Dynamic Programming for Trajectory Optimization of Engine-out Transportation Aircraft

Size: px
Start display at page:

Download "Dynamic Programming for Trajectory Optimization of Engine-out Transportation Aircraft"

Transcription

1 Dynmic Progrmming for Trjectory Optimiztion of Engine-out Trnporttion Aircrft Hongying Wu, Nyibe Chio Cho, Hkim Boudi *, Lunlong Zhong *, Felix Mor-Cmino * *LARA, ENAC, Touloue 355,Frnce E-mil: whyhgh@hotmil.com, hkimboudi@yhoo.fr, lunlong.zhong@enc.fr, morcmino@hotmil.fr # Progrm de Ingenierí Mectrónic, UnB, Bucrmng, Colombi nchio@unb.edu.co Abtrct: The purpoe of thi communiction i to contribute to the development of new trjectory mngement cpbility for n engine-out trnporttion ircrft. Engine-out i drmtic itution for flight fety nd thi tudy focue on the deign of mngement ytem for emergency trjectorie t thi pecil itution. Firt the gliding chrcteritic nd flying qulitie of trnport ircrft with totl engine filure re nlyzed while gliding rnge etimtion i conidered. Then new repreenttion of the flight dynmic of n engine-out ircrft i propoed where the pce vrible i choen independent prmeter inted of the time vrible. Thi llow to propoe new formultion of the correponding trjectory optimiztion problem nd to develop revere dynmic progrmming olution technique. Simultion reult re diplyed nd new development perpective re dicued. Key Word: Flight Sfety, Trjectory Optimiztion, Qui Stedy Glide, Revere Dynmic Progrmming INTRODUCTION The filure of engine i drmtic event for ir flight fety nd mny incident nd ccident re reulting from engine filure. Here n undeirble nd very pecil ce, ll engine out t given point of the flight, i conidered. Thi itution my led to crh unle flyble decent trjectory towrd fe lnding plce i performed. There re mny different reon for engine-out while it pper tht in thi itution ny wrong deciion mde by the pilot my led to cttrophic conequence. So it look quite deirble to develop n emergency guidnce mode for thi itution. Thi new functionlity could be integrted in Flight Mngement Sytem which hould be ble to elect proper lnding ite nd propoe feible trjectory towrd thi ite. To chieve thi purpoe there re mjor tep which hould be performed: etblih nd nlyze the flight dynmic of n ir trnporttion ircrft with totl engine filure (power off, tudy the gliding chrcteritic nd flying qulitie of trnporttion ircrft, develop method to etblih fe rechble re from given itution nd finlly develop method to optimize gliding trjectory towrd poible fe lnding plce. In thi tudy, it i uppoed tht engine out occur once the ircrft h lredy gined ome peed nd ltitude fter tke-off.. Only glide of engine-out irplne in the verticl plne i conidered trt //$6. c IEEE 98 ENGINE OUT FLIGHT DYNAMICS To etblih nd nlyze the flight dynmic of n ir trnporttion ircrft with totl engine filure (power off, the clicl eqution of flight hould be lightly dpted to thi prticulr ce. The erodynmic force (drg D, lift L, nd ide force Y re defined in term of dynmic preure, reference re nd dimenionle erodynmic coefficient []: D / V S C D,, M (- e / V S C L, M (- L, Y / V S CY, r, p, r, M (-3 Here V i the irpeed, i the ir denity (kg/m 3, i the ngle of ttck, e i the elevtor deflection, p i the ircrft roll rte, r i the yw rte nd M i the current Mch number, C D, CL nd CY re dimenionle erodynmic coefficient. C D nd C L re uppoed relted by the polr model CD CD ' K CL where K i contnt. It i conidered tht ome hydrulic power remin vilble to ctivte the elevtor, ileron nd rudder erodynmic urfce, o tht dynmic tbility well ttitude control cn till be performed by the flight control ytem. Indeed, mny trnport ircrft re equipped with n deployble uxiliry turbine (RAM which llow inuring in the control chnnel of the ircrft the vilbility of reidul hydrulic power. While the dditionl drg generted by the RAM remin minor [], the extinction of the ircrft engine reult in noticeble incree of the drg, while lift nd ide force remin quite the me. The drg coefficient i now given by: e

2 ' C D CD, e, M ncde, M ( where C DE i the dditionl drg of hut down engine, nd n i the number of engine of the ircrft. The flight eqution cn be written : V ( D( V,, m g in m (3- ( L( V,, m g co mv (3- x V co (3-3 z V in (3-4 where i the pth ngle, i the pitch ngle. Once fuel dumping h been performed, the m m of the ircrft i conidered to remin contnt. Here x nd z re repectively the current longitudinl nd verticl poition of the ircrft center of grvity. Then, it height bove Erth i given by: h z H (x (4 where H (x i ground level t poition x. where z i the initil ltitude. Now, conidering the bove expreion of D, we get: min mg / ( z S K / C' V ( z (9 D Then the ir peed decree during the qui ttic glide decent. For wide body ircrft, from cruie level, bout 8 m/ re lot for qui tedy initil decent of m. A tll contrint cn be conidered to check the feibility of the glide mneuver: V ( z Vtll ( z mg / ( z S C L mx (- or K / C' D / C (- L mx Thi condition i generl erodynmic condition for gliding feibility of given ircrft under pecific erodynmic itution. Alo, the expreion of D min how tht dynmic preure remin contnt during the qui ttic glide. Figure. diply the irpeed nd tll peed during tedy decent. 3 ESTIMATION OF GLIDING RANGE A firt etimtion of gliding rnge cn be obtined by conidering tht the ircrft remin in qui tedy gliding condition where ir peed nd pth ngle chnge tedily ccording to current ir denity during the whole decent. Fig. Airpeed during tedy gliding Fig. Aircrft force for qui tedy decent In thi itution the pth ngle i uch [3]: rcin (/ f ( V / g (5 or ccording to [4]: det / f mg / where ET mg z mv (6 dz i the ircrft totl energy. Here f =L/D i the lift to drg rtio. According to eqution (5, minimum glide ngle,, mx i chieved with mximum lift to drg rtio. Since L mg, thi correpond to minimum drg. Then it cn be hown tht: / ' K (7- mx C D ' Dmin ( z V (CD Q (C' D (7- A firt pproximtion to the mximum rnge to e level i then given by: R (8 z K C' D Then reltion between the qui ttic glide pth ngle nd the ltitude cn be introduced nd the minimum glide pth ngle i given by: mx tn P C' D K Q g /( R T z/ T ( where ir denity in tndrd tmophere cn be expreed g z RT ( z e with T ( z T z, T 88. 5K, K / m, R m 3 87 / K,.5kg / m. Then thi ngle incree while the ltitude i decreing during the qui tedy glide, hown in Figure 3. The mximum flight rnge R i then more ccurtely determined by: R dz z K C' D z tn mg T R z SC' D P g R T g R ( Thi i illutrted in Figure 4. If the ircrft loe engine power t higher ltitude, it cn glide over n increed 4th Chinee Control nd Deciion Conference (CCDC 99

