Int. J. Computers & Electrical Engineering, vol. 30, no. 1, pp , AN OBSERVER DESIGN PROCEDURE FOR A CLASS OF NONLINEAR TIME-DELAY SYSTEMS

Size: px
Start display at page:

Download "Int. J. Computers & Electrical Engineering, vol. 30, no. 1, pp , AN OBSERVER DESIGN PROCEDURE FOR A CLASS OF NONLINEAR TIME-DELAY SYSTEMS"

Transcription

1 In. J. Compues & Elecical Engineeing, vol. 3, no., pp. 6-7, 3. AN OBSERVER DESIGN PROCEDURE FOR A CLASS OF NONLINEAR TIME-DELAY SYSTEMS * ** H. Tinh *, M. Aleen ** an S. Nahavani * School o Engineeing an Technology, Deakin Univesiy, Geelong, 37, Ausalia. Depamen o Elecical an Eleconic Engineeing, The Univesiy o Melboune, Pakville, Vicoia, 3, Ausalia. Absac: This pape consies a class o unceain, nonlinea ieenial sae elaye conol sysems an pesens a euce-oe obseve esign poceue o asympoically esimae any veco sae uncionals. The meho popose involves ecomposiion o he elaye poion o he sysem ino wo pas: a mache an mismache pa. Povie ha he ank o he mismache pa is less han he numbe o he oupus, a euceoe linea uncional obseve, wih any pescibe sabiliy magin, can be consuce by using a simple poceue. A numeical example is given o illusae he new esign poceue an is eaues. Key Wos: Time-Delay Sysems, Linea Funcional Obseves, Reuce-Oe Sae Obseves, Unceain Sysems.. Inoucion The sae esimaion poblem o ime-elay sysems has been he subjec o consieable eseach aciviies ove he yeas. This is ue o he ac ha ime elays ae inheen in many eal physical sysems, such as mechanical an chemical pocesses, powe an wae isibuion newoks, ai polluion sysems, economeic sysems, ec. Seveal esign poceues have been popose o esign asympoic sae obseves o ime-elay sysems (see o example [] o a bie suvey an he eeences cie heein). In mos cases, epoe esign mehos ([]-[3]) involve he compuaion o he eigenvalues o he ime-elay sysems. Ohe esign mehos eihe assume he socalle maching-coniion on he elaye sae maix o he esuls ae applicable o sysems wih a small ime elay ([4]-[5]). In [6], a inie-oe memoyless sae obseve o ime-elay sysems is popose. As commene in [7], he obseve in [6], howeve, oes no povie acking o inpu signals ha o no convege o zeo. On he ohe han, he use o linea uncional obseves o asympoically geneae conol signals an/o o esimae a subse o saes has pove o be a pacical alenaive o oupu eeback conol. A numbe o esign poceues have been epoe in he lieaue [8]-[] o non-elay sysems. Recenly, he poblem o esigning low-oe linea uncional sae obseves o ime-elay sysems was is suie an a simple obseve esign poceue, which involves solving only a se o linea algebaic equaions, was popose in [3]. So a, epoe obseve esign mehos []-[3] have no eal wih ime-elay sysems ha may conain unceainies an/o nonlineaiies. The esign meho popose in his pape is capable o ealing wih a class o unceain an/o nonlinea imeelay sysems. The poceue oes no involve he compuaion o he eigenvalues o he elaye sysem elaive o some igh hal-plane, as in [-3,6]. Also, unlike ha in [4-5], hee is no esicion impose on he size o he ime elay an he elaye em o he sysem is no assume o saisy maching coniions. Insea, he elaye em is ecompose ino wo poions: a mache an mismache poion. The mismache poion may conain any unceainies an/o nonlineaiies an is eae as an unknown inpu (o isubance) o he sysem [4]. Subjec o he well-known coniion egaing he numbe o unknown inpus an oupus [4], an unknowninpu-ee euce-oe ime-elay sysem can be eive. Then a euce-oe linea uncional obseve, wih any pescibe sabiliy magin, can be sysemaically consuce base on he euce-oe sysem moel.. Sysem Descipion an Peliminaies Consie a class o ime-elay sysems moelle by he ollowing equaions x () = Ax () + Bu () + (, x ( τ )); (a) x () = g (); τ (b) y () = Cx () (c) τ is a posiive eal numbe epesening he ime elay in he sae an g() is a coninuous uncion on he n m ineval [ τ,]. The vecos x() R, u () R an y () R ae he sae, inpu an oupu, especively. n n Maices A R n m, B R n an C R ae consan. Wihou loss o genealiy, i is assume ha C has ull n ank, i.e. ank( C) =. The elaye uncion (, x ( τ )) R may be consue o epesen he unceainies an/o nonlineaiies o he sysem. I is assume ha (, x( τ )) can be ecompose ino a mache poion an a mismache poion, as ollows 6

