P In [Escr Please cite this nternational Jo A Dan Fuzzy have e This p princip contro experi within evalua 1 Tradit of the imple and to by Lo expre mathe severa most r Fuzzy 20 stu introd such a Howe and th curren discus GUNT ball-b hold t develo relativ should On th intuiti fuzzy orient imple digita Fuzzy comp riba texto] s paper as: ournal of Electr An Edu niel Zaldivar, aD controllers hav enabled designe paper presents ples at undergr ol study aims to ments. The pr n the Electronic ation of their im 1. Introdu tional method e system to be ementation of oo difficult or ofti Zadeh [1] sses operatio ematical equa al successful robust and eas y control is an udents per sem duction of fuzz as an educatio ever, the numb he existing on nt available f ssed below. T [7] provide beam model w the ball in a opment softw ve high cost a d be rather co he other side, t ive way. It pr logic gates A tation aims to ementation, it al based system yTECH [9] is letely graphic rical Engineeri ucation u , Erik Cuevas epartamento d Av. R ve gained popul ers to control co an educational raduate level b accompany stu oposed educati cs Department i mpact in the stud ction ds to control a e controlled. A the control al r impossible to ] which helps onal laws of ations. Such l fuzzy control sy to impleme n elective cour mester at each zy control con onal platform ber of comme nes are either t fuzzy logic l es an introduc which acts as a specific posit ware FSH-She and large dime nsidered as a the CE124 [8] rovides a sche AND & OR, o implement does not prov ms. a family of cal and based ing Education, nal Fuz using L s, Marco A. P Edga de Electrónica Revolución 150 larity in the pas omplex system platform base by providing a udents to the le ional platform in the Universit dent performanc any dynamic s An accurate ap gorithm. Unfo o model accu to reduce the f a control s linguistic term approaches i ent algorithms rse at the seco h academic ye ncepts to unde radically help rcially availab too expensive aboratory kit ction to digita a mechanical s tion by tilting ell and then c ensions have y demonstrative ] has been des ematic panel NOT blocks fuzzy system vide convenien fuzzy logic a on ISO 9000 Volume 50, Nu zzy-bas LEGO Pérez-Cisnero ar O. Palafox  a, Universidad 00, Guadalaja Abstract st few decades w ms through lingu ed on LEGO© a simple and e arning of fuzzy has been succ ty of Guadalaja ce are both prov system require pproximation ortunately, mo urately. Fuzzy e complexity system in lin ms are expres in the literatur s. nd year of Ele ear. It has bee ergraduates is ps to understa ble educationa e or relative co ts that offer l real-time co single-variabl g the beam. C compiled to yielded a non e tool. signed to allow compound wi and a defuzz ms by using an nt programmi and neural-fuz and IEC 1131 umber 2 (April sed Con Robot os, Juan H. S x d de Guadalaja ara, Jal, Méxic with successful uistic-based rul NXT to assist asy-to-follow t y control fundam cessfully applie ara. The descrip vided in the pap e the use of s of the system ost real system logic is a ma of controlling nguistic term ssed in the f re, the fuzzy ectronic Engin en agreed amo challenging a and the practic al fuzzy contro omplex to be practical han ontrol by fuzz e system. A fu Control algori generate mic n-practical ind w users to qui ith two fuzzif zifier. It is a nalogue elem ng properties zzy developm 1-7 fuzzy logi 2013), Manche ntrol p s Sossa, Jose G. ara, CUCEI co l implementatio es in contrast t t the learning o teaching setup. mentals by buil ed to several u ption of robotic per. some knowled m is thus crucia ms are nonline athematical fra g nonlinear sy ms instead of form of IF-TH PD controller neering. The c ong our facult and that experi cal implicatio ol laboratory k used. A quick nds-on experie zy methods. T fuzzy control i ithms are init crocontroller dividual develo ickly impleme fiers, a fuzzy unique hardw ments. Despite which are no ment tools who ic standards. I