3 rnge. In the ce of the ccident occurred on 4/8/, the A33 ircrft glided for km. With thi informtion, the rechble lnding ite cn be determined ccording to ome flight plnner [5], [6]. Fig 3. tn during qui tedy gliding Fig. 4 Rechble rnge for qui tedy glide. 4 GLIDE TRAJECTORY OPTIMIZATION FOR SAFETY In thi ection the problem of mnging the trjectory of trnporttion ircrft gliding from given initil flight itution i conidered. Contrrily to the clicl mx rnge gliding problem, by the end of the gliding mneuver, the ircrft mut be in condition (peed nd ttitude to perform fe touch down t lnding. In thi ce, the flight guidnce eqution written in the ircrft wind xi re given by eqution (3. Oberve the eqution tht the only independent input prmeter which i vilble here i the pitch ngle,, which cn, even in n engine-out itution, be controlled by the pilot either through the hydrulic power provided by the RAT or the uxiliry power unit-apu, or through the trim control chnnel. Here the initil flight condition re written : x ( x, h( h, V ( V, ( (3 while the finl lnding condition re uch : h ( t f hg ( x( t f, V ( t f V, ( t f (4 where V nd hould llow fe lnding t ltitude h G ( x( t f where function h G i repreenttive of the ground topogrphy under the conidered flight re. Since finl time i unknown nd i only chrcterized by the tifction of the finl condition, the replcement of independent prmeter t by the pce vrible x llow to diminih the complexity of the problem ince now finl x f i known once the lnding ite h been choen. Moreover, thi pproch hould fcilitte the conidertion of ground eprtion contrint nd could mke eier the conidertion of the effect of wind over the glide trjectory. From eqution (3 with : dt / dx /( V co (5 we get: z tg V ( D( V,, m g in mv co ( L( V,, m g co mv co (6 (6 (6 3 where repreent the derivtive with repect to the longitudinl poition x of the ircrft. The dditionl intnt contrint re: V x V ( z x [ x, x ], z [ z, z ] (7- mx ( min f, ( x ( x min, ( x min min (7- mx mx z x h ( x x [ x, x ] (7-3 ( G f Contrint (7- nd (7- prevent from tlling nd contrint (7-3 from ome flight into terrin-fit itution t n intermediry point of the glide. Then, different formultion of n optimiztion problem [7] cn be conidered to deign fe glide trjectory. For exmple the following criterion could be minimized with repect to the ucceive vlue of long the glide: min ( h( x f hg ( x f (8 under finl contrint V v V ( x f V ( (9- ( min vmx ( gmin ( x f ( g mx (9- where vmin, vmx, g min nd g mx re poitive mrgin nd with tte eqution (6, flight contrint (7 nd initil condition (3. The olution of thi non liner, trongly contrined trjectory optimiztion problem i difficult from the numericl point of view nd direct on line computtion of it olution doe not pper to be feible. For intnce, n pproch bed on the minimum principle [8] hould reult in very difficult two point boundry problem ince the reulting Hmiltonin h not n ffine tructure with f 4th Chinee Control nd Deciion Conference (CCDC

4 repect to the input prmeter. Mny other complex technique hve been developed for trjectory genertion [9], [], [] while Dynmic Progrmming [] pper to provide ome good perpective [3],[4]. To pply effectively Dynmic Progrmming olution trtegy, dicretiztion of thi problem pper necery nd the choice of the pce vrible x independent vrible for the flight eqution pper mot convenient. 5 THE PROPOSED SOLUTION STRATEGY Here dynmic progrmming i ued to generte feible glide trjectory towrd fe lnding plce. To inure the tifction of the finl lnding configurtion given by the qulity contrint (4, which i more criticl condition, revere pproch i dopted. Then the gliding trjectory i computed bckwrd from thee finl condition through the feible glide et defined by contrint (7 nd the pce dicretized tte eqution (6. With the objective of getting mooth flyble trjectory which void wting unnecerily the remining hydrulic energy ued to control the erodynmic ctutor (elevtor, THS, flp nd ero brke long the engine-out glide trjectory, new optimiztion criterion i dopted here. Thi urrogte criteri llow penlizing lrge vrition on pitch ttitude ngle, decent pth ngle, peed nd flight level, o tht it i evlution long feible pth Pk leding to tte i t tge k i given by formul uch : Here, i C k ( E ET ( T i P nd k ET re poitive weight whoe vlue chnge with the ditnce to the lnding ite. Dynmic progrmming, either direct or revere, conider t ech tge different feible tte nd elect for ech of them the bet pth leding to them from the initil tte t the firt tge of the erch proce. Under given vlue of input prmeter i t tge, bckwrd integrtion i ued to e the dditionl cot involved in going from tte (,i to new feible tte t the next tge of the erch proce. However, whtever the ize of the dicrete tep dopted to perform thi revere erch proce, from one tge to nother, lrge number of new tte hould be generted to gurntee the ccurcy of the reulting olution. Thi led to n exploive number of olution to be conidered when the tge order incree. So the exploion of the point mut be voided to inure the computer procee the problem. After ech bckwrd integrting, mny point hould be cut by uing the dynmic progrmming principle. Here, to llevite thi foreeeble computtionl burden, heuritic melting procedure i developed where cloer tte to centrl tte of the current tge in the erch proce re deleted while thi centrl tte i mintined. ij The ditnce between two tte i nd j of tge which h been dopted to generte thee cluter within one tge i given by: i j V Vmx i j z z zmx i j mx ij ( V ( ( ( V z Here two level weighting h been dopted: Vmx, z mx nd mx re cling prmeter nd V, z nd with V z re poitive reltive weighting. The bove pproch which h been developed i biclly n open loop pproch nd require very lrge computtionl effort which i unlikely to be performed on bord n ircrft which i lredy in criticl engine-out itution. Our propol here, which hould be developed in the ner future i to tke profit of the mount of dt generted by the revere dynmic progrmming erch proce, conidering different itution nd prmeter uch ircrft initil flight level, ltitude nd m, to trin neurl network devie deigned to generte pitch ngle directive t ech point long the decent o tht the glide trjectory led fely to the lnding itution. Here the computtionl burden ocited with revere dynmic progrmming i tken into profit to generte the trining dt be for the neurl network [5]. The generted pitch ngle directive cn be either ent to the utopilot when it i till operting or to flight director. In tht lt ce thi will llow thi mneuver to be performed efficiently in mnul mode by the pilot. Oberve tht long the glide trjectory, ech new olicittion of the neurl network will generte new piloting directive in ccordnce with the current itution of the ircrft which i lo the reult of externl perturbtion uch wind. 6 SIMULATION RESULTS A imultion tudy h been performed uing the RCAM wide body trnporttion ircrft model [6]. Then conidering the ce in which n engine filure occur 5km wy from poible lnding ite, different glide trjectorie obtined by revere dynmic progrmming re diplyed on Figure 5. nd on Figure 6 ccording to different initil itution. It pper tht if the ircrft h lrge initil totl energy, which men high peed nd/or high ltitude, the reulting glide trjectory i not be very mooth: the peed nd ltitude re ubject to lrge nd rpid chnge o tht the ircrft loe energy in exce ufficiently quickly to rrive to the lnding ite with cceptble flying prmeter. When initil totl energy i not too much exceive, the reulting glide trjectorie reult to be moother. For exmple, for initil condition with n Figure 7. nd Figure 8. diply n optimized glide trjectory in the ce in which initil ltitude i km (FL33 nd initil irpeed i m/ (bout 4 knot. Figure 9. nd Figure. diply the lnding rnge which cn be reched fely by n ircrft whoe initil glide condition re n ltitude of km nd n irpeed of 4th Chinee Control nd Deciion Conference (CCDC

5 8m/ (bout 36 knot. The lrget obtined glide rnge i bout 37 km while the hortet obtined glide rnge i 6 km. Then in tht ce, the gliding ircrft cn rech fely lnding ite locted between 6km nd 37km wy. Oberve on thee figure tht, the horter the rnge, the rougher i the trjectory. Compring figure 7. nd Figure 9., it pper lo tht with higher initil irpeed the gliding ircrft rnge i lo higher. Thee numericl reult indicte tht revere dynmic progrmming cn be ued to olve the glide trjectory genertion problem nd contribute to the deign of glide trjectory genertor either off line or on line. Fig 7. A mooth optiml glide trjectory in 3-D Fig 8. A mooth optiml glide trjectory in verticl plne Fig 5. Optiml glide trjectorie with different initil peed 3-dimenionl repreenttion Fig 9. Trjectorie of ircrft in verticl plne with different lnding rnge, 3D view Fig. 6 Optiml glide trjectorie in verticl plne with different initil ltitude Fig. Trjectorie of ircrft in verticl plne with different lnding rnge 4th Chinee Control nd Deciion Conference (CCDC