2 In. J. Compues & Elecical Engineeing, vol. 3, no., pp. 6-7, 3. (, x ( τ )) = LCx ( τ) + Dη(, x ( τ)) () L R n n q, D R q, an η(, x ( τ)) R. Fuhemoe, D is assume o have a ull column ank, q. The em Dη (, x( τ )) can be use o escibe aiive isubance as well as many ieen kins o moelling unceainies (ee o [5]-[6] o uhe eails). In his pape, i will be eae as an unknown inpu o he sysem (). Now, he poblem o be aesse in his pape is ha o esigning a euce-oe obseve o imension p o geneae any equie l veco sae uncionals o he om x () = Fx() (3) l n F R. This ype o obseve can be use o iecly ealise a ull sae eeback conol law an/o o esimae any subse o he sae veco x() by leing maix F in equaion (3) o compise hose ows o I n ha coespon o he sae vaiables o be esimae. 3. Reuce-oe Time-Delay Moel In his secion, a euce-oe ime-elay moel ee o he unknown inpu is eive o sysem (). The euce-oe moel is hen use o eive a euce-oe linea uncional obseve wih any pescibe sabiliy magin, making use o he Unknown Inpu Obseves heoy [4]. Le us now consie he ollowing ansomaion x() = T x() (4a) n n T R is a non-singula maix eine as T = [ N D] (4b) an N R n ( n q) is any abiaily ull column ank maix. Subsiue () in () an hen use (4a) on he esulan, he ollowing equivalen sysem is obaine x () = Ax () + Bu () + LCx ( τ) + Dη(, x ( τ)); (5a) x () = g (); τ (5b) y () = Cx () (5c) x () = F x() (5) x () x (), () n q x R, () q x R, = x () A A A = T AT =, A A B B = T B =, B L C = CT = [ CN CD] = C C, L = T L =, D = T D = L I an F = FT = F F q (5e) Fom (5), he ollowing unknown-inpu-ee sysem is obaine x () = A x () + A x () + Bu() + LC x ( τ) + LC x ( τ); (6a) x () = g (); τ (6b) y () = C C x () (6c) x () = F F x() (6) Assuming ha q an maix C = CD has ull column ank q, hen hee exiss a non-singula maix U R > 6

3 In. J. Compues & Elecical Engineeing, vol. 3, no., pp. 6-7, 3. U U = C Q an U = (7) U gives an Q R is any abiaily ull column ank maix, ( q ) U R q ( q) an U R. Using (7) ino (6c) Uy () = UCx () + x() (o x () = Uy () UCx () ) (8a) U y() = U C x () (8b) Subsiuing equaion (8a) ino (6) an ae some manipulaions, he ollowing euce-oe ime-elay sysem is obaine x () = Ax () + Bu() + E y() + E y( τ) + L ( I CU ) C x ( τ); (9a) x () = g (); τ (9b) y () = C x() (9c) x () = F x () + E y() (9) 3 3 A = A AUC, E = A U, E = LC U, C = C U, F = F FU C, E = FU an ( q) y () = Uy () R (9e) Consie maix L ( I C U ) C in equaion (9a) an ecall om (7) ha UC = I q. Then i is clea ha ank{( I C U )} = ( q). Accoingly, hee always exiss a ull column ank maix K R ( n q) ( q) such ha L ( I C U ) = KU () U (SVD). Theeoe has been eine in (7). Noe ha maix K can be easily eive by using singula value ecomposiion L ( I C U ) C x ( τ ) can now be expesse as L( I CU) Cx( τ ) = KUCx( τ ) = KCx ( τ) = Ky ( τ) = KU y ( τ) () As a esul, he ollowing (n-q)-h euce-oe ime-elay sysem is obaine x () = Ax () + Bu() + E y() + E y( τ ); (a) 4 x () = g (); τ (b) y () = C x() (c) x () = F x () + E y() () 3 E = ( E + KU ) R 4 ( n q). Base on he above euce-oe moel, a linea uncional obseve o an/o a euce-oe Luenbege ype obseve o x () can now be easily synhesise. This is consiee in he nex secion. 4. Obseve Design This secion pesens wo ypes o obseves. One is a p-h euce-oe linea uncional obseve o asympoically esimae he veco sae uncionals x (). The ohe is a (n-q)-h euce-oe Luenbege ype obseve o esimae he enie sae veco x(). 4. Linea Funcional Obseve x () 63

4 In. J. Compues & Elecical Engineeing, vol. 3, no., pp. 6-7, 3. Le us now ecompose, abiaily, maix F as ollows F = KT + WC (3) l p K R p ( n q) T R l ( q) W R.,, Subsiuing equaion (3) ino () gives x () = F x () + E y() = KT x () + W y() + E y() 3 3 = K z () + ( WU + E) y () (4a) 3 p z() = Tx () R (4b) Consie he ollowing ieenial-elay equaion z () = Ez () + TBu () + TEy () + T ( E + KU) y ( τ ) + Gy (); (5) wih iniial coniions z () = h (), τ (6) p p E R ( ), G R p q an h() is a coninuous uncion on he inicae close ineval. i Deine an eo e () as e () = z () Tx () (7) Taking he eivaive o (7) gives E{() z Tx ()} ( GC T A ET ) x () = Ee() + ( GC T A + ET ) x () (8) e () = z () Tx () = + + I is clea ha i GC T A ET (9) + = hen equaion (8) becomes e () = Ee (). (a) wih iniial coniion e () = h () Tg (); τ. (b) The above evelopmen implies ha a ynamic elay sysem (5) can be consuce o asympoically geneae linea uncions o he sae (3), povie ha he ollowing coniions hol E = sable GC T A + ET = () F = KT + WC () 64

