INTO CHAINED FORM USING DYANMIC FEEDBACK D. TILBURY, O. SRDALEN, L. BUSHNELL; S. SASTRY

Size: px
Start display at page:

Download "INTO CHAINED FORM USING DYANMIC FEEDBACK D. TILBURY, O. SRDALEN, L. BUSHNELL; S. SASTRY"

Transcription

1 A MULTI-STEERING TRAILER SYSTEM: CONVERSION INTO CHAINED FORM USING DYANMIC FEEDBACK D. TILBURY, O. SRDALEN, L. BUSHNELL; S. SASTRY Electroncs Research Laboratory, Department of Electrcal Engneerng and Computer Scence, Unversty of Calforna, Berkeley, CA 970. E-mal: On leave from the Norwegan Insttute of Technology, Trondhem, Norway Abstract. In ths paper, the knematc model of an autonomous moble robot system consstng of a chan of steerable cars and passve tralers wth axle-to-axle htchng s examned and converted nto a mult-nput chaned form usng dynamc state feedback. Some of the methods whch have been proposed for steerng two-nput chaned form systems are generalzed to mult-chaned systems, and then appled to two example mult-steerng traler systems. Key Words. Moton plannng, nonholonomc systems, dynamc feedback, moble robots, chaned forms.. INTRODUCTION In ths paper the moton plannng problem s solved for a mult-steerng traler system; that s, a car-lke moble robot pullng a combnaton of n passve tralers and m? steerable car-lke robots. The controls avalable to the system are the velocty of the lead car and the steerng veloctes of all m car-lke robots. Ths system can be thought of as a generalzaton of a standard n-traler system, the moton plannng problem for whch was consdered and solved n (Srdalen, 993; Tlbury et al., 993b). Moble robot systems of ths knd are of nterest n practcal applcatons; part of the motvaton for ths work came from work on the re truck (Bushnell et al., 993; Tlbury and Chelouah, 993). Also, the authors have been told anecdotally about the constructon of such n-traler systems wth multsteerng for use n nuclear envronments (Canudas de Wt, 993) and also for baggage and cargo handlng (Gralt, 993). These moble robot systems can be modeled as havng one constrant on each axle; namely, that the wheels are allowed to roll but not to slp. These constrants are nonholonomc or nonntegrable and do not reduce the reachable conguraton space of the moble robot. Although the present system appears at rst glance to be a straghtforward extenson of the systems consdered earler, the man motvaton n wrtng ths paper s to exhbt ts added rchness and complexty. As before, the moton plannng plannng problem s solved by rst convertng the system nto chaned form. Unlke the prevous examples, ths system wll requre states to be added to the system before the transformaton nto chaned form can be found. Motvated by the physcal structure of the constrants nvolved, the dynamc state feedback that s used conssts of addng vrtual axles to each of the steerable cars n the system. A partcularly ntrgung aspect of ths work s ts connecton wth an emergng body of lterature n derentally at systems by Fless and hs coworkers (Fless et al., 99; Rouchon et al., 993). They have shown that chaned form systems are a specal case of what are known as derentally at systems. For the two nput case, t has been ponted out (Martn and Rouchon, 993; Murray, 99) that, modulo somewhat derent regularty condtons, chaned forms are equvalent to at systems for the type of drft-free systems that arse n nonholonomc moton plannng. Ths s not true for systems wth more than two nputs wthout allowng for the possblty of dynamc state feedback.. THE SYSTEM MODEL Consder a mult-steerng traler system,.e. a system of n (passve) tralers and m (steerable) cars lnked together at the axles by rgd bars, as shown n Fgure. It s assumed that each body (traler or car) has only one axle, snce a body wth two axles can be modeled as two one-axle bodes... Conguraton Space The conguraton of the system s dened by the angles of all the axles, the angles of the rgd bars n front of the steerable cars, and the Cartesan poston of the system n the (x; y) plane. The actve or steerng axles are numbered from front () to back (m), and the passve axles are numbered smlarly from to n. The angle of each passve axle wth respect to the horzontal s where s the axle number and s the number of the steer-

2 θ θ - θ - v θ n + φ θ n θ n second steerng tran frst steerng tran L θ body (passve) θ - L θ v - body - (passve or actve) θ m n m θ m n - m mth steerng tran Fg.. A mult-traler system wth n (passve) tralers and m (actve) steerng wheels. ng wheel most drectly n front of that axle. Each steerable axle together wth the passve axles drectly behnd t s called a steerng tran. The passve axles whch are drectly n front of the steerable axles wll be dented by the ndces n ; : : :; n m?. Assumng, by conventon, that the rst axle s steerable, gves n 0 = 0. The angle of the rst axle s 0, and the axles drectly behnd t are denoted by ; : : : ; n. The superscrpts ndcate these axles are n the rst steerng tran. The axle drectly behnd the rst steerng tran s steerable, ts angle s n. The (passve) axles behnd the second steerng wheel are n + ; : : :; n, and the rest of the angles are numbered n a smlar fashon. For convenence of notaton, let n m n, although n general the last axle wll not be steerable. If the last axle s steerable, then n m? = n m. Let be the absolute angle (wth respect to the horzontal) of the bar connectng the ( + ) st steered axle to the last axle of the th steerng tran (whch may be steered or passve). The Cartesan poston, (x; y) of any one of the axles can be used n the denton of the conguraton of the system. For reasons whch wll be explaned n the sequel, the x and y postons of the last axle are chosen as conguraton varables. Ths general system ncludes as specal cases:. the standard n traler system (m = ).. the re truck (m =, n = n = )... Knematc Equatons The knematc model of the system s found by examnng the relatonshps between the veloctes of the bodes, as dened by the rgd connectons between them. If the lnear velocty of the last body s v m n m, then the dervatves of x and y are the proectons of ths velocty, _y = sn m n m v m n m () _x = cos m n m v m n m () Now, let v represent the the lnear velocty of the axle wth angle. Consder rst the case of a passve traler; refer to Fgure. The lnear veloctes of body? has two perpendcular components: Fg.. The velocty relatonshps between adacent bodes when the rear body s a passve traler. The front body may be ether a passve traler or a steerable car. θ + n - φ Ln φ vn + L n + φ + θ n φ - θ n θ n v n frst body of the (+)st steerng tran (actve) last body of the th steerng tran (passve or actve) Fg. 3. Showng the velocty relatonshps between two bodes when the rear body s an actve car. one n the drecton of the lnear velocty of the th body, v = cos(?? )v? ; and the other n the drecton of the angular velocty of the th body, L _ = sn(?? )v? : (3) When the rear body s an actve car nstead of a passve traler (see Fgure 3), the relatonshp between the two lnear veloctes has the form vn + cos(n +? ) = vn cos(n? ) ; and the angular velocty vector L _ n has two components, L _ n + = sn(n +? )vn +? sn(n? )vn () : The dervatves of the steerng wheel angles are the nputs _ n =!? : (5) The knematc equatons for the mult-steerng traler system are completely gven by ({5). 3. CONVERSION TO CHAINED FORM Now that knematc behavor of the mult-steerng system has been descrbed, the transformaton to mult-nput chaned form can be found. 3.. Mult-nput Chaned Form A mult-nput chaned form system s dened as _z 0 0 = u 0 _z 0 = u _z m 0 = u m _z = z 0 u0 _z m = z m 0 u0 (6).. _z n + = z n u _z m n m+ = z m n m u 0 :