ester University platform . Rodríguez, ons in many fie to traditional m of fuzzy logic . The proposed lding hands-on undergraduate c c experiments a dge about the al for the succ ear, highly com amework dev ystems. Fuzzy f traditionally HEN rules. A r [2-6] is one course attracts ty members th imental comp ons of fuzzy c kits is rather l k overview on ence to stude The setup incl is used to atte tially written code. Howev opment setup ent fuzzy logic state table, a ware module e delivering a ormally availab ose programm It provides co y Press, pp. 15 m lds that methods. control d fuzzy robotic courses and the model cessful mplex, eloped y logic y used Among of the s about hat the ponents ontrol. limited n some ents is ludes a empt to in the ver, its which c in an set of whose a quick ble for ming is de and 57-171. P In [Escr Please cite this nternational Jo runtim as InT target most o The F fuzzy contri MAT It is hardw applic comp roboti lasting So far 19]. T with c their theref engin The L which LEGO hardw and C the d proce In this fuzzy algori two ex conce are en platfo fuzzy emerg impac theory The p the e orient perfor 2 In thi rules a riba texto] s paper as: ournal of Electr me modules fo Touch, LabV ted at financia of them are re Fuzzy Logic T logic system ibutions. How LAB program important to ware, software cations may b lemented by r ics motivates g impact on th r, the use of ro They can quick conducted exp immediate in fore not surpri eering subject LEGO© NXT h has demons O© componen ware and softw Control. Studen esigning and ssing and sens s paper, a sim control conce ithm to the stu xperiments us erns about the ncouraged to c orm using RO control issue ged from exp ct of robotics y. paper is organi xperiments. S tation project rmance and its 2. The fuzz s work, the fu and has the str rical Engineeri or microcontro VIEW, FIX, a al and comme elatively comp Toolbox for M ms. Thousand wever, the Mat mming environ consider tha e, hardware-so be learnt thro robotics exerc the learning o he student. obotics has be kly become fa periments tha nterests demon ising that man ts. is a friendly, strated its us nts offer inter ware which ar nts can becom testing their sing units suc mple education epts at underg udents. The ca sing the fuzzy robot’s orien code the real- OBOTC©. Du s as their moti eriments and hands-on exp ized as follow Section 3 sh while Section s evaluation a zy PD cont uzzy PD contr ructure illustr ing Education, ollers, PLCs, p and Matlab/S rcial applicati plex to test and MATLAB [10] ds of code ex tlab© license nment. at educational oftware, sizes ough paper-an cises. This wo of fuzzy contr een positive to amiliar to the p at strength the nstrating the ny universities affordable, m e for researc resting possib re suitable for me quickly fam r own add-on h as microcon nal platform b graduate level. apabilities and y PD controller ntation while t -time applicat uring the who ivation is enco the programm periments for ws. Section 2 e hows the LEG n 5 presents th as some conclu troller roller [2-6] is rated in Figure Volume 50, Nu process contro Simulink. A s ions of fuzzy d more oriente is a set of eas xamples are a is very expen l goals can b and costs in a nd-pencil exe ork has been d rol by connect o encourage th platform and eoretical conce benefits of h s are incorpora motivational an ch and educat bilities. Minds implementing miliar with the n components ntrollers, senso based on LEG . The course s d limitations o r which are tim the second so tion by using ole process, st ouraged by th ming experien motivating st explains the fu GO System he path tracki usions and con used to impl e 1. umber 2 (April ol systems and special versio logic and neu ed as a final a sy-to-use func available sinc nsive and requ be achieved b a variety of pla ercises, traditi developed und ting theory an he student’s in test their own epts. This exp ands-on robo ating the use o nd effective e tional propos storms LEGO g complex