magntic toqu) (N.m), an τ c (t) is th toqu qui to mov th loa (N.m). In PMDC motos, th magntic toqu, τ m (t), is ictly popotional to th cunt in th amatu, i a (t), so that τ m (t) = K τ i a (t), (3) an th angula vlocity, ω m (t), is ictly popotional to th inuc voltag, v i (t), as scib by v i (t) = K ω ω m (t) (4) wh K τ is th toqu constant (N.m/A) an K ω is th vlocity constant (V/a/s) of th PMDC moto [27]. v a (t) Ra ia(t) La v i (t) ωm(t)jm τ v (t) τ m (t) τ c (t) Figu : Elctomchanical schmatic of th PMDC moto. Th longituinal vhicl mol, illustat in Figu 2, can b scib by th xpssion M x(t) t = f t (t) f a (t), (5) wh M is th mass of th vhicl (Kg), x(t) is th lina vlocity of th vhicl (m/s), f t (t) is th taction foc of th vhicl (N), an f a (t) is th fiction foc (N). Figu 2: mol. f(t) f (t) Italo A. Souza-D-Assis, Rnan Olivia, Maclo A. C. Fnans M x(t) f g (t) f g (t)sin(θ(t)) f t (t) θ(t) Schmatic of th longituinal vhicl Accoing to [25], th fiction foc, f a (t), can b xpss as f a (t) = f (t) + f (t) + f g (t) sin(θ(t)), (6) wh f (t) is th aoynamic fiction foc (N), f (t) is th olling sistanc foc (N), f g (t) is th gavitational foc (N), an θ(t) is th inclination angl of th plan on which th vhicl is locat. Th aoynamic fiction can b scib by f (t) = 2 ρc A f x 2 (t), (7) wh ρ is th nsity of ai, C is th aoynamic ag cofficint, an A f is th fontal aa of th vhicl (m 2 ). Th olling sistanc foc can b scib by f (t) = Mg ( C + C x 2 (t) ), (8) E-ISSN: 2224-2856 64 Volum 9, 24
wh C an C a th olling cofficints an g is th acclation u to gavity (m/s 2 ). Finally, th gavitational foc is givn by f g (t) = Mg. (9) Th coupling btwn th PMDC moto an th vhicl was mol by a simpl systm of gas position paalll to th a axl of th vhicl, scib by τ a (t) = kτ m (t), () wh k is th ga atio, an f a (t) = τ a(t) () wh is th aius of th whl of th vhicl (m). 3 Contol statgy Th popos contol statgy uss th fuzzy systms acting in paalll fo th kintic stats of th vhicl (acclation, moving, an baking). This ivision incass th pcision with which th sp of th AEV can b contoll, nabling smooth sponss uing acclation an baking as wll as a mo stabl sp uing moving. Th th systms a govn by a cision-making statgy that mploys two fnc paamts: t f, which tmins th acclation stat tim, an l f, which stablishs th istanc to th final stination in o to initiat th baking stat. In aition to this infomation, th contol statgy uss two aitional paamts, namly th istanc that th vhicl must cov to th final stination, l n, an th fnc sp, x f, which is th sp that th vhicl shoul ach at th n of th acclation stat an thn maintain uing th moving stat. A tail block iagam of th contol statgy is povi in Figu 3. Th fuzzy systm sponsibl fo th acclation stat, FS ( ), can b scib by v (t) = FS ( x (t)) (2) wh v (t) is th voltag (V) appli to th moto uing th acclation stat, an x (t) is th o btwn th fnc sp, x f, which is si at th n of th acclation stat, an th actual sp of th vhicl, scib by x (t) = x f x(t). (3) Th fuzzy systm associat with th moving stat, FS m ( ), is chaactiz by v m (t) = FS m ( x (t), x (t)), (4) wh v m (t) is th voltag (V) appli to th moto uing th moving stat, an x (t) is th ivativ of th o x (t). Finally, th fuzzy systm us to chaactiz th baking stat, FS b ( ), is scib by v b (t) = FS b ( x (t), l (t)), (5) wh v b (t) is th voltag (V) appli to th moto uing th baking stat, an l(t) is th istanc (m) tavll by th vhicl to th final stination. Th