3 (x,y) Fg.. The uncycle model. The robot s allowed to drve forwards or backwards and to spn about ts center axs. (x,y) θ Fg. 5. A uncycle wth a \vrtual" extenson, nterpreted as another axle added n front of the orgnal robot. From equaton (6), t s clear that the states at the bottoms of each chan, that s z 0 0 ; z n + ; : : : ; zm n m+ wll determne the traectores of all the states by the relatons z = _z + = _z0 0 : (7) 3.. Extendng the System wth \Vrtual" Tralers For some nsght nto the formulaton of vrtual axles, consder the smple example of a uncycle, sketched n Fgure. The knematc model takes as nputs the lnear velocty v and the angular velocty! of the uncycle, _x = cos v _y = sn v _ =! : θ ψ (8) Snce the system s drft-free, the relatve degree of any choce of outputs wll be equal to one. In partcular, the relatve degree of the body angle wth respect to the steerng nput s equal to one. Consder addng a new state _ = ; and a feedback! = tan(? ) v: The extended system (x; y; ; ) now satses the equatons _x = cos v _y = sn v (9) _ = tan(? ) v _ = ; and the added state can be nterpreted as the angle of another axle n front of the orgnal steerng wheel, and the new nput as the steerng velocty of ths \vrtual" wheel (see Fgure 5). The relatve degree of the body angle wth respect to the (vrtual) steerng nput s two. Remark. Any traectory = (x; y; ; ) of (9) can be proected down to gve a traectory () = = (x; y; ) of (8). Also, for any traectory of (8) for whch s C and for whch _ = 0 whenever _x = _y = 0, there exsts a traectory of (9) such that () =. Traectores where the uncycle spns about ts axs wthout movng ether forwards or backwards cannot be realzed wth the extended model. See (Isdor, 989) for a dscusson of relatve degree and nonlnear control theory Convertng the Mult-Steerng System nto Chaned Form The (x; y) poston of the last traler along wth all the htch angles f ; : : : ; m? g between steerng trans determne the entre state of the system, and are thus a canddate set of coordnates for the bottoms of the chans n the mult-nput chaned form (6); they are also one set of possble at outputs for ths system. The path taken by the last axle determnes the angle of the last axle by equatons ({): tan n m m = _y= _x. The (Cartesan) poston and angle of any axle wll determne the poston of the axle n front of t from the htch relatonshp. Thus, x; y; n m m determne the postons and angles of all the axles n the last steerng tran. Usng m?, the values for the second-tolast steerng tran can be found, and so forth. The front-most htch angle wll become the state at the bottom of the rst chan, zn. Its + relatve degree wth respect to the rst steerng nput! s equal to n +, one more than the number of axles n the rst steerng tran, and thus t wll need to be derentated a total of n + tmes n order to dene all the states z n the rst chan by equaton (7). However, snce _ depends on all the angles behnd t n the traler system accordng to equaton (), the relatve degree of wth respect to any of the other steerng nputs wll be equal to two. To ensure that the dervatves of these nputs do not appear n the coordnate transformaton, n vrtual axles can be added n front of each steerng axle n to? ncrease the relatve degree of wth respect to the other steerng nputs by n. After a smlar analyss for ; : : :; m? ; y, a total of n vrtual axles wll be added n front of the th steerng wheel, as n Fgure 6. The state varables that have been ntroduced, correspondng to the angles of these vrtual tralers, are denoted by. Ther dervatves are de- ned as f they were actual axles, _ = 0 ; _ = L sn(?? )v? ; (0) where L s an arbtrarly chosen postve parameter. The veloctes of the vrtual axles are de- ned n the same manner as the real axles, and the new nputs represent the angular velocty of the front car n each vrtual extenson. In an eort to wrte the knematc model n a compact form the followng vectors are ntroduced: m = [ ; : : : ; n ; ] = [ m ; : : : ; m n m ; y] = [ ; + ; : : : ; m ] : Another possble choce for the states at the bottoms of the chans (or the at outputs) are the (x; y) poston of the last traler along wth y values of the mdponts of the axles n front of each of the steerng wheels. The resultng chaned form s the same.

4 mth vrtual extenson θ m n m θ m n - m φ m- θn m m- θ m θ n + mth steerng tran m θ n θ n - second steerng tran θ frst vrtual extenson φ θ n θ frst steerng tran Fg. 6. The mult-steerng system, showng the vrtual axles that must be added to convert the system nto mult-nput chaned form. In general terms, the superscrpts () of the vectors refer to the th steerng tran and the subscrpts () refer to the tals of the steerng tran startng from the th traler (whch s real f n? and vrtual f 0 < n? ). The nput u 0 n the mult-nput chaned form of equaton (6) s the lnear velocty n the x drecton of the last body n the last steerng tran, v = cos m n m v m n m : () The lnear velocty at an axle can be wrtten as a functon of the states and the generatng nput: v = s ( )v : Recall that the dervatves of the angles have the same form for both actual (3) and vrtual (0) axles, and dene the functon f to be the dervatve of dvded by the velocty v, f ( )? = L tan(?? )s ( ) : () Let the functons f n + be the dervatves of the htch angles,, dvded by the velocty v; see equaton (). Fnally, equatng _y = fn m m+ v, we have from (): f m n m+ ( m n m ) = tan m n m : (3) By way of notaton, dene = [f ; : : :; f n + ] f F = [f ; f + ; : : : ; f m ]T so that the local knematc model wth dynamc feedback can now be wrtten compactly as _ 0 = ; () _ = F () 0 v (5) _x = v : (6) The rst chan has only one coordnate, z 0 0 = x : (7) The m th chan wll be the longest, wth z m n m+ = y : (8) The other chans have the htch angles at the bottom, z n + = ; (9) and the remanng coordnates are found through the relatonshp (7). Ths can be wrtten more speccally as follows. Recallng that the dervatves of ; : : : ; m? ; y, were dened as f n + t can be seen that the second-to-last coordnate n each chan wll be zn = f n + ( n ) : (0) The new coordnates have the general form = L F L F L F f + n n + ; () z? where L F h denotes the Le dervatve of the functon h along the vector F. The nput transformaton s dened by takng the dervatves of the rst states n the chans u = _z 0 () Theorem Let the coordnates z, be gven by (6{0) and the nputs u, be gven by (). Then the equatons (6) are satsed. Proof. The chaned form follows drectly from the dentons of the coordnates and nput transformaton along wth the knematc model (5). Ths coordnate transformaton has a trangular structure and ts Jacoban s nonsngular at at the orgn, whch mples that t s a local deomorphsm. The detals of the proof can be found n (Tlbury et al., 993a).. STEERING CHAINED FORM SYSTEMS Once a system s n mult-nput chaned form, many derent algorthms (three of whch are presented here) can be used to steer t. The basc dea behnd each of these methods s to parameterze the nput space, ntegrate the chaned form equatons symbolcally, and nally, solve for the nput parameters n terms of the desred ntal and nal states. No partcular system of tralers wll be consdered; nstead, the problem that s solved n ths secton s to nd nputs fu (t) : t [0; T ); = 0; : : :; mg whch wll steer the mult-chaned system (6) from a gven ntal state to a desred nal state... Steerng wth Polynomal Inputs One approach to the pont-to-pont steerng problem s to hold the rst nput u 0 dentcally equal to one over the entre traectory. The tme needed to steer s then determned from the change n the