5 In. J. Compues & Elecical Engineeing, vol. 3, no., pp. 6-7, 3. Une he assumpion ha he pai ( A, C ) is obsevable an maix E is chosen o be sable, maices T, W, K, G can be solve using he poceues epoe in []-[] (ee o [] o a simple an MATLAB base poceue). The esign o a linea muli-uncional obseve is hus complee. 4. A Reuce-Oe Luenbege Obseve Povie ha he pai ( A, C ) is obsevable o eecable, a (n-q)-h Luenbege ype obseve can be eive o esimae he sae veco x() o sysem (). Le us inouce he ollowing ynamic ime-elay sysem v () = ( A LC ) v () + Bu () + ( E+ LU ) y( ) + ( E + KU) y( τ ); (3a) v () = m (); τ (3b) Deine an eo e () as e () = v () x() (4) Taking he eivaive o (4) an subsiuing equaions (3a) an (a) ino he esulan gives e () = v () x () = ( A LC ) e( ) (5) Povie ha maix we have ( n q) ( q) L R is chosen such ha A LC ( ) is sable, v () x ˆ () as. As a esul () ˆ v x ˆ( ) = Tx () = T Uy () UCv () (6) This complees he esign o (n-q)-h euce-oe obseve o esimae he enie sae o sysem (). (Noe ha q he unknown inpus η(, x ( τ)) R may also be esimae base on he euce-oe obseve (3). This can be one in a simila way o he wok epoe in [4]). Remak : The esuls o his pape ae applicable o a class o ime-elay sysems he ank o he mismache poion q is less han he numbe o oupus (i.e. q < ). This assumpion is less esicive han he maching coniion assumpion commonly mae in he lieaue (see [4] an he eeences cie heein). One o he novelies o his pape is he eucion o he ime-elay sysem () ino a lowe-oe sysem () o which available obseve esign heoy can be use. Remak : Noe ha o he case (, x( τ )) = A x( τ ) is a linea uncion [-7,3], he ecomposiion () can be easily peome by some simple maix manipulaions, as shown in he Appenix A. I is also shown in he Appenix ha o he case he numbe o oupus is moe han hal o he numbe o he saes (i.e. >.5n), he coniion q < is always saisie. 5. Numeical Example In his secion, a numeical example is given o illusae he esign poceue an is eaues. Consie he ollowing sysem x( ) sin( x ( )) x( τ ) +.5 x3( ) x ( ) = x ( ) + u ( ) + x( ) + x3( ) 3 x ( ) + x ( ) 3 y() = x(), τ, Fo illusaive pupose, le us now esign a euce-oe obseve o esimae he sae x (), ie. [ ] x () = Fx () = x () The nonlinea uncion can be ecompose ino he om (), 65

6 In. J. Compues & Elecical Engineeing, vol. 3, no., pp. 6-7, 3..5 L =, 3 D = an η(, x ( τ)) = sin{ x()} x( τ) R Base on he poceue given in Secion 3 o he pape, a euce-oe sysem o he om () is easily eive, =, A B =, E =, E 4 3 =, [ ] F = [ ] an [ ] C =, E 3 =. (Noe ha in eiving he above euce-oe moel, he maices N an Q eine in (4b) an (7), especively, ae chosen abiaily as: N = an = ). The pai ( A, C ) is obsevable. Base on he evelopmen in Secion 4 o his pape, an by choosing maix E as E = 5, he ollowing is-oe obseve o he sae x () is easily eive [ ] [ ] [ ] xˆ () = z() + 5 y() z ( ) = 5 z ( ) + u ( ) + y ( ) y ( ), The ollowing simulaion suy was caie ou wih he conol inpu signal is as shown in igue () an he elay is in he nonlinea uncion ( sin( x ( )) x( τ )) τ =. Figue () shows he simulae esponses o x () an xˆ (). Figue (3) shows he eo sae x () = x () xˆ (). The iniial coniions o he sysem an obseve wee aken o be x () = an z () = 5, [,]. Figues ()-(3) clealy show ha he sae esimaion eo conveges o zeo. Exensive compue simulaions have been conuce o ieen nonlinea uncions an ieen values o ime-elay, τ,. In all o he ese cases, he sae esimaion eo convege o zeo. 6. Conclusion In his pape a euce-oe linea uncional obseve esign poceue o a class o unceain an/o nonlinea ieenial sae elaye conol sysems has been popose. The meho involves he ecomposiion o he unceainies an/o nonlinea uncion ino wo pas: a mache an mismache pa. Povie ha he ank o he mismache pa is less han ha o he numbe o he oupus, a euce-oe linea ime-elay moel can be eive. Base on he eive moel, linea uncional obseve an/o euce-oe Luenbege sae obseve, wih any pescibe sabiliy magin, can be consuce by using a simple an sysemaic poceue. A numeical example has been given o illusae he new esign poceue an is main eaues. Reeences [] A.E. Peason an Y.A. Fiagbezi, An obseve o ime lag sysems, IEEE Tans. Auoma. Con., 34 (8), 989, [] K.P.M. Bha an H.N. Koivo, An obseve heoy o ime-elay sysems, IEEE Tans. Auoma. Con.,, 976, [3] D. Salamon, Obseves an ualiy beween obsevaion an sae eeback o ime elay sysems, IEEE Tans. Auoma. Con., 5, 98, [4] G.A. Hewe an G.J. Nazao, Obseve heoy o elaye ieenial equaions, In. J. Conol, 8 (), 973, -7. [5] A. Tonambe, Simple obseve-base conol law o ime lag sysems, In. J. Sysems Sci., 3 (9), 99, [6] J. Leyva-Ramos an A.E. Peason, An asympoic moal obseve o linea auonomous ime lag sysems, IEEE Tans. Auoma. Con., 4 (7), 995, [7] H. Tinh an M. Aleen, Commens on An asympoic moal obseve o linea auonomous ime lag sysems, IEEE Tans. Auoma. Con., 4, 997, u () 66