cision statgy us to slct on of th th systms (FS, FS m an FS b, scib by Eq. (2), Eq. (4), an Eq. (5), spctivly) is chaactiz by v (t) if t t f an l(t) < l n l f v a (t) = v m (t) if t > t f an l(t) < l n l f. v b (t) if t > t f an l(t) l n l f (6) Th input an output mmbship functions an th st of uls associat with ach of th th fuzzy systms a scib in tail in Sctions 3., 3.2 an 3.3. Thy a bas on a subjctiv analysis of th action of a human iv, with th aim of achiving smooth acclation an baking, as wll as a stabl sp in a longituinal out with anom ascnts an scnts. Th limits of th mmbship functions associat with th output vaiabls v (t), v m (t) an v b (t) w slct fo motos with a nominal amatu voltag, v nom a (t), of 22V. Howv, ths limits coul b asily ajust fo motos with oth valus of v nom a (t). 3. Fuzzy systm fo acclation Th fuzzy systm fo acclation, FS ( ), can b scib by th mmbship functions shown in Figus 4 an 5. Th input vaiabl, x (t), s psnt by a goup of svn linguistic vaiabls with tiangula an tapzoial mmbship functions, as illustat in Figu 4. In th cas of th output vaiabl, v (t), only th linguistic vaiabls with tiangula mmbship functions a us (Figu 5). Tabl tails th st of fuzzy uls us in th Mamani infnc pocss in o to lat th input vaiabl, x (t), with th output vaiabl, v (t). Sinc th objctiv of th FS ( ) systm is to achiv smooth acclation, th mmbship functions of th output vaiabl, v (t), a slightly abov th nominal avag amatu voltag of th vhicl, (t), which in th psnt cas is 22V. This statgy nabls th moto voltag uing acclation to b limit to th ang v nom a Italo A. Souza-D-Assis, Rnan Olivia, Maclo A. C. Fnans v min (t) v (t) v max (t) (7) E-ISSN: 2224-2856 642 Volum 9, 24
Italo A. Souza-D-Assis, Rnan Olivia, Maclo A. C. Fnans x f x(t) + - Contol statgy v (t) FS v m (t) x/t FS m v b (t) FS b t f l n l f Dcision statgy v a(t) PMDC Moto EV τ a (t) Vhicl x(t) l(t) Figu 3: Stuctu of th lctic vhicl contol statgy. ip.8 s h b m.6 m f.4 o g.2 GN MN PN Z PP MP GP -5-4 -3-2 - 2 3 4 5 x(t) Figu 4: Mmbship functions of x (t) fo th acclation stat. wh v min (t) an v max (t) a th low an upp limits, spctivly, of th acclation voltag. Th valu of th upp limit must b small than th nominal voltag of th moto (v max (t) < v nom a (t)), t f must b small than th stabilization tim of th systm in opn loop, t st, (t f < t st ) x f must b small than th valu of th spons of th systm, x(t), in opn loop, fo an input stp with a valu of v min (t). Ths th stictions nsu th succss of th acclation stat, avoiing any abupt changs in sp. Figu 6 llustats th lation btwn th input, x (t), an th output, v (t), sulting fom th ul bas (Tabl ) of th mmbship functions psnt in Figus 4 an 5. This cuv was obtain using th minimum in th implication stp, th maximum in th agggation stp, an th cntoi mtho in th fuzzification stp. It can b sn fom Figu 6 that v min (t) = 24 V an that v max (t) = 35 V. 3.2 Fuzzy systm fo moving In th cas of th moving stat, th fuzzy systm, FS m ( ), uss th mmbship functions shown in Figus 7, 8 an 9, togth with th st of uls givn in Tabl 2. Figus 7 an 8 illustat th mmbship functions utiliz fo fuzzification of th input vaiabls x (t) an x (t), spctivly. Fo both input vaiabls, svn mmbship functions w cat (tapzoial in th xtms an tiangula in th main). Fo th output vaiabl, v m (t), svn mmbship functions w cat that w also tapzoial in th xtms an tiangula in th main, as shown in Figu 9. It is impotant