5 z 0 0 coordnate, T = (z 0 0 )f? (z 0 0 ) : (3) The remanng nputs are parameterzed by Taylor polynomals, u = a 0 + a t + : : : + a n+t n+ u = b 0 + b t + : : : + b n+t n+ (). u m = 0 + t + : : : + nm+ t nm+ wth the number of parameters on each nput chosen to be equal to the number of states n ts chan. The chaned form equatons (6) can be ntegrated symbolcally and the nput parameters a ; b ; : : : ; can be found n terms of the ntal and nal states. All of the equatons that need to be solved are lnear. Of course, f the tme needed for steerng s zero from equaton (), then ths method wll not work. One way to remedy ths stuaton s to choose an ntermedate pont and plan the path n two peces... Steerng wth Pecewse Constant Inputs Ths steerng method was orgnally nspred by multrate dgtal control (Monaco and Normand- Cyrot, 99), but s most easly understood n terms of moton plannng smply as pecewse constant nputs. The rst nput u 0 s chosen to be constant over the entre traectory, and the other nputs are chosen to be pecewse constant, wth at least as many swtches as there are states n ts chan. The tme for the traectory s chosen arbtrarly as T. The reader s referred to (Tlbury et al., 993a) for more detals..3. Steerng wth Snusodal Inputs A method for steerng mult-chaned systems wth snusods was proposed n (Bushnell et al., 993), and requred one step to steer each level of the chan. Because of the many steps needed for steerng, the algorthm can be tedous to mplement n practce. An \all-at-once" snusods method, an extenson of that detaled n (Tlbury et al., 993b), has as nputs parameterzed sums of snusods at derent frequences. Agan, the chaned form equatons (6) can be ntegrated symbolcally, evaluated at tme T, and the parameters are found as a functon of the ntal and nal states. In ths case, ndng the nput parameters wll requre solvng nonlnear algebrac equatons. More detals on ths algorthm can be found n (Tlbury et al., 993a). 5. EXAMPLES Two examples wll be brey presented to llustrate the converson procedure. 5.. Fre Truck Example In (Bushnell et al., 993), t was shown that the re truck system could be converted nto a multnput chaned form. The bottoms of the chans n the chaned form (or equvalently the at outputs of the system) were chosen to to be the (x; y) poston of the passve axle along wth the angle of the traler (see Fgure 7), and because of the relatve smplcty of the three-axle system, that (x,y) θ φ L Fg. 7. A sketch of the re truck system showng the vrtual extenson that s added n front of the rear steerng wheel. The extra steerng wheel at the rear of the traler s used for mproved maneuverablty on narrow cty streets. (x,y) θ 3 L 3 L θ Fg. 8. The ve-axle, two-steerng system showng the vrtual extenson whch s added n front of the second steerng wheel. Such a system s envsoned as beng used where maneuverablty around narrow passageways n danger zones s of utmost mportance. choce allowed the knematc equatons to be put nto mult-nput chaned form wthout usng dynamc state feedback. Snce the re truck ts nto the class of mult-steerng traler systems, t can also be converted nto mult-nput chaned form usng the (x; y) poston of the last axle and the traler angle as the bottoms of the chans. One vrtual traler wll then need to be added, showng that although vrtual extenson s not always necessary, the procedure outlned n ths paper wll always result n a chaned form. 5.. Another Example Consder now a ve-axle system wth two steerng wheels, as depcted n Fgure 8. In eect, ths s a re truck wth two passve tralers. Usng the procedure outlned n Secton 3, choosng the bottoms of the chans as the (x; y) poston of the last axle and the htch angle, ths system can be converted nto mult-nput chaned form and steered usng one of the methods outlned n Secton. In fact, as has been recently proven n (Tlbury and Sastry, 99), there does not exst a transformaton nto chaned form for ths partcular ve-axle system wthout usng dynamc feedback. For detals of the knematc equatons and the transformaton for ths system, the reader s encouraged to consult (Tlbury et al., 993a) or to contact the rst author. Once the knematc equatons are n mult-nput chaned form, the system can be steered usng one of the algorthms dscussed n Secton. The system parameters are n = 3 (three passve axles) and m = (two steerng wheels); and for concreteness, let the lengths of the htches be L = L = L 3 = 5; L = 3, and L =. L θ L θ L θ 0 φ θ 0 L θ

6 Fg. 9. A parallel-parkng traectory for the ve-axle, two-steerng system. The plannng algorthm as descrbed n ths paper does not account for obstacle avodance; however, t does plan \nce" paths whch may can be used n conuncton wth an obstacle-avodance algorthm to acheve a complete soluton to the pathplannng problem. To steer the system from an ntal pont of (x; y) = (0; 0) to a nal pont of (x; y) = (0; 0) and all of the body angles (ncludng the vrtual angle) are algned wth the horzontal axs n both the ntal and nal conguratons, polynomal nputs are one possble choce for plannng the traectory n the chaned form coordnates. As noted n Secton., polynomal nputs are not mmedately suted to ths type of traectory snce the tme needed to steer the system, computed from equaton (), s zero and thus the algorthm fals. The traectory can be planned n two steps, usng as an ntermedate pont (x; y) = (30; 0), as shown n Fgure SUMMARY In ths paper, a systematc method for convertng the knematc model of a mult-traler system wth n passve tralers and m steerable cars nto a mult-nput chaned form was presented. Many algorthms for steerng systems n chaned form exst (three were descrbed here), and methods for stablzng systems n mult-nput chaned form have also been presented (Walsh and Bushnell, 993). The method for convertng the mult-traler system nto chaned form added vrtual axles to the system n a form of dynamc state feedback. Although the vrtual extenson was not always necessary, t provded a guaranteed method to convert all mult-steerng traler systems nto chaned form, and thus to nd feasble paths for these systems. Acknowledgements Ths research was supported n part by the NSF under grant IRI-9090 and by the ARO under grant FD-DAAL03. D. Tlbury would lke to acknowledge an AT&T Ph.D. Fellowshp for partal support of ths work. The research of O. Srdalen was supported n part by the Japan Socety of the Promoton of Scence and the Center of Martme Control Systems at NTH/Sntef, Norway. The authors would also lke to thank Greg Walsh for hs help n anmatng the smulatons for the vdeotape was presented at the conference. 7. REFERENCES Bushnell, L., D. Tlbury and S. S. Sastry (993). Steerng three-nput chaned form nonholonomc systems usng snusods: The retruck example. In: Proc. of the European Control Conf. pp. 3{37. Canudas de Wt, C. (993). Personal communcaton. Fless, M., J. Levne, P. Martn and P. Rouchon (99). Flatness and defect of nonlnear systems: Introductory theory and examples. Intl. J. of Control. To Appear. Gralt, G. (993). Personal communcaton. Isdor, A. (989). Nonlnear Control Systems. nd ed.. Sprnger-Verlag. Martn, P. and P. Rouchon (993). Systems wthout drft and atness. In: Math. Theory of Networks and Systems. To appear. Monaco, S. and D. Normand-Cyrot (99). An ntroducton to moton plannng under multrate dgtal control. In: Proc. of the IEEE Conf. on Decson and Control. pp. 780{785. Murray, R. M. (99). Nlpotent bases for a class of non-ntegrable dstrbutons wth applcatons to traectory generaton for nonholonomc systems. Math. of Control, Sgnals, and Systems : MCSS. In press. Murray, R. M. and S. S. Sastry (993). Nonholonomc moton plannng: Steerng usng snusods. IEEE Trans. on Auto. Control 38(5), 700{76. Rouchon, P., M. Fless, J. Levne and P. Martn (993). Flatness and moton plannng: the car wth n tralers. In: Proc. of the European Control Conf. pp. 58{5. Srdalen, O. J. (993). Converson of the knematcs of a car wth N tralers nto a chaned form. In: Proc. of the IEEE Intl. Conf. on Robotcs and Auto.. pp. 38{387. Tlbury, D. and A. Chelouah (993). Steerng a three-nput nonholonomc system usng multrate controls. In: Proc. of the European Control Conf. pp. 8{3. Tlbury, D. and S. Sastry (99). On goursat normal forms, prolongatons, and control systems. Tech. Report UCB/ERL M9/6. Unv. of Calforna, Berkeley. Tlbury, D., O. Srdalen, L. Bushnell and S. Sastry (993a). A mult-steerng traler system: Converson nto chaned form usng dynamc feedback. Tech. Report UCB/ERL M93/55. Unv. of Calforna, Berkeley. Tlbury, D., R. Murray and S. Sastry (993b). Traectory generaton for the N-traler problem usng Goursat normal form. In: Proc. of the IEEE Conf. on Decson and Control. pp. 97{977. To appear n IEEE Trans. on Auto. Control. Walsh, G. C. and L. G. Bushnell (993). Stablzaton of multple nput chaned form control systems. In: Proc. of the IEEE Conf. on Decson and Control. pp. 959{96.