6 7 CONCLUSION The purpoe of thi communiction h been to preent the firt reult of tudy turned towrd the deign of n emergency mngement ytem ble to cope with n engine-out itution for trnporttion ircrft. The min contribution of thi communiction re: - review of the qui tedy glide rnge for trnport ircrft; - the propol of new repreenttion of the flight dynmic of gliding ircrft with the introduction of ptil dimenion independent vrible; - the development of olution trtegy bed on bckwrd integrtion nd revere dynmic progrmming whoe feibility i upported by the diplyed imultion reult. Thi work hould be completed by the integrtion of lterl mneuver nd the conidertion of the effect of wind over the glide trjectory. Thi lt point could be tckled by the development of n dptive pproch bed on the online etimtion of wind nd the ue of neurl mchine to generte control directive on rective bi. Thi remin for further tudie. REFERENCES [] Robert C. Nelon, Flight Stbility nd Automtic Control, McGrw-Hill Book Compny, US 989. [] Zhiyou Liu, Minjie Hou, Gng Wen, Experimentl Determintion of Aero-Engine Windmilling Drg, Journl of Aeropce Power, Vol., No., 6. [3] Nguyen X. Vinh, Flight Mechnic of High-Performnce Aircrft, Cmbridge Univerity Pre, UK, 993. [4] Hongying Wu, Mngement of Emergency Trjectory for Trnport Aircrft, MSc Repport, ENAC, Touloue, September. [5] Ell M. Atkin, Igor Alono Portillo, Mtthew J. Strube, Emergency Flight Plnning Applied to Totl Lo of Thrut. Journl of Aircrft, Vol.43, No. 4, 5-6, 6. [6] Ryn Rpetti, Srigul-Klijn, A 3-phe fe trjectory hping for ditreed ircrft, IEEE Aeropce Conference, USA,. [7] John T. Bett, Survey of Numericl Method for Trjectory Optimiztion, Journl of Guidnce, Control, nd Dynmic,Vol., No., 93-7, 998. [8] S. Khn, Flight Trjectory Optimiztion, Toronto, ICAS. [9] Nerin Srigul-Klijn,, R. Rpetti, A. Jordn, I. Lopez, M. Srigul-Klijn, P. Nepec, Intelligent Flight-Trjectory Genertion to Mximize Sfe-Outcome Probbility After Ditre Event. Journl of Aircrft, Vol.47, No., 55-67,. [] B. Outtr, F. Mor-Cmino, Trjectory Genertion for Reltive Guidnce of Merging Aircrft, in Optimiztion nd Coopertive Control Strtegie, M. Hirch editor, Lecture Note in Control nd Informtion Science Serie, Springer Berlin, 8. [] F.J. Vormer, M. Mulder, M.M. vn Pen, J.A. Mulder, Optimiztion of Flexible Approch Trjectorie Uing Genetic Algorithm, Journl of Aircrft, Vol.43, No.4, 94-95, 6. [] D. Bertek, Dynmic Progrmming nd Optiml Control, Athen Scientific, 7. [3] P. Hgeluer nd F. Mor-Cmino, Evlution of Prcticl Solution for Onbord Aircrft Four Dimenionl Guidnce, AIAA Journl of Guidnce, Control nd Dynmic (5,5-54, 997. [4] P. Hgeluer nd F. Mor-Cmino, A Soft Progrmming Approch for On-line Aircrft 4-D Trjectory Optimiztion, Europen Journl of Opertion Reerch, 87-95, 998. [5] Frncelin, R.A., F.A.C. Gomide, A Neurl Network for n-tge Optiml Control Problem, Proc. IEEE Int. Conf. Neurl Network - ICNN 94, Vol. 7, pp , Orlndo-FL, USA (994. [6] P. Lmbrecht, S. Bennni, G. Looye nd D. Moormnn, The RCAM Deign Chllenge Problem Decription in Robut Flight Control, J.F. Mgni, S. Bennni nd J. Terlouw editor, Lecture Note in Control nd Informtion Science 4, Springer, th Chinee Control nd Deciion Conference (CCDC 3

TP 10:Importance Sampling-The Metropolis Algorithm-The Ising Model-The Jackknife Method

TP 10:Importance Sampling-The Metropolis Algorithm-The Ising Model-The Jackknife Method TP 0:Importnce Smpling-The Metropoli Algorithm-The Iing Model-The Jckknife Method June, 200 The Cnonicl Enemble We conider phyicl ytem which re in therml contct with n environment. The environment i uully

More information

PHYSICS 211 MIDTERM I 22 October 2003

PHYSICS 211 MIDTERM I 22 October 2003 PHYSICS MIDTERM I October 3 Exm i cloed book, cloed note. Ue onl our formul heet. Write ll work nd nwer in exm booklet. The bck of pge will not be grded unle ou o requet on the front of the pge. Show ll

More information

CHOOSING THE NUMBER OF MODELS OF THE REFERENCE MODEL USING MULTIPLE MODELS ADAPTIVE CONTROL SYSTEM

CHOOSING THE NUMBER OF MODELS OF THE REFERENCE MODEL USING MULTIPLE MODELS ADAPTIVE CONTROL SYSTEM Interntionl Crpthin Control Conference ICCC 00 ALENOVICE, CZEC REPUBLIC y 7-30, 00 COOSING TE NUBER OF ODELS OF TE REFERENCE ODEL USING ULTIPLE ODELS ADAPTIVE CONTROL SYSTE rin BICĂ, Victor-Vleriu PATRICIU

More information

Artificial Intelligence Markov Decision Problems

Artificial Intelligence Markov Decision Problems rtificil Intelligence Mrkov eciion Problem ilon - briefly mentioned in hpter Ruell nd orvig - hpter 7 Mrkov eciion Problem; pge of Mrkov eciion Problem; pge of exmple: probbilitic blockworld ction outcome

More information

PHYS 601 HW 5 Solution. We wish to find a Fourier expansion of e sin ψ so that the solution can be written in the form

PHYS 601 HW 5 Solution. We wish to find a Fourier expansion of e sin ψ so that the solution can be written in the form 5 Solving Kepler eqution Conider the Kepler eqution ωt = ψ e in ψ We wih to find Fourier expnion of e in ψ o tht the olution cn be written in the form ψωt = ωt + A n innωt, n= where A n re the Fourier

More information

4-4 E-field Calculations using Coulomb s Law

4-4 E-field Calculations using Coulomb s Law 1/11/5 ection_4_4_e-field_clcultion_uing_coulomb_lw_empty.doc 1/1 4-4 E-field Clcultion uing Coulomb Lw Reding Aignment: pp. 9-98 Specificlly: 1. HO: The Uniform, Infinite Line Chrge. HO: The Uniform Dik

More information

Reinforcement learning

Reinforcement learning Reinforcement lerning Regulr MDP Given: Trnition model P Rewrd function R Find: Policy π Reinforcement lerning Trnition model nd rewrd function initilly unknown Still need to find the right policy Lern

More information

Low-order simultaneous stabilization of linear bicycle models at different forward speeds