to not that th output vaiabl, v m (t), os not hav ngativ valus, hnc avoiing any abupt acclation (in outs with scnts) o clation (in outs with ascnts) u to changs in th iction of th moto. Tabl 2 givs th st of fuzzy uls us in th Mamani infnc pocss in o to lat th input vaiabls, x (t) an x (t), to th output vaiabl, v m (t). Figu shows th lation btwn th inputs, x (t) an x (t), an th output, v (t), sulting fom th ul bas (Tabl 2) fo th mmbship functions shown in Figus 7, 8 an 9. This cuv was obtain using th minimum in th implication stp, th maximum in th agggation stp, an th cntoi mtho in th fuzzification stp. E-ISSN: 2224-2856 643 Volum 9, 24
Italo A. Souza-D-Assis, Rnan Olivia, Maclo A. C. Fnans ip.8 s h b m.6 m f o.4 g.2 D PM M MM 2 3 4 5 6 7 8 v (t) Figu 5: Mmbship functions of v (t) fo th acclation stat of a 22V PMDC moto. Tabl : St of fuzzy systm uls fo th acclation stat, FS ( ). x (t) GN MN PN Z PP MP GP PM PM PM PM PM M MM 3.3 Fuzzy systm fo baking Th fuzzy systm fo baking, FS b ( ), consists of th mmbship functions shown in Figus, 2 an 3, togth with th st of uls givn in Tabl 3. Th input vaiabl, x (t), uss th sam schm scib fo th oth fuzzy systms (FS an FS m ), with svn tapzoial mmbship functions in th xtms an tiangula functions in th main. Th input vaiabl, l(t), (Figu 2) is compos of only two tapzoial mmbship functions, psnting th conitions na an fa. Pio to th fuzzification pocss, th valus of l(t) a nomaliz using th xpssion l N (t) = l(t) l n + l f l f, (8) wh l N (t) is th nomaliz valu of l(t) anging btwn an. Th output vaiabl, v b (t), consists of thitn tapzoial an tiangula mmbship functions, as shown in Figu 3. In this cas, th intntion is to povi gat ganulaity in th baking pocss an nsu smooth clation. Tabl 3 povis tails of th st of fuzzy uls utiliz in th Mamani infnc pocss in o to lat th input vaiabls, x (t) an l N (t), with th output vaiabl, v b (t). Figu 4 illustats th lation btwn th inputs, x (t) an l N (t), an th output, v b (t), sulting fom th ul bas (Tabl 3) fo th mmbship functions shown in Figus, 2 an 3. This cuv was obtain using th minimum in th implication stp, th maximum in th agggation stp, an th cntoi mtho in th fuzzification stp. 4 Simulations an sults Valiation of th popos systm mploy simulations using th moto/gaing/vhicl mol (accoing to th quations psnt in Sction 2). Th valus of th paamts of th PMDC moto an th vhicl a givn in Tabls 4 an 5, spctivly. Ths valus a bas on pvious fil tsts of lctic vhicls pow by PMDC motos [26, 28]. Tabl 4: Paamts of th PMDC moto. Paamt Valu Amatu sistanc (R a ). Ω Coil inuctanc (L a ) 3 H Nominal amatu voltag 22 V (v nom a (t)) Momnt of intia (J m ).7 Kg.m 2 Cofficint of viscosity (B m ).8 N.m.s Toqu constant (K τ ).6 N.m/A Rat constant (K ω ).6 V/a/s Initial otation pm Th simulations pfom using th paamts list in Tabls 4 an 5 show that th stabilization tim of th systm in opn loop, t st, was aoun 9 s, an that th spons of th systm fo an input lvl of v min (t) = 24 V was appoximatly 5.6 Km/h. Hnc, givn th stictions psnt in Sction 3., x f was lss than 5.6 Km/h an t f was lss than 9 s. Tabl 6 lists th valus of th contol statgy paamts us in th simulation. Fo th acclation stp, th valus of t f an x f w slct to giv a longituinal acclation E-ISSN: 2224-2856 644 Volum 9, 24