Difference Equations

Difference Equations Dfference Equatons c Jan Vrbk 1 Bascs Suppose a sequence of numbers, say a 0,a 1,a,a 3,... s defned by a certan general relatonshp between, say, three consecutve values of the sequence, e.g. a + +3a +1

More information

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity Week3, Chapter 4 Moton n Two Dmensons Lecture Quz A partcle confned to moton along the x axs moves wth constant acceleraton from x =.0 m to x = 8.0 m durng a 1-s tme nterval. The velocty of the partcle

More information

Section 8.3 Polar Form of Complex Numbers

Section 8.3 Polar Form of Complex Numbers 80 Chapter 8 Secton 8 Polar Form of Complex Numbers From prevous classes, you may have encountered magnary numbers the square roots of negatve numbers and, more generally, complex numbers whch are the

More information

Physics 5153 Classical Mechanics. D Alembert s Principle and The Lagrangian-1

Physics 5153 Classical Mechanics. D Alembert s Principle and The Lagrangian-1 P. Guterrez Physcs 5153 Classcal Mechancs D Alembert s Prncple and The Lagrangan 1 Introducton The prncple of vrtual work provdes a method of solvng problems of statc equlbrum wthout havng to consder the

More information

EEE 241: Linear Systems

EEE 241: Linear Systems EEE : Lnear Systems Summary #: Backpropagaton BACKPROPAGATION The perceptron rule as well as the Wdrow Hoff learnng were desgned to tran sngle layer networks. They suffer from the same dsadvantage: they

More information

An Algorithm to Solve the Inverse Kinematics Problem of a Robotic Manipulator Based on Rotation Vectors

An Algorithm to Solve the Inverse Kinematics Problem of a Robotic Manipulator Based on Rotation Vectors An Algorthm to Solve the Inverse Knematcs Problem of a Robotc Manpulator Based on Rotaton Vectors Mohamad Z. Al-az*, Mazn Z. Othman**, and Baker B. Al-Bahr* *AL-Nahran Unversty, Computer Eng. Dep., Baghdad,

More information

Lecture 12: Discrete Laplacian

Lecture 12: Discrete Laplacian Lecture 12: Dscrete Laplacan Scrbe: Tanye Lu Our goal s to come up wth a dscrete verson of Laplacan operator for trangulated surfaces, so that we can use t n practce to solve related problems We are mostly

More information

Physics 5153 Classical Mechanics. Principle of Virtual Work-1

Physics 5153 Classical Mechanics. Principle of Virtual Work-1 P. Guterrez 1 Introducton Physcs 5153 Classcal Mechancs Prncple of Vrtual Work The frst varatonal prncple we encounter n mechancs s the prncple of vrtual work. It establshes the equlbrum condton of a mechancal

More information

Distributed Exponential Formation Control of Multiple Wheeled Mobile Robots

Distributed Exponential Formation Control of Multiple Wheeled Mobile Robots Proceedngs of the Internatonal Conference of Control, Dynamc Systems, and Robotcs Ottawa, Ontaro, Canada, May 15-16 214 Paper No. 46 Dstrbuted Exponental Formaton Control of Multple Wheeled Moble Robots

More information

Module 9. Lecture 6. Duality in Assignment Problems

Module 9. Lecture 6. Duality in Assignment Problems Module 9 1 Lecture 6 Dualty n Assgnment Problems In ths lecture we attempt to answer few other mportant questons posed n earler lecture for (AP) and see how some of them can be explaned through the concept

More information

12. The Hamilton-Jacobi Equation Michael Fowler

12. The Hamilton-Jacobi Equation Michael Fowler 1. The Hamlton-Jacob Equaton Mchael Fowler Back to Confguraton Space We ve establshed that the acton, regarded as a functon of ts coordnate endponts and tme, satsfes ( ) ( ) S q, t / t+ H qpt,, = 0, and

More information

Numerical Heat and Mass Transfer

Numerical Heat and Mass Transfer Master degree n Mechancal Engneerng Numercal Heat and Mass Transfer 06-Fnte-Dfference Method (One-dmensonal, steady state heat conducton) Fausto Arpno f.arpno@uncas.t Introducton Why we use models and

More information

Canonical transformations

Canonical transformations Canoncal transformatons November 23, 2014 Recall that we have defned a symplectc transformaton to be any lnear transformaton M A B leavng the symplectc form nvarant, Ω AB M A CM B DΩ CD Coordnate transformatons,

More information

CSci 6974 and ECSE 6966 Math. Tech. for Vision, Graphics and Robotics Lecture 21, April 17, 2006 Estimating A Plane Homography

CSci 6974 and ECSE 6966 Math. Tech. for Vision, Graphics and Robotics Lecture 21, April 17, 2006 Estimating A Plane Homography CSc 6974 and ECSE 6966 Math. Tech. for Vson, Graphcs and Robotcs Lecture 21, Aprl 17, 2006 Estmatng A Plane Homography Overvew We contnue wth a dscusson of the major ssues, usng estmaton of plane projectve

More information

Iterative General Dynamic Model for Serial-Link Manipulators

Iterative General Dynamic Model for Serial-Link Manipulators EEL6667: Knematcs, Dynamcs and Control of Robot Manpulators 1. Introducton Iteratve General Dynamc Model for Seral-Lnk Manpulators In ths set of notes, we are gong to develop a method for computng a general

More information

CHAPTER 6. LAGRANGE S EQUATIONS (Analytical Mechanics)

CHAPTER 6. LAGRANGE S EQUATIONS (Analytical Mechanics) CHAPTER 6 LAGRANGE S EQUATIONS (Analytcal Mechancs) 1 Ex. 1: Consder a partcle movng on a fxed horzontal surface. r P Let, be the poston and F be the total force on the partcle. The FBD s: -mgk F 1 x O

More information

Assortment Optimization under MNL

Assortment Optimization under MNL Assortment Optmzaton under MNL Haotan Song Aprl 30, 2017 1 Introducton The assortment optmzaton problem ams to fnd the revenue-maxmzng assortment of products to offer when the prces of products are fxed.