Low-order simultaneous stabilization of linear bicycle models at different forward speeds 203 Americn Control Conference (ACC) Whington, DC, USA, June 7-9, 203 Low-order imultneou tbiliztion of liner bicycle model t different forwrd peed A. N. Gündeş nd A. Nnngud 2 Abtrct Liner model of bicycle

More information

STABILITY and Routh-Hurwitz Stability Criterion

STABILITY and Routh-Hurwitz Stability Criterion Krdeniz Technicl Univerity Deprtment of Electricl nd Electronic Engineering 6080 Trbzon, Turkey Chpter 8- nd Routh-Hurwitz Stbility Criterion Bu der notlrı dece bu deri ln öğrencilerin kullnımın çık olup,

More information

Reinforcement Learning and Policy Reuse

Reinforcement Learning and Policy Reuse Reinforcement Lerning nd Policy Reue Mnuel M. Veloo PEL Fll 206 Reding: Reinforcement Lerning: An Introduction R. Sutton nd A. Brto Probbilitic policy reue in reinforcement lerning gent Fernndo Fernndez

More information

LINKÖPINGS TEKNISKA HÖGSKOLA. Fluid and Mechanical Engineering Systems

LINKÖPINGS TEKNISKA HÖGSKOLA. Fluid and Mechanical Engineering Systems (6) Fluid nd Mechnicl Engineering Sytem 008086. ) Cvittion in orifice In hydrulic ytem cvittion occur downtrem orifice with high preure drop. For n orifice with contnt inlet preure of p = 00 br cvittion

More information

Estimation of Regions of Attraction of Spin Modes

Estimation of Regions of Attraction of Spin Modes 7 TH EUROPEAN CONFERENCE FOR AEROSPACE SCIENCES (EUCASS) Etimtion of Region of Attrction of Spin Mode Alexnder Khrbrov, Mri Sidoryuk, nd Dmitry Igntyev Centrl Aerohydrodynmic Intitute (TAGI), Zhukovky,

More information

CONTROL SYSTEMS LABORATORY ECE311 LAB 3: Control Design Using the Root Locus

CONTROL SYSTEMS LABORATORY ECE311 LAB 3: Control Design Using the Root Locus CONTROL SYSTEMS LABORATORY ECE311 LAB 3: Control Deign Uing the Root Locu 1 Purpoe The purpoe of thi lbortory i to deign cruie control ytem for cr uing the root locu. 2 Introduction Diturbnce D( ) = d

More information

Reinforcement Learning for Robotic Locomotions

Reinforcement Learning for Robotic Locomotions Reinforcement Lerning for Robotic Locomotion Bo Liu Stnford Univerity 121 Cmpu Drive Stnford, CA 94305, USA bliuxix@tnford.edu Hunzhong Xu Stnford Univerity 121 Cmpu Drive Stnford, CA 94305, USA xuhunvc@tnford.edu

More information

VSS CONTROL OF STRIP STEERING FOR HOT ROLLING MILLS. M.Okada, K.Murayama, Y.Anabuki, Y.Hayashi

VSS CONTROL OF STRIP STEERING FOR HOT ROLLING MILLS. M.Okada, K.Murayama, Y.Anabuki, Y.Hayashi V ONTROL OF TRIP TEERING FOR OT ROLLING MILL M.Okd.Murym Y.Anbuki Y.yhi Wet Jpn Work (urhiki Ditrict) JFE teel orportion wkidori -chome Mizuhim urhiki 7-85 Jpn Abtrct: trip teering i one of the mot eriou

More information

Markov Decision Processes

Markov Decision Processes Mrkov Deciion Procee A Brief Introduction nd Overview Jck L. King Ph.D. Geno UK Limited Preenttion Outline Introduction to MDP Motivtion for Study Definition Key Point of Interet Solution Technique Prtilly

More information

DYNAMICS VECTOR MECHANICS FOR ENGINEERS: Plane Motion of Rigid Bodies: Forces and Accelerations. Seventh Edition CHAPTER

DYNAMICS VECTOR MECHANICS FOR ENGINEERS: Plane Motion of Rigid Bodies: Forces and Accelerations. Seventh Edition CHAPTER CHAPTER 16 VECTOR MECHANICS FOR ENGINEERS: DYNAMICS Ferdinnd P. Beer E. Ruell Johnton, Jr. Lecture Note: J. Wlt Oler Tex Tech Univerity Plne Motion of Rigid Bodie: Force nd Accelertion Content Introduction

More information

APPENDIX 2 LAPLACE TRANSFORMS

APPENDIX 2 LAPLACE TRANSFORMS APPENDIX LAPLACE TRANSFORMS Thi ppendix preent hort introduction to Lplce trnform, the bic tool ued in nlyzing continuou ytem in the frequency domin. The Lplce trnform convert liner ordinry differentil

More information

20.2. The Transform and its Inverse. Introduction. Prerequisites. Learning Outcomes

20.2. The Transform and its Inverse. Introduction. Prerequisites. Learning Outcomes The Trnform nd it Invere 2.2 Introduction In thi Section we formlly introduce the Lplce trnform. The trnform i only pplied to cul function which were introduced in Section 2.1. We find the Lplce trnform

More information

PRACTICE EXAM 2 SOLUTIONS

PRACTICE EXAM 2 SOLUTIONS MASSACHUSETTS INSTITUTE OF TECHNOLOGY Deprtment of Phyic Phyic 8.01x Fll Term 00 PRACTICE EXAM SOLUTIONS Proble: Thi i reltively trihtforwrd Newton Second Lw problem. We et up coordinte ytem which i poitive

More information

ARCHIVUM MATHEMATICUM (BRNO) Tomus 47 (2011), Kristína Rostás

ARCHIVUM MATHEMATICUM (BRNO) Tomus 47 (2011), Kristína Rostás ARCHIVUM MAHEMAICUM (BRNO) omu 47 (20), 23 33 MINIMAL AND MAXIMAL SOLUIONS OF FOURH ORDER IERAED DIFFERENIAL EQUAIONS WIH SINGULAR NONLINEARIY Kritín Rotá Abtrct. In thi pper we re concerned with ufficient

More information

2. The Laplace Transform

2. The Laplace Transform . The Lplce Trnform. Review of Lplce Trnform Theory Pierre Simon Mrqui de Lplce (749-87 French tronomer, mthemticin nd politicin, Miniter of Interior for 6 wee under Npoleon, Preident of Acdemie Frncie

More information

Modeling and Controller Design for the Air-to-Air Missile Uncertain System

Modeling and Controller Design for the Air-to-Air Missile Uncertain System Interntionl ournl of Computer (IC) ISSN 07-45 (Print & Online) Globl Society of Scientific Reserch nd Reserchers http://ijcjournl.org/ Modeling nd Controller Design for the Air-to-Air Missile Uncertin

More information

SIMULATION OF TRANSIENT EQUILIBRIUM DECAY USING ANALOGUE CIRCUIT

SIMULATION OF TRANSIENT EQUILIBRIUM DECAY USING ANALOGUE CIRCUIT Bjop ol. o. Decemer 008 Byero Journl of Pure nd Applied Science, ():70 75 Received: Octoer, 008 Accepted: Decemer, 008 SIMULATIO OF TRASIET EQUILIBRIUM DECAY USIG AALOGUE CIRCUIT *Adullhi,.., Ango U.S.