de e set by taking . They might ors, etc. GO© NXT is p starts by theor f LEGO© NX mely provided lves a robotic their own pro tudents strong he robotic appl nce. The pape tudents’ intere uzzy PD contr configuration ing setup. Sec ntributions of ement robot e 2013), Manche d popular soft on, fuzzyTEC uro-fuzzy tech application too ctions for buil ce world-wid uires users to by a wide ra atforms. Fuzzy ional comput der the hypoth nd exercises yi nterest on eng n ideas based o pands student otics on the cl of robotics pla educational rob ses [22-29]. A O kits include esigns for Rob g further steps t also interfa presented to a retically introd XT mobile rob d by the lectur c path tracking ogramming sk gly reinforce lication and th er also discus est on learnin roller algorith n. Section 4 ction 6 discus f the paper are experiments. I ester University tware package CH for Busin hnologies. How ol. lding and eval e users have be familiar w ange of comp y control theo ter programm hesis that the ielding a deep gineering topic on project des t knowledge b lassroom [20] ants to teach s botics platform At first glanc relatively low botics, Mechat s and adventur ace the kit to assist the learn ducing the fuz bots are studie rer. The first p g problem. St kills over the the learning he visual resul sses on the p ng the fuzzy c hm which featu shows the r ses on the stu drawn in Sec It consists of y Press, pp. 15 es such ness is wever, luating made with the plexity, ory and ming or use of per and cs [11- signing beyond ]. It is several m [21] ce, the w-cost tronics ring to o other ning of zzy PD ed with project tudents LEGO of the lts that ositive control ures in robot’s udent’s ction 7. only 4 57-171. P In [Escr Please cite this nternational Jo The v All ar the de 2.1 Fu As it error The ra where two m memb memb The o determ that H of eac The m follow Were positiv riba texto] s paper as: ournal of Electr values Gu, Ge re to be determ efuzzyficated uzzyfication is shown in F is defined as: ate is defined e ce is the cur membership f bership functi bership functi output memb mined by expe H=L. It is obse ch specific con membership fu ws: ep  is the er ve. + - Set-point - rical Engineeri en rn   e and Gr corre mined either b output, which Figure 1, there as follows: rrent error, pe functions (pos ions, one at ons: error po ership functio erimentation erved that its ntrol problem functions for t rror positive, rate error de/dt ep   rp L   ing Education, n Figure 1 Fu espond to the by experimen h is also known e are two inpu error = rate = ( e is the previo sitive and neg each input ( sitive (ep), er on is shown [4-6]. In orde value depend as it is presen the input vari en  is the er Figure 2 In Gr Ge ( * ) 2 e L G error L  ( * ) 2 r L G rate L  -L Volume 50, Nu uzzy PD contro output gain, ntation or by t n as “crisp ou uts to the contr = setpoint - y (ce - pe) / sp, ous error and gative) for ea (one for the rror negative in Figure 3. er to reduce th ds on the limit nted in Section iables, error a rror negative, nput membersh Fuzzyficati Control Ru Defuzzyficat ) en  rn  0 1.0 umber 2 (April ller structure the error gain the method de utput”. roller: error a sp is the sam ach input (err error and on (en), rate pos . H and L ar he number of of universe o n 4.1. and rate, are rn  is the ra hip functions ion les tion u* ( * 2 e L G erro L   ( * 2 r L G rate L   ep  L 2013), Manche n and error rat escribed on [3 and rate (the e mpling period. ror and rate), ne for the ra sitive (rp) and re two positi control param of discourse fo defined as de ate negative, u Gu Proc ) or )e rp  Ge*error Gr*rate ester University te gain respec 30]. The value error´s change (1 (2 Figure 2 repr , with two pa ate) and four d rate negativ ive constants meters, it is as or the input va escribed in [2 (3 and rp  is th y cess y Press, pp. 15 ctively. e u* is e). The 1) 2) resents airs of r input ve (rn). to be ssumed ariable 2-3] as 3) he rate 57-171. P In [Escr Please