More information

Integrals and Invariants of Euler-Lagrange Equations

Integrals and Invariants of Euler-Lagrange Equations Lecture 16 Integrals and Invarants of Euler-Lagrange Equatons ME 256 at the Indan Insttute of Scence, Bengaluru Varatonal Methods and Structural Optmzaton G. K. Ananthasuresh Professor, Mechancal Engneerng,

More information

Lesson 5: Kinematics and Dynamics of Particles

Lesson 5: Kinematics and Dynamics of Particles Lesson 5: Knematcs and Dynamcs of Partcles hs set of notes descrbes the basc methodology for formulatng the knematc and knetc equatons for multbody dynamcs. In order to concentrate on the methodology and

More information

Moments of Inertia. and reminds us of the analogous equation for linear momentum p= mv, which is of the form. The kinetic energy of the body is.

Moments of Inertia. and reminds us of the analogous equation for linear momentum p= mv, which is of the form. The kinetic energy of the body is. Moments of Inerta Suppose a body s movng on a crcular path wth constant speed Let s consder two quanttes: the body s angular momentum L about the center of the crcle, and ts knetc energy T How are these

More information

Snce h( q^; q) = hq ~ and h( p^ ; p) = hp, one can wrte ~ h hq hp = hq ~hp ~ (7) the uncertanty relaton for an arbtrary state. The states that mnmze t

Snce h( q^; q) = hq ~ and h( p^ ; p) = hp, one can wrte ~ h hq hp = hq ~hp ~ (7) the uncertanty relaton for an arbtrary state. The states that mnmze t 8.5: Many-body phenomena n condensed matter and atomc physcs Last moded: September, 003 Lecture. Squeezed States In ths lecture we shall contnue the dscusson of coherent states, focusng on ther propertes

More information

coordinates. Then, the position vectors are described by

coordinates. Then, the position vectors are described by Revewng, what we have dscussed so far: Generalzed coordnates Any number of varables (say, n) suffcent to specfy the confguraton of the system at each nstant to tme (need not be the mnmum number). In general,

More information

DO NOT DO HOMEWORK UNTIL IT IS ASSIGNED. THE ASSIGNMENTS MAY CHANGE UNTIL ANNOUNCED.

DO NOT DO HOMEWORK UNTIL IT IS ASSIGNED. THE ASSIGNMENTS MAY CHANGE UNTIL ANNOUNCED. EE 539 Homeworks Sprng 08 Updated: Tuesday, Aprl 7, 08 DO NOT DO HOMEWORK UNTIL IT IS ASSIGNED. THE ASSIGNMENTS MAY CHANGE UNTIL ANNOUNCED. For full credt, show all work. Some problems requre hand calculatons.

More information

Physics 2A Chapters 6 - Work & Energy Fall 2017

Physics 2A Chapters 6 - Work & Energy Fall 2017 Physcs A Chapters 6 - Work & Energy Fall 017 These notes are eght pages. A quck summary: The work-energy theorem s a combnaton o Chap and Chap 4 equatons. Work s dened as the product o the orce actng on

More information

Fundamental loop-current method using virtual voltage sources technique for special cases

Fundamental loop-current method using virtual voltage sources technique for special cases Fundamental loop-current method usng vrtual voltage sources technque for specal cases George E. Chatzaraks, 1 Marna D. Tortorel 1 and Anastasos D. Tzolas 1 Electrcal and Electroncs Engneerng Departments,

More information

χ x B E (c) Figure 2.1.1: (a) a material particle in a body, (b) a place in space, (c) a configuration of the body

χ x B E (c) Figure 2.1.1: (a) a material particle in a body, (b) a place in space, (c) a configuration of the body Secton.. Moton.. The Materal Body and Moton hyscal materals n the real world are modeled usng an abstract mathematcal entty called a body. Ths body conssts of an nfnte number of materal partcles. Shown

More information

Lecture 10 Support Vector Machines II

Lecture 10 Support Vector Machines II Lecture 10 Support Vector Machnes II 22 February 2016 Taylor B. Arnold Yale Statstcs STAT 365/665 1/28 Notes: Problem 3 s posted and due ths upcomng Frday There was an early bug n the fake-test data; fxed

More information

Additional Codes using Finite Difference Method. 1 HJB Equation for Consumption-Saving Problem Without Uncertainty

Additional Codes using Finite Difference Method. 1 HJB Equation for Consumption-Saving Problem Without Uncertainty Addtonal Codes usng Fnte Dfference Method Benamn Moll 1 HJB Equaton for Consumpton-Savng Problem Wthout Uncertanty Before consderng the case wth stochastc ncome n http://www.prnceton.edu/~moll/ HACTproect/HACT_Numercal_Appendx.pdf,

More information

Finite Element Modelling of truss/cable structures

Finite Element Modelling of truss/cable structures Pet Schreurs Endhoven Unversty of echnology Department of Mechancal Engneerng Materals echnology November 3, 214 Fnte Element Modellng of truss/cable structures 1 Fnte Element Analyss of prestressed structures

More information

Polynomial Regression Models

Polynomial Regression Models LINEAR REGRESSION ANALYSIS MODULE XII Lecture - 6 Polynomal Regresson Models Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur Test of sgnfcance To test the sgnfcance

More information

PHYS 705: Classical Mechanics. Calculus of Variations II

PHYS 705: Classical Mechanics. Calculus of Variations II 1 PHYS 705: Classcal Mechancs Calculus of Varatons II 2 Calculus of Varatons: Generalzaton (no constrant yet) Suppose now that F depends on several dependent varables : We need to fnd such that has a statonary

More information

Important Instructions to the Examiners:

Important Instructions to the Examiners: Summer 0 Examnaton Subject & Code: asc Maths (70) Model Answer Page No: / Important Instructons to the Examners: ) The Answers should be examned by key words and not as word-to-word as gven n the model

More information

Controller Design of High Order Nonholonomic System with Nonlinear Drifts

Controller Design of High Order Nonholonomic System with Nonlinear Drifts Internatonal Journal of Automaton and Computng 6(3, August 9, 4-44 DOI:.7/s633-9-4- Controller Desgn of Hgh Order Nonholonomc System wth Nonlnear Drfts Xu-Yun Zheng Yu-Qang Wu Research Insttute of Automaton,

More information

The Geometry of Logit and Probit

The Geometry of Logit and Probit The Geometry of Logt and Probt Ths short note s meant as a supplement to Chapters and 3 of Spatal Models of Parlamentary Votng and the notaton and reference to fgures n the text below s to those two chapters.

More information

Mathematical Preparations

Mathematical Preparations 1 Introducton Mathematcal Preparatons The theory of relatvty was developed to explan experments whch studed the propagaton of electromagnetc radaton n movng coordnate systems. Wthn expermental error the

More information

Salmon: Lectures on partial differential equations. Consider the general linear, second-order PDE in the form. ,x 2

Salmon: Lectures on partial differential equations. Consider the general linear, second-order PDE in the form. ,x 2 Salmon: Lectures on partal dfferental equatons 5. Classfcaton of second-order equatons There are general methods for classfyng hgher-order partal dfferental equatons. One s very general (applyng even to

More information

Temperature. Chapter Heat Engine

Temperature. Chapter Heat Engine Chapter 3 Temperature In prevous chapters of these notes we ntroduced the Prncple of Maxmum ntropy as a technque for estmatng probablty dstrbutons consstent wth constrants. In Chapter 9 we dscussed the

More information

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module 3 LOSSY IMAGE COMPRESSION SYSTEMS Verson ECE IIT, Kharagpur Lesson 6 Theory of Quantzaton Verson ECE IIT, Kharagpur Instructonal Objectves At the end of ths lesson, the students should be able to:

More information

Inner Product. Euclidean Space. Orthonormal Basis. Orthogonal

Inner Product. Euclidean Space. Orthonormal Basis. Orthogonal Inner Product Defnton 1 () A Eucldean space s a fnte-dmensonal vector space over the reals R, wth an nner product,. Defnton 2 (Inner Product) An nner product, on a real vector space X s a symmetrc, blnear,

More information

For now, let us focus on a specific model of neurons. These are simplified from reality but can achieve remarkable results.