More information

Review of Calculus, cont d

Review of Calculus, cont d Jim Lmbers MAT 460 Fll Semester 2009-10 Lecture 3 Notes These notes correspond to Section 1.1 in the text. Review of Clculus, cont d Riemnn Sums nd the Definite Integrl There re mny cses in which some

More information

SPACE VECTOR PULSE- WIDTH-MODULATED (SV-PWM) INVERTERS

SPACE VECTOR PULSE- WIDTH-MODULATED (SV-PWM) INVERTERS CHAPTER 7 SPACE VECTOR PULSE- WIDTH-MODULATED (SV-PWM) INVERTERS 7-1 INTRODUCTION In Chpter 5, we briefly icue current-regulte PWM inverter uing current-hyterei control, in which the witching frequency

More information

EE Control Systems LECTURE 8

EE Control Systems LECTURE 8 Coyright F.L. Lewi 999 All right reerved Udted: Sundy, Ferury, 999 EE 44 - Control Sytem LECTURE 8 REALIZATION AND CANONICAL FORMS A liner time-invrint (LTI) ytem cn e rereented in mny wy, including: differentil

More information

Fatigue Failure of an Oval Cross Section Prismatic Bar at Pulsating Torsion ( )

Fatigue Failure of an Oval Cross Section Prismatic Bar at Pulsating Torsion ( ) World Engineering & Applied Science Journl 6 (): 7-, 5 ISS 79- IDOSI Publiction, 5 DOI:.59/idoi.wej.5.6.. Ftigue Filure of n Ovl Cro Section Primtic Br t Pulting Torion L.Kh. Tlybly nd.m. giyev Intitute

More information

Transfer Functions. Chapter 5. Transfer Functions. Derivation of a Transfer Function. Transfer Functions

Transfer Functions. Chapter 5. Transfer Functions. Derivation of a Transfer Function. Transfer Functions 5/4/6 PM : Trnfer Function Chpter 5 Trnfer Function Defined G() = Y()/U() preent normlized model of proce, i.e., cn be ued with n input. Y() nd U() re both written in devition vrible form. The form of

More information

Chapter 2 Organizing and Summarizing Data. Chapter 3 Numerically Summarizing Data. Chapter 4 Describing the Relation between Two Variables

Chapter 2 Organizing and Summarizing Data. Chapter 3 Numerically Summarizing Data. Chapter 4 Describing the Relation between Two Variables Copyright 013 Peron Eduction, Inc. Tble nd Formul for Sullivn, Sttitic: Informed Deciion Uing Dt 013 Peron Eduction, Inc Chpter Orgnizing nd Summrizing Dt Reltive frequency = frequency um of ll frequencie

More information

Optimal Treatment of Queueing Model for Highway

Optimal Treatment of Queueing Model for Highway Journl of Computtion & Modelling, vol.1, no.1, 011, 61-71 ISSN: 179-765 (print, 179-8850 (online Interntionl Scientific Pre, 011 Optiml Tretment of Queueing Model for Highwy I.A. Imil 1, G.S. Mokddi, S.A.

More information

CONSTRUCTIVE CHARACTERISTICS AND MATHEMATICAL MODELLING OF MECHANIC-HIDRAULIC NETWORKS FOR COMPENSATING THE DYNAMICS OF ASSYMETRIC HYDRAULIC MOTORS

CONSTRUCTIVE CHARACTERISTICS AND MATHEMATICAL MODELLING OF MECHANIC-HIDRAULIC NETWORKS FOR COMPENSATING THE DYNAMICS OF ASSYMETRIC HYDRAULIC MOTORS Scientific Bulletin of the Politehnic Univerity of Timior Trnction on Mechnic Specil iue The 6 th Interntionl Conference on Hydrulic Mchinery nd Hydrodynmic Timior, Romni, October -, 004 CONSTRUCTIVE CHRCTERISTICS

More information

MULTI-DISCIPLINARY SYSTEM DESIGN OPTIMIZATION OF THE F-350 REAR SUSPENSION *

MULTI-DISCIPLINARY SYSTEM DESIGN OPTIMIZATION OF THE F-350 REAR SUSPENSION * AIAA-00-xxxx MULTI-DISCIPLINARY SYSTEM DESIGN OPTIMIZATION OF THE F-350 REAR SUSPENSION * Jcob Wronki Mter of Science Cndidte Deprtment of Mechnicl Engineering MIT CADlb J. Michel Gry Mter of Science Cndidte

More information

Wind-Induced Phenomenon in a Closed Water Area with Floating-Leaved Plant

Wind-Induced Phenomenon in a Closed Water Area with Floating-Leaved Plant Interntionl Journl of Environmentl nd Erth Science 1: 0 Wind-Induced Phenomenon in Cloed Wter Are with Floting-Leved Plnt Akinori Ozki Abtrct In thi tudy, in order to clrify wind-induced phenomen, epecilly

More information

Sealed tuned liquid column dampers: a cost effective solution for vibration damping of large arch hangers

Sealed tuned liquid column dampers: a cost effective solution for vibration damping of large arch hangers Seled tuned liquid column dmper: cot effective olution for vibrtion dmping of lrge rch hnger W. De Corte, C. Deleie nd Ph. Vn Bogert Ghent Univerity, Deprtment of Civil Engineering, Ghent, Belgium ABSTRACT:

More information

Section 4.2 Analysis of synchronous machines Part II

Section 4.2 Analysis of synchronous machines Part II Section 4. Anlyi of ynchronou mchine Prt 4.. Sttor flux linkge in non-lient pole ynchronou motor due to rotor The ir-gp field produced by the rotor produce flux linkge with individul phe winding. Thee

More information

Reinforcement Learning

Reinforcement Learning Reinforcement Lerning Tom Mitchell, Mchine Lerning, chpter 13 Outline Introduction Comprison with inductive lerning Mrkov Decision Processes: the model Optiml policy: The tsk Q Lerning: Q function Algorithm

More information

Robot Planning in Partially Observable Continuous Domains

Robot Planning in Partially Observable Continuous Domains Robot Plnning in Prtilly Obervble Continuou Domin Joep M. Port Intitut de Robòtic i Informàtic Indutril (UPC-CSIC) Lloren i Artig 4-6, 828, Brcelon Spin Emil: port@iri.upc.edu Mtthij T. J. Spn Informtic

More information

positive definite (symmetric with positive eigenvalues) positive semi definite (symmetric with nonnegative eigenvalues)

positive definite (symmetric with positive eigenvalues) positive semi definite (symmetric with nonnegative eigenvalues) Chter Liner Qudrtic Regultor Problem inimize the cot function J given by J x' Qx u' Ru dt R > Q oitive definite ymmetric with oitive eigenvlue oitive emi definite ymmetric with nonnegtive eigenvlue ubject

More information

Chapter 0. What is the Lebesgue integral about?

Chapter 0. What is the Lebesgue integral about? Chpter 0. Wht is the Lebesgue integrl bout? The pln is to hve tutoril sheet ech week, most often on Fridy, (to be done during the clss) where you will try to get used to the ides introduced in the previous

More information

A REVIEW OF CALCULUS CONCEPTS FOR JDEP 384H. Thomas Shores Department of Mathematics University of Nebraska Spring 2007

A REVIEW OF CALCULUS CONCEPTS FOR JDEP 384H. Thomas Shores Department of Mathematics University of Nebraska Spring 2007 A REVIEW OF CALCULUS CONCEPTS FOR JDEP 384H Thoms Shores Deprtment of Mthemtics University of Nebrsk Spring 2007 Contents Rtes of Chnge nd Derivtives 1 Dierentils 4 Are nd Integrls 5 Multivrite Clculus

More information

Accelerator Physics. G. A. Krafft Jefferson Lab Old Dominion University Lecture 5

Accelerator Physics. G. A. Krafft Jefferson Lab Old Dominion University Lecture 5 Accelertor Phyic G. A. Krfft Jefferon L Old Dominion Univerity Lecture 5 ODU Accelertor Phyic Spring 15 Inhomogeneou Hill Eqution Fundmentl trnvere eqution of motion in prticle ccelertor for mll devition