Italo A. Souza-D-Assis, Rnan Olivia, Maclo A. C. Fnans 36 34 32 3 ) t ( v 28 26 24 22-5 -4-3 -2-2 3 4 5 x(t) Figu 6: Rlation btwn input an output fo th ul bas us in th acclation stp ( x (t) v (t)). GN MN PN Z PP MP GP Dg of mmbship.8.6.4.2 2 5 5 5 5 2 x(t) Figu 7: Mmbship function of th x (t) vaiabl uing th moving stat. Tabl 5: Paamts of th vhicl. Paamt Valu Mass of th vhicl (M) 5 Kg Ai nsity (ρ).8 Cofficint of aoynamic ag.5 (C ) Fontal aa (A f ) 2.4 m 2 Rolling sistanc cofficint.5 (C ) Rolling sistanc cofficint (C ) Acclation of gavity (g) 9.8 m/s 2 Whl aius ().26 m of aoun 2 m/s 2, which is consi to b comfotabl [29, 3]. In o to analyz th pfomanc of th contol statgy un avs conitions, th simulation involv a longituinal Km out with sval changs in gaint (Figu 5). Th vhicl ncount two positiv inclins of an 5 gs, initiat at an 2.5 Km, spctivly, on ngativ Tabl 6: Contol statgy paamts us in th simulation. Paamt Valu Tim in acclating stat (t f ) 7 s Rfnc sp (x f ) 5 Km/h Tavl istanc (l n ) Km Distanc to th final stination, to stat th baking stat (l f ) 25 m inclin of gs, initiat at 5 Km, an fou flat gions. Th baking stat was configu to bgin at 25 m fom th final aival point, at 9.975 Km. Th contol statgy was implmnt in a isct mann, with a sampling at of ms, an th ivativ of th o, x (t), was stimat by iffnc. Th simulation sults obtain using th slct paamt valus a shown in Figus 6, 7 an 8. Figu 6 shows th sp of th vhicl uing th acclation stat, which poc smoothly up to th fnc sp (x f = 5 Km/h) in th fnc tim (t f = 7 s). E-ISSN: 2224-2856 645 Volum 9, 24
Italo A. Souza-D-Assis, Rnan Olivia, Maclo A. C. Fnans Dg of mmbship.8.6.4.2 GN MN PN Z PP MP GP 2.5.5.5.5 2 x(t) Figu 8: Mmbship function of th x (t) vaiabl uing th moving stat. ip s h.8 b m.6 m f.4 o.2 g D FoN MN FN Z FP MP FoP 2 4 6 8 2 4 6 8 2 22 vm(t) Figu 9: Mmbship function of th v m (t) vaiabl uing th moving stat fo 22V PMDC motos. Figu 7 shows th sp of th vhicl uing th moving stat. It can b sn that th sp main clos to th fnc sp (x f ), vn uing changs in gaint. Th o was appoximatly.2% (x(t) = 5.6 km/h) fo th flat gions, 2.2% (x(t) = 5. km/h) fo th gs ngativ inclin, an.4% (x(t) = 49.3 km/h) an 2.7% (x(t) = 48.64 km/h) fo th an 5 gs positiv inclins, spctivly. Th contol statgy thfo function ffctivly uing th moving stat, with vy small changs in sp thoughout th out. Finally, Figu 8 shows th simulation sults obtain fo th sp of th vhicl uing th baking stat. Th vhicl clat smoothly until it ach a complt halt. Th baking tim was aoun 8 s, an th avag clation was appoximatly.74 m/s 2, which is a saf an comfotabl valu fo passngs an fagil itms [29, 3]. 5 Conclusions A cuis contol statgy fo autonomous lctic vhicls was vlop bas on th fuzzy systms acting in paalll fo th kintic stats of th vhicl (acclation, moving, an baking). Th tchniqu offs gat pcision than oth systms scib in th litatu, an can b customiz fo iffnt kintic stats, hnc offing a way of impoving th lvls of comfot an safty fo occupants an fagil objcts within th vhicl. Th statgy was valiat by simulation of a longituinal vhicl pow by a pmannt magnt DC moto. Th sults confim that th systm compli with th configu fnc citia, nabling fficint sp contol an smooth acclation an baking. This contol tchniqu thfo has potntial fo us in pactical applications. Rfncs: [] Z. Kovacic an S. Bogan, Fuzzy Contoll Dsign: Thoy an Applications. Automation an Contol Engining, Taylo & Fancis, 25. [2] S. Haykin, Nual Ntwoks an Laning Machins. No. v. in Nual ntwoks an laning machins, Pntic Hall, 29. [3] J. Pz, A. Gajat, V. Milans, E. Oniva, an M. Santos, Dsign an implmntation of a nuo-fuzzy systm fo longituinal contol of autonomous vhicls, in Fuzzy Systms (FUZZ), 2 IEEE Intnational Confnc on, pp. 6, 2. E-ISSN: 2224-2856 646 Volum 9, 24