cite this nternational Jo 2.2 Fu Accor Abov More Accor Wher outpu In ord this w inputs (see E comb riba texto] s paper as: ournal of Electr uzzy rules an rding to [4] th e, ep is the po details about rding to [3], th e 1( ) 2( , R x R   ut values. der to simplify work, follows s region (IC) Equation 6) w ination of the rical Engineeri nd defuzzyfica here are four ru R1. R2. R3. R4. ositive error, e the interpreta he defuzzyfica u ( ) 3( ) , , x R x R   y the controlle the design pr as it is shown with only on error value a - Negativ ing Education, Figure 3 Ou ation ules to evalua If error is ep If error is ep If error is en If error is en en is the nega ation of these f ation method ) ( 4 ) ( 4 ) ( x R x R H u     4( ) R x are the m er algorithm an roposed in [4- n by Figure 4 ne being used and its rate. -H ve Output Volume 50, Nu utput membersh ate the fuzzy P p and rate is rp and rate is rn and rate is rp n and rate is rn ative error, rn four rules are employs the c ( 3 ) ( 2 ) ) ( 2 ( ( 0 ) R x R R x R         membership in nd save comp -5]. In such a 4. Nine equati d depending 0 Zero Output umber 2 (April hip functions PD controller: p then output n then output p then output n then output is the negativ provided by [ centre of mass ) ( 1 ) ( ( 1 ) ( 3 ) ( ) x R x x R x R H     nput values and puting time, th approach, the ions are used on which reg H Positive 2013), Manche is op is oz is oz is on ve rate and rp [4]. s method as fo )) x d –H,0, H are he fuzzy PD co input space is to calculate t gion is activa e Output Output (u*) ester University (4) p is the positiv ollows: (5) the membersh ontroller, adop s divided into the control ou ated by the c y Press, pp. 15 ve rate. hip pted at o a 20- utput u current 57-171. P In [Escr Please cite this nternational Jo 3 The b servo (alrea a com measu headin totally ROBO riba texto] s paper as: ournal of Electr 3. Experim block diagram motors conne ady embedded mpass sensor fr ures the earth ng is calculat y prepared to OTC© progra I erro rat er ra IC error 0 < ra IC error -L < r rical Engineeri 2(2 e L u L G er   2(2 r L u L G ra   1 [ * 2 r u L G ra   1 [ * 2 e u L G e   1[ * 2 r u L G r   1 [ * 2 e u L G    u L for IC  u L for I  0 1 u en IC  mental setu m for the LEG ected to out p d and transpare from HiTechni ’s magnetic f ted to the near be compatib am is transpare -L C18 or < -L te > L IC19 rror < -L ate < -L C13 r < -L ate < L C14 r < -L rate < 0 -er -er F ing Education, [ * ) e G error rror [ * ) e G error ate  ] ate for IC ] error for I ] rate for IC * ] error for 17. C 19. IC 18, 20. IC up GO system for ports A and B ent to the user ic© is used as field and outp rest 1̊ and ret ble with the L ent for the use IC12 -L < error < 0 rate > L IC15 -L < error < 0 rate < -L IC4 -error rate IC6 rror > -rate Figure 4 Input Volume 50, Nu * ] r r G rate  * ] r G rate f  9, 10. C IC 11, 12. IC IC 13, 14. C IC 15, 16. r IC IC r both exercise as actuators. r) which is ge s input signal puts a value re turned as a nu LEGO NXT© er. L - IC 0 < err rate IC 0 < err rate te te er e IC8 error < -ra IC3 error < rat rate combinations umber 2 (April 1, 2, for IC IC I 3, 4, for IC IC IC es is shown in Such motors enerated by the in port 1. Suc epresenting th umber from 0 © electronics, L C11 ror < L > L C16 ror < L < -L IC1 rror > -rate IC2 rror > rate ate te 2013), Manche 5, 6. IC IC 7, 8. C IC n Figure 5. T are controlle e LEGO brick ch sensor is a he current hea 0 to 359. This whose implem IC17 error > L rate > L IC20 error > L rate < -L IC10 error > L 0 < rate < L IC9 error > L -L < rate < 0 ester University (6) The system us ed by a PWM k. On the othe digital compa ading. The ma third-part sen mentation usi error y Press, pp. 15 es two signal er side, ass that agnetic nsor is ing the 57-171. P In [Escr Please cite this nternational Jo 4 In thi explai as it i contro error r to one Eq. (6 4.1 Im This whole been positiv Using softw riba texto] s paper as: ournal of Electr 4. Orienta is