More information

Robot Planning in Partially Observable Continuous Domains

Robot Planning in Partially Observable Continuous Domains Robot Plnning in Prtilly Obervble Continuou Domin Joep M. Port Intitut de Robòtic i Informàtic Indutril (UPC-CSIC) Lloren i Artig 4-6, 828, Brcelon Spin Emil: port@iri.upc.edu Mtthij T. J. Spn Informtic

More information

Policy Gradient Methods for Reinforcement Learning with Function Approximation

Policy Gradient Methods for Reinforcement Learning with Function Approximation Policy Grdient Method for Reinforcement Lerning with Function Approximtion Richrd S. Sutton, Dvid McAlleter, Stinder Singh, Yihy Mnour AT&T Lb Reerch, 180 Prk Avenue, Florhm Prk, NJ 07932 Abtrct Function

More information

Non-Myopic Multi-Aspect Sensing with Partially Observable Markov Decision Processes

Non-Myopic Multi-Aspect Sensing with Partially Observable Markov Decision Processes Non-Myopic Multi-Apect Sening with Prtilly Oervle Mrkov Deciion Procee Shiho Ji 2 Ronld Prr nd Lwrence Crin Deprtment of Electricl & Computer Engineering 2 Deprtment of Computer Engineering Duke Univerity

More information

Forces from Strings Under Tension A string under tension medites force: the mgnitude of the force from section of string is the tension T nd the direc

Forces from Strings Under Tension A string under tension medites force: the mgnitude of the force from section of string is the tension T nd the direc Physics 170 Summry of Results from Lecture Kinemticl Vribles The position vector ~r(t) cn be resolved into its Crtesin components: ~r(t) =x(t)^i + y(t)^j + z(t)^k. Rtes of Chnge Velocity ~v(t) = d~r(t)=

More information

Calculus of Variations

Calculus of Variations Clculus of Vritions Com S 477/577 Notes) Yn-Bin Ji Dec 4, 2017 1 Introduction A functionl ssigns rel number to ech function or curve) in some clss. One might sy tht functionl is function of nother function

More information

Mathematical Sciences Technical Reports (MSTR)

Mathematical Sciences Technical Reports (MSTR) Roe-Hulmn Intitute of Technology Roe-Hulmn Scholr Mthemticl Science Technicl Report (MSTR) Mthemtic 8-15-9 Flttening Cone Sen A. Broughton Roe-Hulmn Intitute of Technology, brought@roe-hulmn.edu Follow

More information

Acceptance Sampling by Attributes

Acceptance Sampling by Attributes Introduction Acceptnce Smpling by Attributes Acceptnce smpling is concerned with inspection nd decision mking regrding products. Three spects of smpling re importnt: o Involves rndom smpling of n entire

More information

Predict Global Earth Temperature using Linier Regression

Predict Global Earth Temperature using Linier Regression Predict Globl Erth Temperture using Linier Regression Edwin Swndi Sijbt (23516012) Progrm Studi Mgister Informtik Sekolh Teknik Elektro dn Informtik ITB Jl. Gnesh 10 Bndung 40132, Indonesi 23516012@std.stei.itb.c.id

More information

Module 6: LINEAR TRANSFORMATIONS

Module 6: LINEAR TRANSFORMATIONS Module 6: LINEAR TRANSFORMATIONS. Trnsformtions nd mtrices Trnsformtions re generliztions of functions. A vector x in some set S n is mpped into m nother vector y T( x). A trnsformtion is liner if, for

More information

Tests for the Ratio of Two Poisson Rates

Tests for the Ratio of Two Poisson Rates Chpter 437 Tests for the Rtio of Two Poisson Rtes Introduction The Poisson probbility lw gives the probbility distribution of the number of events occurring in specified intervl of time or spce. The Poisson

More information

Design of a Piezoelectric Actuator Using Topology Optimization

Design of a Piezoelectric Actuator Using Topology Optimization Univerity of Tenneee, Knoxville Trce: Tenneee Reerch nd Cretive Exchnge Mter Thee Grdute School 5-23 Deign of Piezoelectric Actutor Uing Topology Optimiztion Jochim Drenckhn Univerity of Tenneee - Knoxville

More information

Ordinary differential equations

Ordinary differential equations Ordinry differentil equtions Introduction to Synthetic Biology E Nvrro A Montgud P Fernndez de Cordob JF Urchueguí Overview Introduction-Modelling Bsic concepts to understnd n ODE. Description nd properties

More information

Jack Simons, Henry Eyring Scientist and Professor Chemistry Department University of Utah

Jack Simons, Henry Eyring Scientist and Professor Chemistry Department University of Utah 1. Born-Oppenheimer pprox.- energy surfces 2. Men-field (Hrtree-Fock) theory- orbitls 3. Pros nd cons of HF- RHF, UHF 4. Beyond HF- why? 5. First, one usully does HF-how? 6. Bsis sets nd nottions 7. MPn,

More information

Math 1B, lecture 4: Error bounds for numerical methods

Math 1B, lecture 4: Error bounds for numerical methods Mth B, lecture 4: Error bounds for numericl methods Nthn Pflueger 4 September 0 Introduction The five numericl methods descried in the previous lecture ll operte by the sme principle: they pproximte the

More information

New data structures to reduce data size and search time

New data structures to reduce data size and search time New dt structures to reduce dt size nd serch time Tsuneo Kuwbr Deprtment of Informtion Sciences, Fculty of Science, Kngw University, Hirtsuk-shi, Jpn FIT2018 1D-1, No2, pp1-4 Copyright (c)2018 by The Institute

More information

Design, modeling and analysis of a brushless doubly-fed doubly-salient machine for electric vehicles

Design, modeling and analysis of a brushless doubly-fed doubly-salient machine for electric vehicles itle Deign, modeling nd nlyi of bruhle doubly-fed doubly-lient mchine for electric vehicle Author() Fn, Y; Chu, K Cittion Conference Record - I Annul eeting (Ieee Indutry Appliction Society), 005, v. 4,

More information

PHYS 4390: GENERAL RELATIVITY LECTURE 6: TENSOR CALCULUS

PHYS 4390: GENERAL RELATIVITY LECTURE 6: TENSOR CALCULUS PHYS 4390: GENERAL RELATIVITY LECTURE 6: TENSOR CALCULUS To strt on tensor clculus, we need to define differentition on mnifold.a good question to sk is if the prtil derivtive of tensor tensor on mnifold?

More information

Studies on Nuclear Fuel Rod Thermal Performance

Studies on Nuclear Fuel Rod Thermal Performance Avilble online t www.sciencedirect.com Energy Procedi 1 (1) 1 17 Studies on Nucler Fuel od herml Performnce Eskndri, M.1; Bvndi, A ; Mihndoost, A3* 1 Deprtment of Physics, Islmic Azd University, Shirz

More information

Tuning a Linguistic Information Retrieval System *

Tuning a Linguistic Information Retrieval System * uning Linguitic Informtion Retrievl Sytem * E. Herrer-Viedm, A. G. Lopez-Herrer nd L. Hidlgo Dept. of Computer Science nd Artificil Intelligence, Lirry Science Studie School, Univerity of Grnd, 18017 Grnd,

More information

International Journal of Scientific & Engineering Research, Volume 4, Issue 8, August ISSN

International Journal of Scientific & Engineering Research, Volume 4, Issue 8, August ISSN Interntionl Journl of Scientific & Engineering Reerc Volume Iue 8 ugut- 68 ISSN 9-558 n Inventory Moel wit llowble Sortge Uing rpezoil Fuzzy Number P. Prvti He & ocite Profeor eprtment of Mtemtic ui- E

More information

NUMERICAL INTEGRATION. The inverse process to differentiation in calculus is integration. Mathematically, integration is represented by.