Italo A. Souza-D-Assis, Rnan Olivia, Maclo A. C. Fnans Tabl 2: St of fuzzy systm uls fo th moving stat, FS m ( ). x (t) GN MN PN Z PP MP GP x (t) GN FoN FoN FoN FoN MN FN Z MN FoN FoN FoN MN FN Z FP PN FoN FoN MN FN Z FP MP Z FoN MN FN Z FP MP FoP PP MN FN Z FP MP FoP FoP MP FN Z FP MP FoP FoP FoP GP Z FP MP Fop Fop FoP FoP 5 vm(t) 5 2 x (t) 2 5 x(t) 5 Figu : Rlation btwn th inputs an output fo th ul bas us fo th moving stat, ( x (t), x (t) v m (t)). [4] L. Cai, A. Ra, an W.-L. Chan, An intllignt longituinal contoll fo application in smiautonomous vhicls, Inustial Elctonics, IEEE Tansactions on, vol. 57, no. 4, pp. 487 497, 2. [5] P. Ioannou an C. Chin, Autonomous intllignt cuis contol, Vhicula Tchnology, IEEE Tansactions on, vol. 42, no. 4, pp. 657 672, 993. [6] K. S. Chang an J. S. Choi, Automatic vhicl following using th fuzzy logic, in Vhicl Navigation an Infomation Systms Confnc, 995. Pocings. In conjunction with th Pacific Rim TansTch Confnc. 6th Intnational VNIS. A Ri into th Futu, pp. 26 23, 995. [7] R. Vma, D. Dl Vcchio, an H. Fathy, Dvlopmnt of a scal vhicl with longituinal ynamics of an hmmwv fo an its tstb, Mchatonics, IEEE/ASME Tansactions on, vol. 3, no., pp. 46 57, 28. [8] L. Cai, A. Ra, W. L. Chan, an M. L. Ho, A nual-fuzzy contoll fo intllignt cuis contol of vhicl in highways, in Intllignt Tanspotation Systms, 23. Pocings. 23 IEEE, vol. 2, pp. 389 393 vol.2, 23. [9] K. E. Majoub, F. Gii, H. Ouai, L. Duga, an F. Chaoui, Vhicl longituinal motion moling fo nonlina contol, Contol Engining Pactic, vol. 2, no., pp. 69 8, 22. [] P. Khatun, C. Bingham, N. Schofil, an P. Mllo, Application of fuzzy contol algoithms fo lctic vhicl antilock baking/taction contol systms, Vhicula Tchnology, IEEE Tansactions on, vol. 52, no. 5, pp. 356 364, 23. [] S. Saagioto an W. Pia, Lógica fuzzy aplicaa ao contolao vlocia uma linha montagm ixos vículos, in Simpósio Exclência m Gstão Tcnologia, 22. [2] A. Nasi, A. Hazzab, I. Bousshan, S. Haji, an P. Sica, Fuzzy-sliing mo sp E-ISSN: 2224-2856 647 Volum 9, 24
Italo A. Souza-D-Assis, Rnan Olivia, Maclo A. C. Fnans GN MN PN Z PP MP GP Dg of mmbship.8.6.4.2-5 -4-3 -2-2 3 4 5 x(t) Figu : Mmbship function of th x (t) vaiabl uing th baking stat. Dg of mmbship.8.6.4.2 Fa Na.2.4.6.8 l N (t) Figu 2: Mmbship function of th l N (t) vaiabl uing th baking stat. contol fo two whls lctic vhicl iv, Jounal of Elctical Engining & Tchnology, vol. 4, pp. 499 59, 2. [3] C. Han, J. Sul, S. Kim, Y. Lim, an J. L, Dvlopmnt of intllignt cuis contol systm, in Fuzzy Systms Confnc Pocings, 999. FUZZ-IEEE 99. 999 IEEE Intnational, vol., pp. 44 443 vol., 999. [4] K. R. S. Koagoa, W. Wijsoma, an E. Toh, Fuzzy sp an sting contol of an agv, Contol Systms Tchnology, IEEE Tansactions on, vol., no., pp. 2 2, 22. [5] V. Milans, J. Villaga, J. Pz, an C. Gonzalz, Low-sp longituinal contolls fo mass-pouc cas: A compaativ stuy, Inustial Elctonics, IEEE Tansactions on, vol. 59, no., pp. 62 628, 22. [6] H. Takahashi, Automatic sp contol vic using slf-tuning fuzzy logic, in Automotiv Applications of Elctonics, 988., IEEE Wokshop on, pp. 65 7, 988. [7] Z. Zalila an P. Lzy, Longituinal contol of an autonomous vhicl though a hybi fuzzy/classical contoll, in WESCON/94. Ia/Micolctonics. Confnc Rco, pp. 8 24, 994. [8] R. Holv, P. Potzl, an K. Naab, Gnating fuzzy uls fo th acclation contol of an aaptiv cuis contol systm, in Fuzzy Infomation Pocssing Socity, 996. NAFIPS., 996 Binnial Confnc of th Noth Amican, pp. 45 455, 996. [9] J. Aoyab, G. Aangun, L. Nozal, an J. Matin, Autonomous vhicl guianc with fuzzy algoithm, in Inustial Elctonics Socity, 2. IECON 2. 