For now, let us focus on a specific model of neurons. These are simplified from reality but can achieve remarkable results. Neural Networks : Dervaton compled by Alvn Wan from Professor Jtendra Malk s lecture Ths type of computaton s called deep learnng and s the most popular method for many problems, such as computer vson

More information

MEV442 Introduction to Robotics Module 2. Dr. Santhakumar Mohan Assistant Professor Mechanical Engineering National Institute of Technology Calicut

MEV442 Introduction to Robotics Module 2. Dr. Santhakumar Mohan Assistant Professor Mechanical Engineering National Institute of Technology Calicut MEV442 Introducton to Robotcs Module 2 Dr. Santhakumar Mohan Assstant Professor Mechancal Engneerng Natonal Insttute of Technology Calcut Jacobans: Veloctes and statc forces Introducton Notaton for tme-varyng

More information

Irregular vibrations in multi-mass discrete-continuous systems torsionally deformed

Irregular vibrations in multi-mass discrete-continuous systems torsionally deformed (2) 4 48 Irregular vbratons n mult-mass dscrete-contnuous systems torsonally deformed Abstract In the paper rregular vbratons of dscrete-contnuous systems consstng of an arbtrary number rgd bodes connected

More information

Physics 53. Rotational Motion 3. Sir, I have found you an argument, but I am not obliged to find you an understanding.

Physics 53. Rotational Motion 3. Sir, I have found you an argument, but I am not obliged to find you an understanding. Physcs 53 Rotatonal Moton 3 Sr, I have found you an argument, but I am not oblged to fnd you an understandng. Samuel Johnson Angular momentum Wth respect to rotatonal moton of a body, moment of nerta plays

More information

Formulas for the Determinant

Formulas for the Determinant page 224 224 CHAPTER 3 Determnants e t te t e 2t 38 A = e t 2te t e 2t e t te t 2e 2t 39 If 123 A = 345, 456 compute the matrx product A adj(a) What can you conclude about det(a)? For Problems 40 43, use

More information

The equation of motion of a dynamical system is given by a set of differential equations. That is (1)

The equation of motion of a dynamical system is given by a set of differential equations. That is (1) Dynamcal Systems Many engneerng and natural systems are dynamcal systems. For example a pendulum s a dynamcal system. State l The state of the dynamcal system specfes t condtons. For a pendulum n the absence

More information

Week 5: Neural Networks

Week 5: Neural Networks Week 5: Neural Networks Instructor: Sergey Levne Neural Networks Summary In the prevous lecture, we saw how we can construct neural networks by extendng logstc regresson. Neural networks consst of multple

More information

PHYS 705: Classical Mechanics. Newtonian Mechanics

PHYS 705: Classical Mechanics. Newtonian Mechanics 1 PHYS 705: Classcal Mechancs Newtonan Mechancs Quck Revew of Newtonan Mechancs Basc Descrpton: -An dealzed pont partcle or a system of pont partcles n an nertal reference frame [Rgd bodes (ch. 5 later)]

More information

COMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD

COMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD COMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD Ákos Jósef Lengyel, István Ecsed Assstant Lecturer, Professor of Mechancs, Insttute of Appled Mechancs, Unversty of Mskolc, Mskolc-Egyetemváros,

More information

Structure and Drive Paul A. Jensen Copyright July 20, 2003

Structure and Drive Paul A. Jensen Copyright July 20, 2003 Structure and Drve Paul A. Jensen Copyrght July 20, 2003 A system s made up of several operatons wth flow passng between them. The structure of the system descrbes the flow paths from nputs to outputs.

More information

MAE140 - Linear Circuits - Winter 16 Final, March 16, 2016

MAE140 - Linear Circuits - Winter 16 Final, March 16, 2016 ME140 - Lnear rcuts - Wnter 16 Fnal, March 16, 2016 Instructons () The exam s open book. You may use your class notes and textbook. You may use a hand calculator wth no communcaton capabltes. () You have

More information

College of Computer & Information Science Fall 2009 Northeastern University 20 October 2009

College of Computer & Information Science Fall 2009 Northeastern University 20 October 2009 College of Computer & Informaton Scence Fall 2009 Northeastern Unversty 20 October 2009 CS7880: Algorthmc Power Tools Scrbe: Jan Wen and Laura Poplawsk Lecture Outlne: Prmal-dual schema Network Desgn:

More information

Indeterminate pin-jointed frames (trusses)

Indeterminate pin-jointed frames (trusses) Indetermnate pn-jonted frames (trusses) Calculaton of member forces usng force method I. Statcal determnacy. The degree of freedom of any truss can be derved as: w= k d a =, where k s the number of all

More information

CHAPTER 4. Vector Spaces

CHAPTER 4. Vector Spaces man 2007/2/16 page 234 CHAPTER 4 Vector Spaces To crtcze mathematcs for ts abstracton s to mss the pont entrel. Abstracton s what makes mathematcs work. Ian Stewart The man am of ths tet s to stud lnear

More information

Physics 2A Chapter 3 HW Solutions

Physics 2A Chapter 3 HW Solutions Phscs A Chapter 3 HW Solutons Chapter 3 Conceptual Queston: 4, 6, 8, Problems: 5,, 8, 7, 3, 44, 46, 69, 70, 73 Q3.4. Reason: (a) C = A+ B onl A and B are n the same drecton. Sze does not matter. (b) C

More information

1 GSW Iterative Techniques for y = Ax

1 GSW Iterative Techniques for y = Ax 1 for y = A I m gong to cheat here. here are a lot of teratve technques that can be used to solve the general case of a set of smultaneous equatons (wrtten n the matr form as y = A), but ths chapter sn

More information

Module 3: Element Properties Lecture 1: Natural Coordinates

Module 3: Element Properties Lecture 1: Natural Coordinates Module 3: Element Propertes Lecture : Natural Coordnates Natural coordnate system s bascally a local coordnate system whch allows the specfcaton of a pont wthn the element by a set of dmensonless numbers

More information

The Feynman path integral

The Feynman path integral The Feynman path ntegral Aprl 3, 205 Hesenberg and Schrödnger pctures The Schrödnger wave functon places the tme dependence of a physcal system n the state, ψ, t, where the state s a vector n Hlbert space

More information

Solution Thermodynamics

Solution Thermodynamics Soluton hermodynamcs usng Wagner Notaton by Stanley. Howard Department of aterals and etallurgcal Engneerng South Dakota School of nes and echnology Rapd Cty, SD 57701 January 7, 001 Soluton hermodynamcs

More information

36.1 Why is it important to be able to find roots to systems of equations? Up to this point, we have discussed how to find the solution to

36.1 Why is it important to be able to find roots to systems of equations? Up to this point, we have discussed how to find the solution to ChE Lecture Notes - D. Keer, 5/9/98 Lecture 6,7,8 - Rootndng n systems o equatons (A) Theory (B) Problems (C) MATLAB Applcatons Tet: Supplementary notes rom Instructor 6. Why s t mportant to be able to

More information

Graph Reconstruction by Permutations

Graph Reconstruction by Permutations Graph Reconstructon by Permutatons Perre Ille and Wllam Kocay* Insttut de Mathémathques de Lumny CNRS UMR 6206 163 avenue de Lumny, Case 907 13288 Marselle Cedex 9, France e-mal: lle@ml.unv-mrs.fr Computer

More information

SCALARS AND VECTORS All physical quantities in engineering mechanics are measured using either scalars or vectors.