NUMERICAL INTEGRATION. The inverse process to differentiation in calculus is integration. Mathematically, integration is represented by. NUMERICAL INTEGRATION 1 Introduction The inverse process to differentition in clculus is integrtion. Mthemticlly, integrtion is represented by f(x) dx which stnds for the integrl of the function f(x) with

More information

Open Access Analysis of RLV s Coupling Characteristic and Control Strategy Design

Open Access Analysis of RLV s Coupling Characteristic and Control Strategy Design Send Orders for Reprints to reprints@benthmscience.e The Open Automtion nd Control Systems Journl, 215, 7, 613-622 613 Open Access Anlysis of RLV s Coupling Chrcteristic nd Control Strtegy Design Shi Linn,

More information

MAC-solutions of the nonexistent solutions of mathematical physics

MAC-solutions of the nonexistent solutions of mathematical physics Proceedings of the 4th WSEAS Interntionl Conference on Finite Differences - Finite Elements - Finite Volumes - Boundry Elements MAC-solutions of the nonexistent solutions of mthemticl physics IGO NEYGEBAUE

More information

MA FINAL EXAM INSTRUCTIONS

MA FINAL EXAM INSTRUCTIONS MA 33 FINAL EXAM INSTRUCTIONS NAME INSTRUCTOR. Intructor nme: Chen, Dong, Howrd, or Lundberg 2. Coure number: MA33. 3. SECTION NUMBERS: 6 for MWF :3AM-:2AM REC 33 cl by Erik Lundberg 7 for MWF :3AM-:2AM

More information

Stuff You Need to Know From Calculus

Stuff You Need to Know From Calculus Stuff You Need to Know From Clculus For the first time in the semester, the stuff we re doing is finlly going to look like clculus (with vector slnt, of course). This mens tht in order to succeed, you

More information

Research on Influences of Retaining Wall Draining Capacity on Stability of Reservoir Bank Slope Retaining Wall

Research on Influences of Retaining Wall Draining Capacity on Stability of Reservoir Bank Slope Retaining Wall 5th Interntionl Conerence on Civil Engineering nd Trnporttion (ICCET 2015) Reerch on Inluence o Retining Wll Drining Cpcity on Stbility o Reervoir Bnk Slope Retining Wll Yiong Zhng1, *Liming Wu1, Zijin

More information

Lyapunov-type inequality for the Hadamard fractional boundary value problem on a general interval [a; b]; (1 6 a < b)

Lyapunov-type inequality for the Hadamard fractional boundary value problem on a general interval [a; b]; (1 6 a < b) Lypunov-type inequlity for the Hdmrd frctionl boundry vlue problem on generl intervl [; b]; ( 6 < b) Zid Ldjl Deprtement of Mthemtic nd Computer Science, ICOSI Lbortory, Univerity of Khenchel, 40000, Algeri.

More information

The Wave Equation I. MA 436 Kurt Bryan

The Wave Equation I. MA 436 Kurt Bryan 1 Introduction The Wve Eqution I MA 436 Kurt Bryn Consider string stretching long the x xis, of indeterminte (or even infinite!) length. We wnt to derive n eqution which models the motion of the string

More information

Analysis of Finite Element formulations for computing electromagnetic fields in the human body

Analysis of Finite Element formulations for computing electromagnetic fields in the human body Anlyi of Finite lement formultion for computing electromgnetic field in the humn body Lurent Bernrd, Joo Vconcelo, Noël Buri, Lurent Krähenbühl, Lurent Nicol To cite thi verion: Lurent Bernrd, Joo Vconcelo,

More information

ADJOINT ANALYSIS OF GUIDED PROJECTILE TERMINAL PHASE

ADJOINT ANALYSIS OF GUIDED PROJECTILE TERMINAL PHASE 9 ADJOIT AALYSIS OF GUIDED PROJECTILE TERMIAL PHASE Tio Silrnt nd Ari Siltvuori Fculty of Engineering nd Architecture Alto Univerity, School of Science nd Technology, Finlnd Sury Guided projectile terinl

More information

Math 426: Probability Final Exam Practice

Math 426: Probability Final Exam Practice Mth 46: Probbility Finl Exm Prctice. Computtionl problems 4. Let T k (n) denote the number of prtitions of the set {,..., n} into k nonempty subsets, where k n. Argue tht T k (n) kt k (n ) + T k (n ) by

More information

INTRODUCTION. The three general approaches to the solution of kinetics problems are:

INTRODUCTION. The three general approaches to the solution of kinetics problems are: INTRODUCTION According to Newton s lw, prticle will ccelerte when it is subjected to unblnced forces. Kinetics is the study of the reltions between unblnced forces nd the resulting chnges in motion. The

More information

Section 4.8. D v(t j 1 ) t. (4.8.1) j=1

Section 4.8. D v(t j 1 ) t. (4.8.1) j=1 Difference Equtions to Differentil Equtions Section.8 Distnce, Position, nd the Length of Curves Although we motivted the definition of the definite integrl with the notion of re, there re mny pplictions

More information

State space systems analysis (continued) Stability. A. Definitions A system is said to be Asymptotically Stable (AS) when it satisfies

State space systems analysis (continued) Stability. A. Definitions A system is said to be Asymptotically Stable (AS) when it satisfies Stte spce systems nlysis (continued) Stbility A. Definitions A system is sid to be Asymptoticlly Stble (AS) when it stisfies ut () = 0, t > 0 lim xt () 0. t A system is AS if nd only if the impulse response

More information

SKEW-NORMAL CORRECTION TO GEODETIC DIRECTIONS ON AN ELLIPSOID

SKEW-NORMAL CORRECTION TO GEODETIC DIRECTIONS ON AN ELLIPSOID Geoptil Science SKEW-NORMAL CORRECTION TO GEODETIC DIRECTIONS ON AN ELLIPSOID In Figure, n re two point t height n h bove n ellipoi of P h emi-mjor xi, n flttening f. The norml n PH (piercing the PH ellipoi

More information

Excerpted Section. Consider the stochastic diffusion without Poisson jumps governed by the stochastic differential equation (SDE)

Excerpted Section. Consider the stochastic diffusion without Poisson jumps governed by the stochastic differential equation (SDE) ? > ) 1 Technique in Computtionl Stochtic Dynmic Progrmming Floyd B. Hnon niverity of Illinoi t Chicgo Chicgo, Illinoi 60607-705 Excerpted Section A. MARKOV CHAI APPROXIMATIO Another pproch to finite difference

More information

MArkov decision processes (MDPs) have been widely

MArkov decision processes (MDPs) have been widely Spre Mrkov Deciion Procee with Cul Spre Tlli Entropy Regulriztion for Reinforcement Lerning yungje Lee, Sungjoon Choi, nd Songhwi Oh rxiv:709.0693v3 [c.lg] 3 Oct 07 Abtrct In thi pper, re Mrkov deciion

More information

AN020. a a a. cos. cos. cos. Orientations and Rotations. Introduction. Orientations

AN020. a a a. cos. cos. cos. Orientations and Rotations. Introduction. Orientations AN020 Orienttions nd Rottions Introduction The fct tht ccelerometers re sensitive to the grvittionl force on the device llows them to be used to determine the ttitude of the sensor with respect to the

More information

Monte Carlo method in solving numerical integration and differential equation

Monte Carlo method in solving numerical integration and differential equation Monte Crlo method in solving numericl integrtion nd differentil eqution Ye Jin Chemistry Deprtment Duke University yj66@duke.edu Abstrct: Monte Crlo method is commonly used in rel physics problem. The

More information

Analysis of Variance and Design of Experiments-II

Analysis of Variance and Design of Experiments-II Anlyi of Vrince nd Deign of Experiment-II MODULE VI LECTURE - 7 SPLIT-PLOT AND STRIP-PLOT DESIGNS Dr. Shlbh Deprtment of Mthemtic & Sttitic Indin Intitute of Technology Knpur Anlyi of covrince ith one

More information

Reinforcement learning II

Reinforcement learning II CS 1675 Introduction to Mchine Lerning Lecture 26 Reinforcement lerning II Milos Huskrecht milos@cs.pitt.edu 5329 Sennott Squre Reinforcement lerning Bsics: Input x Lerner Output Reinforcement r Critic

More information

Optimization and Simulation of Secondary Settler Models

Optimization and Simulation of Secondary Settler Models Proceeding of the 6th WE Interntionl Conference on imultion Modelling nd Optimiztion Libon Portugl eptember 22-24 26 24 Optimiztion nd imultion of econdry ettler Model I.. C. P. EPÍRITO NTO E. M. G. P.