7 In. J. Compues & Elecical Engineeing, vol. 3, no., pp. 6-7, 3. [8] F.W. Faiman an R.D. Gupa, Design o muli-uncional euce-oe obseve, In. J. Sysems Science,, 98, [9] J. O'Reilly, Obseves o Linea Sysems (Acaemic Pess, Lonon, 983). [] C.C. Tsui, 986, On he oe eucion o linea uncional obseves, IEEE Tans. Auoma. Con., 3, 986, [] M. Aleen an H. Tinh, Reuce-oe linea uncional obseve o linea sysems, IEE Poceeings, Pa D, Conol Theoy an Applicaions, 46, 999, [] L. Lin, M. Aleen an H. Tinh, A ecenalise obseve scheme o ineconnece sysems wih highoe ineconnecions, Fouh Inenaional Coneence on Conol, Auomaion, Roboic an Vision, Singapoe, vol. 3, pp , 996. [3] H. Tinh, Linea uncional sae obseve o ime-elay sysems, In. J. Conol, 7(8), 999, [4] M. Hou an P.C. Mulle, Design o obseves o linea sysems wih unknown inpus, IEEE Tans. Auoma. Con., 37, 99, [5] M. Hou an P.C. Mulle, Faul eecion an isolaion obseves, In. J. Conol, 6(5), 994, [6] J. Chen, R.J. Paon an H.Y. Zhang, Design o unknown inpu obseves an obus aul eecion iles, In. J. Conol, 63(), 996, Appenix A: Maix Decomposiion C n n Une he assumpion ha ank( C) =, we can consuc a non-singula maix M as M = R, H ( n ) n H R. Then C an A can be ansome ino Cnew = CM [ I ] = (A) A = MA M = L C + A,, new new new new (A) Fom (A)-(A), n n n new can be chosen o compise he is columns o A new,. Maix A new, R is hen L R easily obaine wih is is o Anew,. Accoingly, columns being all zeos an is las (n ) columns being he las ( n ) columns A can be ecompose ino A = LC + A = n ; L R (A3) A = M A M ; A n n R (A4) L M L new, new I easy o see, om he above evelopmen, ha he ank o Thus, hee exiss a ull column ank maix n q D R such ha A saisies he coniion ank( A ) ( n ) q. Ax ( τ ) = DVx ( τ) = Dw ( τ ) (A5) w ( τ) = Vx ( τ) R q is eine as an unknown inpu. I is also clea om above ha o saisy he coniion q< equies ( n ) < (i.e. >.5n). This means ha o he case he numbe o oupus is moe han hal o he numbe o he saes hen he coniion q < is always saisie. 67

8 In. J. Compues & Elecical Engineeing, vol. 3, no., pp. 6-7, Figue (): Inpu signal u () F Figue (): Responses o x () (soli line) an xˆ () (ashe line) Figue (3): Response o he eo sae x () 68

An Automatic Door Sensor Using Image Processing

An Automatic Door Sensor Using Image Processing An Auomaic Doo Senso Using Image Pocessing Depamen o Elecical and Eleconic Engineeing Faculy o Engineeing Tooi Univesiy MENDEL 2004 -Insiue o Auomaion and Compue Science- in BRNO CZECH REPUBLIC 1. Inoducion

More information

On Control Problem Described by Infinite System of First-Order Differential Equations

On Control Problem Described by Infinite System of First-Order Differential Equations Ausalian Jounal of Basic and Applied Sciences 5(): 736-74 ISS 99-878 On Conol Poblem Descibed by Infinie Sysem of Fis-Ode Diffeenial Equaions Gafujan Ibagimov and Abbas Badaaya J'afau Insiue fo Mahemaical

More information

Servomechanism Design

Servomechanism Design Sevomechanism Design Sevomechanism (sevo-sysem) is a conol sysem in which he efeence () (age, Se poin) changes as ime passes. Design mehods PID Conol u () Ke P () + K I ed () + KDe () Sae Feedback u()

More information

Numerical solution of fuzzy differential equations by Milne s predictor-corrector method and the dependency problem

Numerical solution of fuzzy differential equations by Milne s predictor-corrector method and the dependency problem Applied Maemaics and Sciences: An Inenaional Jounal (MaSJ ) Vol. No. Augus 04 Numeical soluion o uzz dieenial equaions b Milne s pedico-coeco meod and e dependenc poblem Kanagaajan K Indakuma S Muukuma

More information

On The Estimation of Two Missing Values in Randomized Complete Block Designs

On The Estimation of Two Missing Values in Randomized Complete Block Designs Mahemaical Theoy and Modeling ISSN 45804 (Pape ISSN 505 (Online Vol.6, No.7, 06 www.iise.og On The Esimaion of Two Missing Values in Randomized Complee Bloc Designs EFFANGA, EFFANGA OKON AND BASSE, E.

More information

[ ] 0. = (2) = a q dimensional vector of observable instrumental variables that are in the information set m constituents of u

[ ] 0. = (2) = a q dimensional vector of observable instrumental variables that are in the information set m constituents of u Genealized Mehods of Momens he genealized mehod momens (GMM) appoach of Hansen (98) can be hough of a geneal pocedue fo esing economics and financial models. he GMM is especially appopiae fo models ha

More information

STUDY OF THE STRESS-STRENGTH RELIABILITY AMONG THE PARAMETERS OF GENERALIZED INVERSE WEIBULL DISTRIBUTION

STUDY OF THE STRESS-STRENGTH RELIABILITY AMONG THE PARAMETERS OF GENERALIZED INVERSE WEIBULL DISTRIBUTION Inenaional Jounal of Science, Technology & Managemen Volume No 04, Special Issue No. 0, Mach 205 ISSN (online): 2394-537 STUDY OF THE STRESS-STRENGTH RELIABILITY AMONG THE PARAMETERS OF GENERALIZED INVERSE

More information

Computer Propagation Analysis Tools

Computer Propagation Analysis Tools Compue Popagaion Analysis Tools. Compue Popagaion Analysis Tools Inoducion By now you ae pobably geing he idea ha pedicing eceived signal sengh is a eally impoan as in he design of a wieless communicaion

More information

Lecture-V Stochastic Processes and the Basic Term-Structure Equation 1 Stochastic Processes Any variable whose value changes over time in an uncertain

Lecture-V Stochastic Processes and the Basic Term-Structure Equation 1 Stochastic Processes Any variable whose value changes over time in an uncertain Lecue-V Sochasic Pocesses and he Basic Tem-Sucue Equaion 1 Sochasic Pocesses Any vaiable whose value changes ove ime in an unceain way is called a Sochasic Pocess. Sochasic Pocesses can be classied as