SCALARS AND VECTORS All physical quantities in engineering mechanics are measured using either scalars or vectors. SCALARS AND ECTORS All phscal uanttes n engneerng mechancs are measured usng ether scalars or vectors. Scalar. A scalar s an postve or negatve phscal uantt that can be completel specfed b ts magntude.

More information

PHYS 705: Classical Mechanics. Hamilton-Jacobi Equation

PHYS 705: Classical Mechanics. Hamilton-Jacobi Equation 1 PHYS 705: Classcal Mechancs Hamlton-Jacob Equaton Hamlton-Jacob Equaton There s also a very elegant relaton between the Hamltonan Formulaton of Mechancs and Quantum Mechancs. To do that, we need to derve

More information

CHAPTER 14 GENERAL PERTURBATION THEORY

CHAPTER 14 GENERAL PERTURBATION THEORY CHAPTER 4 GENERAL PERTURBATION THEORY 4 Introducton A partcle n orbt around a pont mass or a sphercally symmetrc mass dstrbuton s movng n a gravtatonal potental of the form GM / r In ths potental t moves

More information

Module 2. Random Processes. Version 2 ECE IIT, Kharagpur

Module 2. Random Processes. Version 2 ECE IIT, Kharagpur Module Random Processes Lesson 6 Functons of Random Varables After readng ths lesson, ou wll learn about cdf of functon of a random varable. Formula for determnng the pdf of a random varable. Let, X be

More information

Psychology 282 Lecture #24 Outline Regression Diagnostics: Outliers

Psychology 282 Lecture #24 Outline Regression Diagnostics: Outliers Psychology 282 Lecture #24 Outlne Regresson Dagnostcs: Outlers In an earler lecture we studed the statstcal assumptons underlyng the regresson model, ncludng the followng ponts: Formal statement of assumptons.

More information

Army Ants Tunneling for Classical Simulations

Army Ants Tunneling for Classical Simulations Electronc Supplementary Materal (ESI) for Chemcal Scence. Ths journal s The Royal Socety of Chemstry 2014 electronc supplementary nformaton (ESI) for Chemcal Scence Army Ants Tunnelng for Classcal Smulatons

More information

Spring Force and Power

Spring Force and Power Lecture 13 Chapter 9 Sprng Force and Power Yeah, energy s better than orces. What s net? Course webste: http://aculty.uml.edu/andry_danylov/teachng/physcsi IN THIS CHAPTER, you wll learn how to solve problems

More information

EN40: Dynamics and Vibrations. Homework 7: Rigid Body Kinematics

EN40: Dynamics and Vibrations. Homework 7: Rigid Body Kinematics N40: ynamcs and Vbratons Homewor 7: Rgd Body Knematcs School of ngneerng Brown Unversty 1. In the fgure below, bar AB rotates counterclocwse at 4 rad/s. What are the angular veloctes of bars BC and C?.

More information

Design and Optimization of Fuzzy Controller for Inverse Pendulum System Using Genetic Algorithm

Design and Optimization of Fuzzy Controller for Inverse Pendulum System Using Genetic Algorithm Desgn and Optmzaton of Fuzzy Controller for Inverse Pendulum System Usng Genetc Algorthm H. Mehraban A. Ashoor Unversty of Tehran Unversty of Tehran h.mehraban@ece.ut.ac.r a.ashoor@ece.ut.ac.r Abstract:

More information

10. Canonical Transformations Michael Fowler

10. Canonical Transformations Michael Fowler 10. Canoncal Transformatons Mchael Fowler Pont Transformatons It s clear that Lagrange s equatons are correct for any reasonable choce of parameters labelng the system confguraton. Let s call our frst

More information

princeton univ. F 17 cos 521: Advanced Algorithm Design Lecture 7: LP Duality Lecturer: Matt Weinberg

princeton univ. F 17 cos 521: Advanced Algorithm Design Lecture 7: LP Duality Lecturer: Matt Weinberg prnceton unv. F 17 cos 521: Advanced Algorthm Desgn Lecture 7: LP Dualty Lecturer: Matt Wenberg Scrbe: LP Dualty s an extremely useful tool for analyzng structural propertes of lnear programs. Whle there

More information

U.C. Berkeley CS294: Beyond Worst-Case Analysis Luca Trevisan September 5, 2017

U.C. Berkeley CS294: Beyond Worst-Case Analysis Luca Trevisan September 5, 2017 U.C. Berkeley CS94: Beyond Worst-Case Analyss Handout 4s Luca Trevsan September 5, 07 Summary of Lecture 4 In whch we ntroduce semdefnte programmng and apply t to Max Cut. Semdefnte Programmng Recall that

More information

1 Matrix representations of canonical matrices

1 Matrix representations of canonical matrices 1 Matrx representatons of canoncal matrces 2-d rotaton around the orgn: ( ) cos θ sn θ R 0 = sn θ cos θ 3-d rotaton around the x-axs: R x = 1 0 0 0 cos θ sn θ 0 sn θ cos θ 3-d rotaton around the y-axs:

More information

Physics 111: Mechanics Lecture 11

Physics 111: Mechanics Lecture 11 Physcs 111: Mechancs Lecture 11 Bn Chen NJIT Physcs Department Textbook Chapter 10: Dynamcs of Rotatonal Moton q 10.1 Torque q 10. Torque and Angular Acceleraton for a Rgd Body q 10.3 Rgd-Body Rotaton

More information

Note on EM-training of IBM-model 1

Note on EM-training of IBM-model 1 Note on EM-tranng of IBM-model INF58 Language Technologcal Applcatons, Fall The sldes on ths subject (nf58 6.pdf) ncludng the example seem nsuffcent to gve a good grasp of what s gong on. Hence here are

More information

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system Transfer Functons Convenent representaton of a lnear, dynamc model. A transfer functon (TF) relates one nput and one output: x t X s y t system Y s The followng termnology s used: x y nput output forcng

More information

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X Statstcs 1: Probablty Theory II 37 3 EPECTATION OF SEVERAL RANDOM VARIABLES As n Probablty Theory I, the nterest n most stuatons les not on the actual dstrbuton of a random vector, but rather on a number

More information

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix Lectures - Week 4 Matrx norms, Condtonng, Vector Spaces, Lnear Independence, Spannng sets and Bass, Null space and Range of a Matrx Matrx Norms Now we turn to assocatng a number to each matrx. We could

More information

Problem Set 9 Solutions

Problem Set 9 Solutions Desgn and Analyss of Algorthms May 4, 2015 Massachusetts Insttute of Technology 6.046J/18.410J Profs. Erk Demane, Srn Devadas, and Nancy Lynch Problem Set 9 Solutons Problem Set 9 Solutons Ths problem

More information

Linear Feature Engineering 11

Linear Feature Engineering 11 Lnear Feature Engneerng 11 2 Least-Squares 2.1 Smple least-squares Consder the followng dataset. We have a bunch of nputs x and correspondng outputs y. The partcular values n ths dataset are x y 0.23 0.19

More information

Affine transformations and convexity

Affine transformations and convexity Affne transformatons and convexty The purpose of ths document s to prove some basc propertes of affne transformatons nvolvng convex sets. Here are a few onlne references for background nformaton: http://math.ucr.edu/

More information

Kernel Methods and SVMs Extension

Kernel Methods and SVMs Extension Kernel Methods and SVMs Extenson The purpose of ths document s to revew materal covered n Machne Learnng 1 Supervsed Learnng regardng support vector machnes (SVMs). Ths document also provdes a general

More information

20. Mon, Oct. 13 What we have done so far corresponds roughly to Chapters 2 & 3 of Lee. Now we turn to Chapter 4. The first idea is connectedness.