section, the ined. In order is depicted by ol problem is h rate r ( / de dt  e out of 20 po 6) is used to ca mplementatio section starts e strategy for experimentall ve limit (L) is g ROBOTC© are. ref  rical Engineeri tion contro e experiment to reach the r y Figure 6. C handled as fo ), the fuzzy P ossible regions alculate the co on by explainin controlling t ly obtained a s set to 360, d © as developm f   ing Education, Figure 5. Di ol using the to control the reference angl Considering th llows: Using PD controller i s (see Figure 4 ontroller outpu ng the implem the robot’s or and the L val defining the lim ment platform Figure 6. Ob Figure 7. R F de dt e r PWM PWM Volume 50, Nu iagram of the L e Fuzzy PD e robot’s orie le ref  , the ang he fuzzy appr as inputs the identifies the 4). Once the c ut u. mentation of t rientation. Lin lue. Since the mits of interes m, students ar btaining the ang Robot’s orienta Fuzzy PD Di M M umber 2 (April LEGO system controller entation ref  u gle’s error e roach present angle’s error region (input control region the first expe ne 1 shows th e angle varies st for the univ re encourage gle’s error e ation control Robot u gital input Compass sensor 2013), Manche using the fuz must be calcu ted on Section e (see Figur combination) has been defi eriment. Algo he controller’ s from 360 to verse of discou d to code th actual  ester University zzy PD contro ulated by ref  - n 2, the orien re 7) and the a ) which corres ined, one of th rithm 1 depic s gains which o -360 degree urse at this pro he real-time c y Press, pp. 15 oller is - actual  ntation angle’s sponds he nine cts the h have es, the oblem. control 57-171. P In [Escr Please cite this nternational Jo Ori In ord been i Figure Consi which F riba texto] s paper as: ournal of Electr ientation contr G G G L r a  u r e e 1: G 2: L While 3: e 4: degree 5: e 6: degree 7: 8: r 9: e 10: 11: r 12: u 13: 14: robot r 15: 16: 17: robot r 18: 19: der to elimina included to de e 8 shows the idering its imp h is shown in t Fuzzy PD Algo 1: FUZ 2: Eva 3: if 4: 5: if 6: 7: if 8: 9: if 10: 11: if 12: rical Engineeri rol Algorithm e G : error’s ga r G : rate’s gai u G : output’s g L: universe of ref  : desired an actual  : actual a u: output of t r: rate of the : angle’s er 1 : angle’s er e G • 20, r G • L • 360 (true) • ref actual    if( e> ) t s, to turn th • e-2  if( e<- ) s, to turn th e• e+2  r • 1 e e    1 • e e• *  e e G r • * r r G • FUZZY( e,r u • u u G * if ( e>0 rotates antic motorA • motorB • else rotates clock motorA • motorB • ate the error e efine the short inclusion of s portance, the the Algorithm orithm ZZY( e,r) luate the 20 ( e>-r) or ( u • (L/(2* ( eL) and u ← (L+r)/2 ((0< er) or (- e> *(2*L-abs( e) eL)) or (( )/2 0r) or (- e>-r )))*( e+r) <-r) or ( e<-r ))*( e+r) ((0L) and(-L< e e<-L) and (-L< umber 2 (April us period of t the controll positive limi the angle’s if the error if the error he angle’s err e last angle’ he actual ang e rate by its e fuzzy funct the output b e’s error is p ’s error is ne ntrol algorithm g ref  , lines 4 nce angle cons c example. scribed as a se t u r) then • re r) then • re >L)) then <0)) then r<0))then 2013), Manche time ler’s gains it error is bigger tha is smaller th ror rate s error le’s error by gain ion to obtain by its gain positive then egative then 4 and 6 of th sidering the a eparate functi egions ic1, ic egions ic3, ic • regions • regions ic1 • regions ester University an 180 han -180 y its gain n the output the the e Algorithm ctual robot po on (FUZZY( c2, ic5, ic6 c4, ic7, ic8 ic9, ic10 1, ic12 ic13, ic14 y Press, pp. 15 1 have osition. e,r)) 57-171. P In [Escr Please cite this nternational Jo Figure of 90 300 it riba texto] s paper as: ournal of Electr 13: if 14: 15: if 16: 17: if 18: 19: if 20: 21: Figure 8 e 9 shows the degrees. Figu terations. Such 3: 6 : ( 7 : e e if e e e e             rical Engineeri ((r<-L) and ( u • (-L+ e ( e>L) and ( u ← L ( e<-L) and u ← -L (( e<-L) and u • 0 return u  