More information

Time-Space Model of Business Fluctuations

Time-Space Model of Business Fluctuations Time-Sace Moel of Business Flucuaions Aleei Kouglov*, Mahemaical Cene 9 Cown Hill Place, Suie 3, Eobicoke, Onaio M8Y 4C5, Canaa Email: Aleei.Kouglov@SiconVieo.com * This aicle eesens he esonal view of

More information

Combinatorial Approach to M/M/1 Queues. Using Hypergeometric Functions

Combinatorial Approach to M/M/1 Queues. Using Hypergeometric Functions Inenaional Mahemaical Foum, Vol 8, 03, no 0, 463-47 HIKARI Ld, wwwm-hikaicom Combinaoial Appoach o M/M/ Queues Using Hypegeomeic Funcions Jagdish Saan and Kamal Nain Depamen of Saisics, Univesiy of Delhi,

More information

MEEN 617 Handout #11 MODAL ANALYSIS OF MDOF Systems with VISCOUS DAMPING

MEEN 617 Handout #11 MODAL ANALYSIS OF MDOF Systems with VISCOUS DAMPING MEEN 67 Handou # MODAL ANALYSIS OF MDOF Sysems wih VISCOS DAMPING ^ Symmeic Moion of a n-dof linea sysem is descibed by he second ode diffeenial equaions M+C+K=F whee () and F () ae n ows vecos of displacemens

More information

works must be obtained from the IEEE.

works must be obtained from the IEEE. NAOSTE: Nagasaki Univesiy's Ac Tile Auho(s) Opeaion chaaceisics impoveme hal-wave eciie sel exciaion Hiayama, Taashi; Higuchi, Tsuyosh Ciaion CEMS 7, pp.8-8 ssue Dae 7- URL Righ hp://hl.hanle.ne/69/6 (c)7

More information

Sharif University of Technology - CEDRA By: Professor Ali Meghdari

Sharif University of Technology - CEDRA By: Professor Ali Meghdari Shaif Univesiy of echnology - CEDRA By: Pofesso Ali Meghai Pupose: o exen he Enegy appoach in eiving euaions of oion i.e. Lagange s Meho fo Mechanical Syses. opics: Genealize Cooinaes Lagangian Euaion

More information

Orthotropic Materials

Orthotropic Materials Kapiel 2 Ohoopic Maeials 2. Elasic Sain maix Elasic sains ae elaed o sesses by Hooke's law, as saed below. The sesssain elaionship is in each maeial poin fomulaed in he local caesian coodinae sysem. ε

More information

A note on characterization related to distributional properties of random translation, contraction and dilation of generalized order statistics

A note on characterization related to distributional properties of random translation, contraction and dilation of generalized order statistics PobSa Foum, Volume 6, July 213, Pages 35 41 ISSN 974-3235 PobSa Foum is an e-jounal. Fo eails please visi www.pobsa.og.in A noe on chaaceizaion elae o isibuional popeies of anom anslaion, conacion an ilaion

More information

Control Volume Derivation

Control Volume Derivation School of eospace Engineeing Conol Volume -1 Copyigh 1 by Jey M. Seizman. ll ighs esee. Conol Volume Deiaion How o cone ou elaionships fo a close sysem (conol mass) o an open sysem (conol olume) Fo mass

More information

AN EVOLUTIONARY APPROACH FOR SOLVING DIFFERENTIAL EQUATIONS

AN EVOLUTIONARY APPROACH FOR SOLVING DIFFERENTIAL EQUATIONS AN EVOLUTIONARY APPROACH FOR SOLVING DIFFERENTIAL EQUATIONS M. KAMESWAR RAO AND K.P. RAVINDRAN Depamen of Mechanical Engineeing, Calicu Regional Engineeing College, Keala-67 6, INDIA. Absac:- We eploe

More information

Lecture 22 Electromagnetic Waves

Lecture 22 Electromagnetic Waves Lecue Elecomagneic Waves Pogam: 1. Enegy caied by he wave (Poyning veco).. Maxwell s equaions and Bounday condiions a inefaces. 3. Maeials boundaies: eflecion and efacion. Snell s Law. Quesions you should

More information

CS 188: Artificial Intelligence Fall Probabilistic Models

CS 188: Artificial Intelligence Fall Probabilistic Models CS 188: Aificial Inelligence Fall 2007 Lecue 15: Bayes Nes 10/18/2007 Dan Klein UC Bekeley Pobabilisic Models A pobabilisic model is a join disibuion ove a se of vaiables Given a join disibuion, we can

More information

336 ERIDANI kfk Lp = sup jf(y) ; f () jj j p p whee he supemum is aken ove all open balls = (a ) inr n, jj is he Lebesgue measue of in R n, () =(), f

336 ERIDANI kfk Lp = sup jf(y) ; f () jj j p p whee he supemum is aken ove all open balls = (a ) inr n, jj is he Lebesgue measue of in R n, () =(), f TAMKANG JOURNAL OF MATHEMATIS Volume 33, Numbe 4, Wine 2002 ON THE OUNDEDNESS OF A GENERALIED FRATIONAL INTEGRAL ON GENERALIED MORREY SPAES ERIDANI Absac. In his pape we exend Nakai's esul on he boundedness

More information

POSITIVE SOLUTIONS WITH SPECIFIC ASYMPTOTIC BEHAVIOR FOR A POLYHARMONIC PROBLEM ON R n. Abdelwaheb Dhifli

POSITIVE SOLUTIONS WITH SPECIFIC ASYMPTOTIC BEHAVIOR FOR A POLYHARMONIC PROBLEM ON R n. Abdelwaheb Dhifli Opuscula Mah. 35, no. (205), 5 9 hp://dx.doi.og/0.7494/opmah.205.35..5 Opuscula Mahemaica POSITIVE SOLUTIONS WITH SPECIFIC ASYMPTOTIC BEHAVIOR FOR A POLYHARMONIC PROBLEM ON R n Abdelwaheb Dhifli Communicaed