More information

We are IntechOpen, the world s leading publisher of Open Access books Built by scientists, for scientists. International authors and editors

We are IntechOpen, the world s leading publisher of Open Access books Built by scientists, for scientists. International authors and editors We re IntechOpen, the world leding publiher of Open Acce book Built by cientit, for cientit,500 108,000 1.7 M Open cce book vilble Interntionl uthor nd editor Downlod Our uthor re mong the 151 Countrie

More information

LINEAR STOCHASTIC DIFFERENTIAL EQUATIONS WITH ANTICIPATING INITIAL CONDITIONS

LINEAR STOCHASTIC DIFFERENTIAL EQUATIONS WITH ANTICIPATING INITIAL CONDITIONS Communiction on Stochtic Anlyi Vol. 7, No. 2 213 245-253 Seril Publiction www.erilpubliction.com LINEA STOCHASTIC DIFFEENTIAL EQUATIONS WITH ANTICIPATING INITIAL CONDITIONS NAJESS KHALIFA, HUI-HSIUNG KUO,

More information

Physics 201 Lab 3: Measurement of Earth s local gravitational field I Data Acquisition and Preliminary Analysis Dr. Timothy C. Black Summer I, 2018

Physics 201 Lab 3: Measurement of Earth s local gravitational field I Data Acquisition and Preliminary Analysis Dr. Timothy C. Black Summer I, 2018 Physics 201 Lb 3: Mesurement of Erth s locl grvittionl field I Dt Acquisition nd Preliminry Anlysis Dr. Timothy C. Blck Summer I, 2018 Theoreticl Discussion Grvity is one of the four known fundmentl forces.

More information

Time Optimal Control of the Brockett Integrator

Time Optimal Control of the Brockett Integrator Milno (Itly) August 8 - September, 011 Time Optiml Control of the Brockett Integrtor S. Sinh Deprtment of Mthemtics, IIT Bomby, Mumbi, Indi (emil : sunnysphs4891@gmil.com) Abstrct: The Brockett integrtor

More information

Pressure Wave Analysis of a Cylindrical Drum

Pressure Wave Analysis of a Cylindrical Drum Pressure Wve Anlysis of Cylindricl Drum Chris Clrk, Brin Anderson, Brin Thoms, nd Josh Symonds Deprtment of Mthemtics The University of Rochester, Rochester, NY 4627 (Dted: December, 24 In this pper, hypotheticl

More information

Solutions Problem Set 2. Problem (a) Let M denote the DFA constructed by swapping the accept and non-accepting state in M.

Solutions Problem Set 2. Problem (a) Let M denote the DFA constructed by swapping the accept and non-accepting state in M. Solution Prolem Set 2 Prolem.4 () Let M denote the DFA contructed y wpping the ccept nd non-ccepting tte in M. For ny tring w B, w will e ccepted y M, tht i, fter conuming the tring w, M will e in n ccepting

More information

Working with Powers and Exponents

Working with Powers and Exponents Working ith Poer nd Eponent Nme: September. 00 Repeted Multipliction Remember multipliction i y to rite repeted ddition. To y +++ e rite. Sometime multipliction i done over nd over nd over. To rite e rite.

More information

Definition of Continuity: The function f(x) is continuous at x = a if f(a) exists and lim

Definition of Continuity: The function f(x) is continuous at x = a if f(a) exists and lim Mth 9 Course Summry/Study Guide Fll, 2005 [1] Limits Definition of Limit: We sy tht L is the limit of f(x) s x pproches if f(x) gets closer nd closer to L s x gets closer nd closer to. We write lim f(x)

More information

19 Optimal behavior: Game theory

19 Optimal behavior: Game theory Intro. to Artificil Intelligence: Dle Schuurmns, Relu Ptrscu 1 19 Optiml behvior: Gme theory Adversril stte dynmics hve to ccount for worst cse Compute policy π : S A tht mximizes minimum rewrd Let S (,

More information

1.9 C 2 inner variations

1.9 C 2 inner variations 46 CHAPTER 1. INDIRECT METHODS 1.9 C 2 inner vritions So fr, we hve restricted ttention to liner vritions. These re vritions of the form vx; ǫ = ux + ǫφx where φ is in some liner perturbtion clss P, for

More information

M. A. Pathan, O. A. Daman LAPLACE TRANSFORMS OF THE LOGARITHMIC FUNCTIONS AND THEIR APPLICATIONS

M. A. Pathan, O. A. Daman LAPLACE TRANSFORMS OF THE LOGARITHMIC FUNCTIONS AND THEIR APPLICATIONS DEMONSTRATIO MATHEMATICA Vol. XLVI No 3 3 M. A. Pthn, O. A. Dmn LAPLACE TRANSFORMS OF THE LOGARITHMIC FUNCTIONS AND THEIR APPLICATIONS Abtrct. Thi pper del with theorem nd formul uing the technique of

More information

Introduction to the Calculus of Variations

Introduction to the Calculus of Variations Introduction to the Clculus of Vritions Jim Fischer Mrch 20, 1999 Abstrct This is self-contined pper which introduces fundmentl problem in the clculus of vritions, the problem of finding extreme vlues

More information

PART 1 MULTIPLE CHOICE Circle the appropriate response to each of the questions below. Each question has a value of 1 point.

PART 1 MULTIPLE CHOICE Circle the appropriate response to each of the questions below. Each question has a value of 1 point. PART MULTIPLE CHOICE Circle the pproprite response to ech of the questions below. Ech question hs vlue of point.. If in sequence the second level difference is constnt, thn the sequence is:. rithmetic

More information

Lecture XVII. Vector functions, vector and scalar fields Definition 1 A vector-valued function is a map associating vectors to real numbers, that is

Lecture XVII. Vector functions, vector and scalar fields Definition 1 A vector-valued function is a map associating vectors to real numbers, that is Lecture XVII Abstrct We introduce the concepts of vector functions, sclr nd vector fields nd stress their relevnce in pplied sciences. We study curves in three-dimensionl Eucliden spce nd introduce the

More information

Evolutionary Algorithms Based Fixed Order Robust Controller Design and Robustness Performance Analysis

Evolutionary Algorithms Based Fixed Order Robust Controller Design and Robustness Performance Analysis Proceeding of 01 4th International Conference on Machine Learning and Computing IPCSIT vol. 5 (01) (01) IACSIT Pre, Singapore Evolutionary Algorithm Baed Fixed Order Robut Controller Deign and Robutne

More information

1 Bending of a beam with a rectangular section

1 Bending of a beam with a rectangular section 1 Bending of bem with rectngulr section x3 Episseur b M x 2 x x 1 2h M Figure 1 : Geometry of the bem nd pplied lod The bem in figure 1 hs rectngur section (thickness 2h, width b. The pplied lod is pure

More information