8. Reaching effi e performance ure 9, below, s h graphic is a 3 2 ) 2 3 2 2 1 2 ref actual then e                ing Education, (-L< e<0)) or ( e)/2 r>L) then (r<-L) then (r>L)) or (( Algorithm 2. iciently ref  , (i. e of the real-tim shows the evo compulsory a  Clockwise Volume 50, Nu (r<-L) and (0< e>L) and (r<- Fuzzy PD cont .e. deciding if it me fuzzy con olution of pow assignment for 3 2 ref    umber 2 (April < e L)then ► ween L and -L u= L u< L)then u= -L R p K  ► ro ( 2 l b w v u       0.8 1 exp l w lw   ( 2 r b w v u     0.8 1 exp r w r w   motorA ← w motorB ← w he performan y and the actua Figure 11. T and discus ribes the posi rget has been een incorpora ment of the Un rs two perform to an examina n the other han finishing the f ar for both the ider a univers ontrol course a robotic subje a year in term highest mark w 100 −80 0 0 0 0 0 0 0 0 0 ing Education, preventing a obot’s lineal 1 ) c           ► ► 1 ) 2 b c           ► o ► a l w ► applyin r w ► applyin Algorithm 3. P nce of the fuz al trajectory a The fuzzy contro sion itive impact o the motivatio ated into an niversity of G mance indexes ation that has b nd, the latter fuzzy course. e practical and se of forty stu and the remain ect. Table 1 ms of the Ave while the Wors −60 −40 Volume 50, Nu an overflow of velocity scal obtaining the avoiding satu obtaining the avoiding satur ng the output ng the output Path tracking co zzy controller re both plotted oller performan on students a on for learnin elective seco Guadalajara. s: the Course E been applied considers a s Such proced d non-practica udents with tw ning referring shows the v erage and the st value corres 0 −20 cms umber 2 (April f the output b led by a line e left wheel uration right wheel ration to the robot t to the robot ontrol algorithm for a generic d in centimete nce over a path- after the impl ng fuzzy contr ond-year und Examination a to student jus second examin dure aims to e al course atten wenty corresp g to those stud values of the e Worst-Best sponds to the 0 20 s 2013), Manche by limiting it ear gain. velocity velocity ’s left motor t’s right moto m c path-trackin ers. -tracking task. lementation o rol theory. All ergraduate co and the Exam st after finishin nation that is evaluate the s ndees. ponding to th dents who hav e Course Ex obtained valu lowest score. 40 6 Reference tra Robot’s traje ester University ts value to r or ng task. The r of hands-on r l the experime ourse taught ination after a ng courses on applied to st student’s know hose who atten e attended the xamination an ues. The Best 60 80 trajectory ajectory y Press, pp. 15 robot’s robotic ents in in the a year. n fuzzy tudents wledge nded a e fuzzy nd the value, 57-171. P In [Escr Please cite this nternational Jo Table hands trend have b index been o 7 Fuzzy indust contro By us nonlin based course exper while are pr of a L to im Exper issues trend worke learni the stu Refe [1] L. [2] H. 513-5 [3] H contro [4] Y Analy Albuq [5] E contro 1998 I [6] F. applic Ex riba texto] s paper as: ournal of Electr e 1 presents th s-on robotic c is observed f been given to addresses low observed for e 7. Conclus y controllers h trial and acad ol courses in m sing fuzzy lo near systems. d on LEGO© es. The capab iments using the second so resented inclu LEGO© NXT mplement cont rimental evide s for the stud to hold the kn ed through th ing of fuzzy c udents. erences A. Zadeh, ´F . Ying, W. Sil 520. H.A. Malki, h ol systems´, IE Y.C Hsu, G. ysis´ Proceed querque, NM, . Sanchez, L. ol´, Fuzzy Sys IEEE Interna Lara-Rojo, E cations´, Journ Course Exam xamination af rical Engineeri he Course Ex ourse are high for the Examin o students atte wer values fo either the Cou Ta sions have become demic subject many technica gic control, d In this pape NXT to assi bilities and lim a fuzzy PD c olves the robo uding their cor as a robust ro trol algorithm ence shows an ents who hav nowledge of fu he proposed e control by con uzzy sets´. Inf ler, J. J. Buckl