More information

Online Completion of Ill-conditioned Low-Rank Matrices

Online Completion of Ill-conditioned Low-Rank Matrices Online Compleion of Ill-condiioned Low-Rank Maices Ryan Kennedy and Camillo J. Taylo Compue and Infomaion Science Univesiy of Pennsylvania Philadelphia, PA, USA keny, cjaylo}@cis.upenn.edu Laua Balzano

More information

Synchronization of Fractional Chaotic Systems via Fractional-Order Adaptive Controller

Synchronization of Fractional Chaotic Systems via Fractional-Order Adaptive Controller Synchonizaion of Facional Chaoic Sysems via Facional-Ode Adapive Conolle S.H. Hosseinnia*, R. Ghadei*, A. Ranjba N.*, J. Sadai*, S. Momani** * Noshivani Univesiy of Technology, Faculy of Elecical Compue

More information

Lecture 18: Kinetics of Phase Growth in a Two-component System: general kinetics analysis based on the dilute-solution approximation

Lecture 18: Kinetics of Phase Growth in a Two-component System: general kinetics analysis based on the dilute-solution approximation Lecue 8: Kineics of Phase Gowh in a Two-componen Sysem: geneal kineics analysis based on he dilue-soluion appoximaion Today s opics: In he las Lecues, we leaned hee diffeen ways o descibe he diffusion

More information

Stability and Bifurcation in a Neural Network Model with Two Delays

Stability and Bifurcation in a Neural Network Model with Two Delays Inernaional Mahemaical Forum, Vol. 6, 11, no. 35, 175-1731 Sabiliy and Bifurcaion in a Neural Nework Model wih Two Delays GuangPing Hu and XiaoLing Li School of Mahemaics and Physics, Nanjing Universiy

More information

Discretization of Fractional Order Differentiator and Integrator with Different Fractional Orders

Discretization of Fractional Order Differentiator and Integrator with Different Fractional Orders Inelligen Conol and Auomaion, 207, 8, 75-85 hp://www.scip.og/jounal/ica ISSN Online: 253-066 ISSN Pin: 253-0653 Disceizaion of Facional Ode Diffeeniao and Inegao wih Diffeen Facional Odes Qi Zhang, Baoye

More information

The Production of Polarization

The Production of Polarization Physics 36: Waves Lecue 13 3/31/211 The Poducion of Polaizaion Today we will alk abou he poducion of polaized ligh. We aleady inoduced he concep of he polaizaion of ligh, a ansvese EM wave. To biefly eview

More information

ENGI 4430 Advanced Calculus for Engineering Faculty of Engineering and Applied Science Problem Set 9 Solutions [Theorems of Gauss and Stokes]

ENGI 4430 Advanced Calculus for Engineering Faculty of Engineering and Applied Science Problem Set 9 Solutions [Theorems of Gauss and Stokes] ENGI 44 Avance alculus fo Engineeing Faculy of Engineeing an Applie cience Poblem e 9 oluions [Theoems of Gauss an okes]. A fla aea A is boune by he iangle whose veices ae he poins P(,, ), Q(,, ) an R(,,

More information

, on the power of the transmitter P t fed to it, and on the distance R between the antenna and the observation point as. r r t

, on the power of the transmitter P t fed to it, and on the distance R between the antenna and the observation point as. r r t Lecue 6: Fiis Tansmission Equaion and Rada Range Equaion (Fiis equaion. Maximum ange of a wieless link. Rada coss secion. Rada equaion. Maximum ange of a ada. 1. Fiis ansmission equaion Fiis ansmission

More information

Probabilistic Models. CS 188: Artificial Intelligence Fall Independence. Example: Independence. Example: Independence? Conditional Independence

Probabilistic Models. CS 188: Artificial Intelligence Fall Independence. Example: Independence. Example: Independence? Conditional Independence C 188: Aificial Inelligence Fall 2007 obabilisic Models A pobabilisic model is a join disibuion ove a se of vaiables Lecue 15: Bayes Nes 10/18/2007 Given a join disibuion, we can eason abou unobseved vaiables

More information

7 Wave Equation in Higher Dimensions

7 Wave Equation in Higher Dimensions 7 Wave Equaion in Highe Dimensions We now conside he iniial-value poblem fo he wave equaion in n dimensions, u c u x R n u(x, φ(x u (x, ψ(x whee u n i u x i x i. (7. 7. Mehod of Spheical Means Ref: Evans,

More information

Kalman Filter: an instance of Bayes Filter. Kalman Filter: an instance of Bayes Filter. Kalman Filter. Linear dynamics with Gaussian noise

Kalman Filter: an instance of Bayes Filter. Kalman Filter: an instance of Bayes Filter. Kalman Filter. Linear dynamics with Gaussian noise COM47 Inoducion o Roboics and Inelligen ysems he alman File alman File: an insance of Bayes File alman File: an insance of Bayes File Linea dynamics wih Gaussian noise alman File Linea dynamics wih Gaussian

More information

Lag synchronization of hyperchaotic complex nonlinear systems via passive control

Lag synchronization of hyperchaotic complex nonlinear systems via passive control Appl. Mah. Inf. Sci. 7, No. 4, 1429-1436 (213) 1429 Applied Mahemaics & Infomaion Sciences An Inenaional Jounal hp://dx.doi.og/1.12785/amis/7422 Lag synchonizaion of hypechaoic complex nonlinea sysems

More information

Representing Knowledge. CS 188: Artificial Intelligence Fall Properties of BNs. Independence? Reachability (the Bayes Ball) Example

Representing Knowledge. CS 188: Artificial Intelligence Fall Properties of BNs. Independence? Reachability (the Bayes Ball) Example C 188: Aificial Inelligence Fall 2007 epesening Knowledge ecue 17: ayes Nes III 10/25/2007 an Klein UC ekeley Popeies of Ns Independence? ayes nes: pecify complex join disibuions using simple local condiional