20. Mon, Oct. 13 What we have done so far corresponds roughly to Chapters 2 & 3 of Lee. Now we turn to Chapter 4. The first idea is connectedness. 20. Mon, Oct. 13 What we have done so far corresponds roughly to Chapters 2 & 3 of Lee. Now we turn to Chapter 4. The frst dea s connectedness. Essentally, we want to say that a space cannot be decomposed

More information

Poisson brackets and canonical transformations

Poisson brackets and canonical transformations rof O B Wrght Mechancs Notes osson brackets and canoncal transformatons osson Brackets Consder an arbtrary functon f f ( qp t) df f f f q p q p t But q p p where ( qp ) pq q df f f f p q q p t In order

More information

ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM

ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM An elastc wave s a deformaton of the body that travels throughout the body n all drectons. We can examne the deformaton over a perod of tme by fxng our look

More information

9 Characteristic classes

9 Characteristic classes THEODORE VORONOV DIFFERENTIAL GEOMETRY. Sprng 2009 [under constructon] 9 Characterstc classes 9.1 The frst Chern class of a lne bundle Consder a complex vector bundle E B of rank p. We shall construct

More information

C/CS/Phy191 Problem Set 3 Solutions Out: Oct 1, 2008., where ( 00. ), so the overall state of the system is ) ( ( ( ( 00 ± 11 ), Φ ± = 1

C/CS/Phy191 Problem Set 3 Solutions Out: Oct 1, 2008., where ( 00. ), so the overall state of the system is ) ( ( ( ( 00 ± 11 ), Φ ± = 1 C/CS/Phy9 Problem Set 3 Solutons Out: Oct, 8 Suppose you have two qubts n some arbtrary entangled state ψ You apply the teleportaton protocol to each of the qubts separately What s the resultng state obtaned

More information

Report on Image warping

Report on Image warping Report on Image warpng Xuan Ne, Dec. 20, 2004 Ths document summarzed the algorthms of our mage warpng soluton for further study, and there s a detaled descrpton about the mplementaton of these algorthms.

More information

= = = (a) Use the MATLAB command rref to solve the system. (b) Let A be the coefficient matrix and B be the right-hand side of the system.

= = = (a) Use the MATLAB command rref to solve the system. (b) Let A be the coefficient matrix and B be the right-hand side of the system. Chapter Matlab Exercses Chapter Matlab Exercses. Consder the lnear system of Example n Secton.. x x x y z y y z (a) Use the MATLAB command rref to solve the system. (b) Let A be the coeffcent matrx and

More information

11. Dynamics in Rotating Frames of Reference

11. Dynamics in Rotating Frames of Reference Unversty of Rhode Island DgtalCommons@URI Classcal Dynamcs Physcs Course Materals 2015 11. Dynamcs n Rotatng Frames of Reference Gerhard Müller Unversty of Rhode Island, gmuller@ur.edu Creatve Commons

More information

Advanced Circuits Topics - Part 1 by Dr. Colton (Fall 2017)

Advanced Circuits Topics - Part 1 by Dr. Colton (Fall 2017) Advanced rcuts Topcs - Part by Dr. olton (Fall 07) Part : Some thngs you should already know from Physcs 0 and 45 These are all thngs that you should have learned n Physcs 0 and/or 45. Ths secton s organzed

More information

Part C Dynamics and Statics of Rigid Body. Chapter 5 Rotation of a Rigid Body About a Fixed Axis

Part C Dynamics and Statics of Rigid Body. Chapter 5 Rotation of a Rigid Body About a Fixed Axis Part C Dynamcs and Statcs of Rgd Body Chapter 5 Rotaton of a Rgd Body About a Fxed Axs 5.. Rotatonal Varables 5.. Rotaton wth Constant Angular Acceleraton 5.3. Knetc Energy of Rotaton, Rotatonal Inerta

More information

Introduction to Vapor/Liquid Equilibrium, part 2. Raoult s Law:

Introduction to Vapor/Liquid Equilibrium, part 2. Raoult s Law: CE304, Sprng 2004 Lecture 4 Introducton to Vapor/Lqud Equlbrum, part 2 Raoult s Law: The smplest model that allows us do VLE calculatons s obtaned when we assume that the vapor phase s an deal gas, and

More information

Online Appendix. t=1 (p t w)q t. Then the first order condition shows that

Online Appendix. t=1 (p t w)q t. Then the first order condition shows that Artcle forthcomng to ; manuscrpt no (Please, provde the manuscrpt number!) 1 Onlne Appendx Appendx E: Proofs Proof of Proposton 1 Frst we derve the equlbrum when the manufacturer does not vertcally ntegrate

More information

Foundations of Arithmetic

Foundations of Arithmetic Foundatons of Arthmetc Notaton We shall denote the sum and product of numbers n the usual notaton as a 2 + a 2 + a 3 + + a = a, a 1 a 2 a 3 a = a The notaton a b means a dvdes b,.e. ac = b where c s an

More information

A particle in a state of uniform motion remain in that state of motion unless acted upon by external force.

A particle in a state of uniform motion remain in that state of motion unless acted upon by external force. The fundamental prncples of classcal mechancs were lad down by Galleo and Newton n the 16th and 17th centures. In 1686, Newton wrote the Prncpa where he gave us three laws of moton, one law of gravty,

More information

Scroll Generation with Inductorless Chua s Circuit and Wien Bridge Oscillator

Scroll Generation with Inductorless Chua s Circuit and Wien Bridge Oscillator Latest Trends on Crcuts, Systems and Sgnals Scroll Generaton wth Inductorless Chua s Crcut and Wen Brdge Oscllator Watcharn Jantanate, Peter A. Chayasena, and Sarawut Sutorn * Abstract An nductorless Chua

More information

Note 10. Modeling and Simulation of Dynamic Systems

Note 10. Modeling and Simulation of Dynamic Systems Lecture Notes of ME 475: Introducton to Mechatroncs Note 0 Modelng and Smulaton of Dynamc Systems Department of Mechancal Engneerng, Unversty Of Saskatchewan, 57 Campus Drve, Saskatoon, SK S7N 5A9, Canada

More information

Integrals and Invariants of

Integrals and Invariants of Lecture 16 Integrals and Invarants of Euler Lagrange Equatons NPTEL Course Varatonal Methods and Structural Optmzaton G. K. Ananthasuresh Professor, Mechancal Engneerng, Indan Insttute of Scence, Banagalore

More information

Physics 181. Particle Systems

Physics 181. Particle Systems Physcs 181 Partcle Systems Overvew In these notes we dscuss the varables approprate to the descrpton of systems of partcles, ther defntons, ther relatons, and ther conservatons laws. We consder a system

More information