26th Annual Confjnc of th IEEE, vol. 3, pp. 53 58 vol.3, 2. [2] C. Hatipoglu, U. Ozgun, an M. Sommvill, Longituinal haway contol of autonomous vhicls, in Contol Applications, 996., Pocings of th 996 IEEE Intnational Confnc on, pp. 72 726, 996. [2] R. Mull an G. Nock, Intllignt cuis contol with fuzzy logic, in Intllignt Vhicls 92 Symposium., Pocings of th, pp. 73 78, 992. [22] Z. Avagic, E. Cnica, an S. Konjicija, Longituinal vhicl guianc using fuzzy logic, E-ISSN: 2224-2856 648 Volum 9, 24
Italo A. Souza-D-Assis, Rnan Olivia, Maclo A. C. Fnans Dg of mmbship.8.6.4.2 FN FN9 FN8 FN7 FN6 FN5 FN4 FN3 FN2 FN FP FP2 FP3-5 -4-3 -2 - v b (t) Figu 3: Mmbship function of th v b (t) vaiabl uing th baking stat. Tabl 3: St of uls fo th baking stat fuzzy systm, FS b ( ). x (t) GN MN PN Z PP MP GP l N (t) Fa FN FN9 FN8 FN7 FN6 FN5 FN4 Na FP FP2 FP3 FN3 FN3 FN2 FN in Inustial Tchnology, 26. ICIT 26. IEEE Intnational Confnc on, pp. 893 898, 26. [23] F. Cabllo, A. Acuna, P. Valljos, M. Ocha, an J. l Sola, Dsign an valiation of a fuzzy longituinal contoll bas on a vhicl ynamic simulato, in Contol an Automation (ICCA), 2 9th IEEE Intnational Confnc on, pp. 997 2, 2. [24] A. Rschka, J. Bohm, F. Saust, B. Licht, an M. Mau, Saf, ynamic an comfotabl longituinal contol fo an autonomous vhicl, in Intllignt Vhicls Symposium (IV), 22 IEEE, pp. 346 35, 22. [25] H. B. Pacjka, Ti an vhicl ynamics, Socity of Automotiv Engins an Buttwoth- Hinmann, 22. [26] J. Tovao, P. Piinha, an H. Jog, Simulation mol an oa tsts compaativ sults of a small uban lctic vhicl, in Inustial Elctonics, 29. IECON 9. 35th Annual Confnc of IEEE, pp. 836 84, 29. [27] K. Ogata, Mon Contol Engining. Pntic Hall PTR, 2. [28] E. Elbakush, A. Shaaf, an I. Altas, An fficint ti-loop contoll fo photovoltaic pow fou-whl lctic vhicl, in Innovations in Infomation Tchnology, 27. IIT 7. 4th Intnational Confnc on, pp. 42 425, 27. [29] A. Rschka, J. Bohm, F. Saust, B. Licht, an M. Mau, Saf, ynamic an comfotabl longituinal contol fo an autonomous vhicl, in Intllignt Vhicls Symposium (IV), 22 IEEE, pp. 346 35, 22. [3] J.-J. Matinz an C. Canuas- Wit, A saf longituinal contol fo aaptiv cuis contol an stop-an-go scnaios, Contol Systms Tchnology, IEEE Tansactions on, vol. 5, no. 2, pp. 246 258, 27. E-ISSN: 2224-2856 649 Volum 9, 24
Italo A. Souza-D-Assis, Rnan Olivia, Maclo A. C. Fnans v b (t) 2 4 6 8 5.8.6.4 l N (t).2 5 x(t) Figu 4: Rlation btwn th inputs an th output fo th ul bas us fo th baking stat, ( x (t), l N (t)) v b (t)..25.2 Hight (km).5..5.5.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9 9.5 l n (km) Figu 5: Rout us in th simulation. 55 5 45 4 x(t)(km/h) 35 3 25 2 5 5 2 3 4 5 6 7 t(scons) Figu 6: Simulation sults fo th acclation stat. E-ISSN: 2224-2856 65 Volum 9, 24
Italo A. Souza-D-Assis, Rnan Olivia, Maclo A. C. Fnans 5 x(t)(km/h) 4 3 2 2 3 4 5 6 7 t(scons) Figu 7: Simulation sults fo th moving stat. 6 5 x(t)(km/h) 4 3 2 73 74 75 76 77 78 79 72 t(scons) Figu 8: Simulation sults fo th baking stat. E-ISSN: 2224-2856 65 Volum 9, 24