More information

Projection of geometric models

Projection of geometric models ojecion of geomeic moels Copigh@, YZU Opimal Design Laboao. All ighs eseve. Las upae: Yeh-Liang Hsu (-9-). Noe: his is he couse maeial fo ME55 Geomeic moeling an compue gaphics, Yuan Ze Univesi. a of his

More information

Risk tolerance and optimal portfolio choice

Risk tolerance and optimal portfolio choice Risk oleance and opimal pofolio choice Maek Musiela BNP Paibas London Copoae and Invesmen Join wok wih T. Zaiphopoulou (UT usin) Invesmens and fowad uiliies Pepin 6 Backwad and fowad dynamic uiliies and

More information

Variance and Covariance Processes

Variance and Covariance Processes Vaiance and Covaiance Pocesses Pakash Balachandan Depamen of Mahemaics Duke Univesiy May 26, 2008 These noes ae based on Due s Sochasic Calculus, Revuz and Yo s Coninuous Maingales and Bownian Moion, Kaazas

More information

Application of Bernoulli wavelet method for numerical solution of fuzzy linear Volterra-Fredholm integral equations Abstract Keywords

Application of Bernoulli wavelet method for numerical solution of fuzzy linear Volterra-Fredholm integral equations Abstract Keywords Applicaion o enoulli wavele mehod o numeical soluion o uzz linea Volea-edholm inegal equaions Mohamed A. Ramadan a and Mohamed R. Ali b a Depamen o Mahemaics acul o Science Menouia Univesi Egp mamadan@eun.eg;

More information

A DELAY-DEPENDENT STABILITY CRITERIA FOR T-S FUZZY SYSTEM WITH TIME-DELAYS

A DELAY-DEPENDENT STABILITY CRITERIA FOR T-S FUZZY SYSTEM WITH TIME-DELAYS A DELAY-DEPENDENT STABILITY CRITERIA FOR T-S FUZZY SYSTEM WITH TIME-DELAYS Xinping Guan ;1 Fenglei Li Cailian Chen Insiue of Elecrical Engineering, Yanshan Universiy, Qinhuangdao, 066004, China. Deparmen

More information

Signals and Systems Profs. Byron Yu and Pulkit Grover Fall Midterm 1 Solutions

Signals and Systems Profs. Byron Yu and Pulkit Grover Fall Midterm 1 Solutions 8-90 Signals and Sysems Profs. Byron Yu and Pulki Grover Fall 07 Miderm Soluions Name: Andrew ID: Problem Score Max 0 8 4 6 5 0 6 0 7 8 9 0 6 Toal 00 Miderm Soluions. (0 poins) Deermine wheher he following

More information

Low-complexity Algorithms for MIMO Multiplexing Systems

Low-complexity Algorithms for MIMO Multiplexing Systems Low-complexiy Algoihms fo MIMO Muliplexing Sysems Ouline Inoducion QRD-M M algoihm Algoihm I: : o educe he numbe of suviving pahs. Algoihm II: : o educe he numbe of candidaes fo each ansmied signal. :

More information

Reinforcement learning

Reinforcement learning Lecue 3 Reinfocemen leaning Milos Hauskech milos@cs.pi.edu 539 Senno Squae Reinfocemen leaning We wan o lean he conol policy: : X A We see examples of x (bu oupus a ae no given) Insead of a we ge a feedback

More information

Mean-square Stability Control for Networked Systems with Stochastic Time Delay

Mean-square Stability Control for Networked Systems with Stochastic Time Delay JOURNAL OF SIMULAION VOL. 5 NO. May 7 Mean-square Sabiliy Conrol for Newored Sysems wih Sochasic ime Delay YAO Hejun YUAN Fushun School of Mahemaics and Saisics Anyang Normal Universiy Anyang Henan. 455

More information

t + t sin t t cos t sin t. t cos t sin t dt t 2 = exp 2 log t log(t cos t sin t) = Multiplying by this factor and then integrating, we conclude that

t + t sin t t cos t sin t. t cos t sin t dt t 2 = exp 2 log t log(t cos t sin t) = Multiplying by this factor and then integrating, we conclude that ODEs, Homework #4 Soluions. Check ha y ( = is a soluion of he second-order ODE ( cos sin y + y sin y sin = 0 and hen use his fac o find all soluions of he ODE. When y =, we have y = and also y = 0, so

More information

Extremal problems for t-partite and t-colorable hypergraphs

Extremal problems for t-partite and t-colorable hypergraphs Exemal poblems fo -paie and -coloable hypegaphs Dhuv Mubayi John Talbo June, 007 Absac Fix ineges and an -unifom hypegaph F. We pove ha he maximum numbe of edges in a -paie -unifom hypegaph on n veices

More information

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

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

More information

Two-dimensional Effects on the CSR Interaction Forces for an Energy-Chirped Bunch. Rui Li, J. Bisognano, R. Legg, and R. Bosch

Two-dimensional Effects on the CSR Interaction Forces for an Energy-Chirped Bunch. Rui Li, J. Bisognano, R. Legg, and R. Bosch Two-dimensional Effecs on he CS Ineacion Foces fo an Enegy-Chiped Bunch ui Li, J. Bisognano,. Legg, and. Bosch Ouline 1. Inoducion 2. Pevious 1D and 2D esuls fo Effecive CS Foce 3. Bunch Disibuion Vaiaion

More information

Sections 3.1 and 3.4 Exponential Functions (Growth and Decay)

Sections 3.1 and 3.4 Exponential Functions (Growth and Decay) Secions 3.1 and 3.4 Eponenial Funcions (Gowh and Decay) Chape 3. Secions 1 and 4 Page 1 of 5 Wha Would You Rahe Have... $1million, o double you money evey day fo 31 days saing wih 1cen? Day Cens Day Cens