h. Li, G. Che EEE Transacti Chen, E. San dings of the 1997, pp. 141 A. Nuno, Y.C stems Proceed tional Confer E.N. Sanchez, nal of Applied mination fter a year ing Education, xamination ind her than those nation after a ending the fuz or students att urse Examinat able 1. The aver popular in r ts. Such trend al colleges and designing a c r, the authors ist the learnin mitations of L controller. The ot’s path track rresponding e obotic platform ms by simply n increase in t ve attended th fuzzy control i exercises. Suc nnecting theor formation and ley, ´Fuzzy Co n, ´New desi ions on Fuzzy nchez, ‘A Fu 1997 IEEE 12-1417. C. Hsu, G. C dings, 1998. I ence on , 1, (1 D. Zaldivar, d Research an Fuzzy con Average 70 55 Volume 50, Nu dex which sh e given to stu year index. A zzy hands-on tending a trad tion or the Exa raged scholar-p recent decade d has indeed d universities ontroller is re s have presen ng of fuzzy c LEGO© NXT e first experim king task. Both xperimental r m for teachin y doing progr the performan he hands-on r issues for long ch results ind ry and exercis d control, Vol ontrol Theory ign and stabi y Systems, 2 ( uzzy controlle International Chen, ´Fuzzy P IEEE World C 1998), 302-30 ´Minimal fuzz d Technology ntrol course Best Worst 92 60 76 45 umber 2 (April hows that the udents attendin Again, the Bes control cours ditional fuzzy amination afte performance res es with succes triggered a r around the wo elatively simp nted the use o control concep T mobile robo ment addresse h algorithms a results. The pa g fuzzy contro ramming at a nce and reinfor obotic exercis ger periods of dicates that th ses yet sowin l. 8, Academic y: A Nonlinear ility analysis (1994), 245 – er for a Mult l Conference PD scheme fo Congress on 06. zy microcontr y, 1(2) (2003) Fuzzy t Av 2013), Manche marks for stu ng a tradition st index show se. On the oth y control cour er a year index sults ssful impleme remarkable a orld. ple task yet f of a simple e pts in undergr ots have been s the robot’s and their requ aper has also ol. The platfo a high-level rcement of lea ses. Similarly f time for those he use of rob g a deeper an c, New York, r Case, Autom of fuzzy pro 254. ti-Link Robo e on Robotics for underactua Computationa roller impleme 137-147. y control cour robotic exe verage 82 72 ester University udents attendi al course. A s ws that higher her hand, the rse. Same tren x. entations in s availability of facing comple ducational pl raduate engin studied with orientation pr ired additiona shown the po orm enables st language inte arning fuzzy c y, evidence sh e students wh botics motivat nd lasting imp 1965, pp 338- matica, 26 (3) oportional-deri t Control: St s and Autom ated robot sw al Intelligence entation for d rse + hands-on ercises Best 100 97 y Press, pp. 15 ing the similar marks Worst nd has several f fuzzy ex and atform neering in two roblem al tools otential tudents erface. control hows a o have tes the pact on -353. 1990, ivative tability mation, wing-up e., The idactic n Worst 73 62 57-171. P In [Escr Please cite this nternational Jo [7] GU GmbH [8] C system [9] Fu [10] logic/ [11] L Proce Florid [12] C in Au 2451– [13] J LEGO TRAN [14] T Engin [15] A Noll, Cours [16] B engin [17] Proce volum [18] F system [19] P Educa [20] L small, [21] R progra [22] D in the Confe [23] D LEGO 2011, [24] A electr Appli riba texto] s paper as: ournal of Electr UNT Gerateb H, Fahrenberg CE124 Fuzzy ms.pdf [Visite uzzyTech, http Fuzzy L /index.html;jse L. Meeden. U eedings of the da AI Research C. A. Jara, F. A utomatics and –2461. J. M. Gómez-d O NXT Mob NSACTIONS T. Karp, R. G neers With LE A. Behrens, L K. Hameyer se Into Practic Beer, R. D.; C eering. Comm Kumar, D., eedings of the me 30(1) of SI Fabiane Barre matic review´, P. Ranganath ation´, Procee L. Greenwald , low-cost plat R. Ramli, M am´, Procedia D. Martinec a e IEEE Inter erence on Syst D. Zermas, C O Platform, IE pp. 1381-138 A. 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