More information

Tracking Control for Hybrid Systems via Embedding of Known Reference Trajectories

Tracking Control for Hybrid Systems via Embedding of Known Reference Trajectories Tacking Conol fo Hybid Sysems via Embedding of Known Refeence Tajecoies Ricado G. Sanfelice, J. J. Benjamin Biemond, Nahan van de Wouw, and W. P. Mauice H. Heemels Absac We sudy he poblem of designing

More information

ON 3-DIMENSIONAL CONTACT METRIC MANIFOLDS

ON 3-DIMENSIONAL CONTACT METRIC MANIFOLDS Mem. Fac. Inegaed As and Sci., Hioshima Univ., Se. IV, Vol. 8 9-33, Dec. 00 ON 3-DIMENSIONAL CONTACT METRIC MANIFOLDS YOSHIO AGAOKA *, BYUNG HAK KIM ** AND JIN HYUK CHOI ** *Depamen of Mahemaics, Faculy

More information

Monochromatic Wave over One and Two Bars

Monochromatic Wave over One and Two Bars Applied Mahemaical Sciences, Vol. 8, 204, no. 6, 307-3025 HIKARI Ld, www.m-hikai.com hp://dx.doi.og/0.2988/ams.204.44245 Monochomaic Wave ove One and Two Bas L.H. Wiyano Faculy of Mahemaics and Naual Sciences,

More information

Exponential and Logarithmic Equations and Properties of Logarithms. Properties. Properties. log. Exponential. Logarithmic.

Exponential and Logarithmic Equations and Properties of Logarithms. Properties. Properties. log. Exponential. Logarithmic. Eponenial and Logaihmic Equaions and Popeies of Logaihms Popeies Eponenial a a s = a +s a /a s = a -s (a ) s = a s a b = (ab) Logaihmic log s = log + logs log/s = log - logs log s = s log log a b = loga

More information

An Open cycle and Closed cycle Gas Turbine Engines. Methods to improve the performance of simple gas turbine plants

An Open cycle and Closed cycle Gas Turbine Engines. Methods to improve the performance of simple gas turbine plants An Open cycle and losed cycle Gas ubine Engines Mehods o impove he pefomance of simple gas ubine plans I egeneaive Gas ubine ycle: he empeaue of he exhaus gases in a simple gas ubine is highe han he empeaue

More information

A STOCHASTIC MODELING FOR THE UNSTABLE FINANCIAL MARKETS

A STOCHASTIC MODELING FOR THE UNSTABLE FINANCIAL MARKETS A STOCHASTIC MODELING FOR THE UNSTABLE FINANCIAL MARKETS Assoc. Pof. Romeo Negea Ph. D Poliehnica Univesiy of Timisoaa Depamen of Mahemaics Timisoaa, Romania Assoc. Pof. Cipian Peda Ph. D Wes Univesiy

More information

KINEMATICS OF RIGID BODIES

KINEMATICS OF RIGID BODIES KINEMTICS OF RIGID ODIES In igid body kinemaics, we use he elaionships govening he displacemen, velociy and acceleaion, bu mus also accoun fo he oaional moion of he body. Descipion of he moion of igid

More information

Lecture 20: Riccati Equations and Least Squares Feedback Control

Lecture 20: Riccati Equations and Least Squares Feedback Control 34-5 LINEAR SYSTEMS Lecure : Riccai Equaions and Leas Squares Feedback Conrol 5.6.4 Sae Feedback via Riccai Equaions A recursive approach in generaing he marix-valued funcion W ( ) equaion for i for he

More information

Static Output Feedback Variable Structure Control for a Class of Time-delay Systems

Static Output Feedback Variable Structure Control for a Class of Time-delay Systems AMSE JOURNALS 04-Series: Avances C; Vol. 69; N ; pp 58-68 Submie Sep. 03; Revise June 30, 04; Accepe July 5, 04 Saic Oupu Feeback Variable Srucure Conrol for a Class of ime-elay Sysems Y. ian, H. Yao,

More information

Passivity-Based Control of Saturated Induction Motors

Passivity-Based Control of Saturated Induction Motors Passivity-Base Contol of Satuate Inuction otos Levent U. Gökee, embe, IEEE, awan A. Simaan, Fellow, IEEE, an Chales W. Bice, Senio embe, IEEE Depatment of Electical Engineeing Univesity of South Caolina

More information

MA 214 Calculus IV (Spring 2016) Section 2. Homework Assignment 1 Solutions

MA 214 Calculus IV (Spring 2016) Section 2. Homework Assignment 1 Solutions MA 14 Calculus IV (Spring 016) Secion Homework Assignmen 1 Soluions 1 Boyce and DiPrima, p 40, Problem 10 (c) Soluion: In sandard form he given firs-order linear ODE is: An inegraing facor is given by

More information

MATHEMATICAL FOUNDATIONS FOR APPROXIMATING PARTICLE BEHAVIOUR AT RADIUS OF THE PLANCK LENGTH

MATHEMATICAL FOUNDATIONS FOR APPROXIMATING PARTICLE BEHAVIOUR AT RADIUS OF THE PLANCK LENGTH Fundamenal Jounal of Mahemaical Phsics Vol 3 Issue 013 Pages 55-6 Published online a hp://wwwfdincom/ MATHEMATICAL FOUNDATIONS FOR APPROXIMATING PARTICLE BEHAVIOUR AT RADIUS OF THE PLANCK LENGTH Univesias

More information

Chapter Three Systems of Linear Differential Equations

Chapter Three Systems of Linear Differential Equations Chaper Three Sysems of Linear Differenial Equaions In his chaper we are going o consier sysems of firs orer orinary ifferenial equaions. These are sysems of he form x a x a x a n x n x a x a x a n x n

More information

Projection of geometric models

Projection of geometric models ojecion of geomeic moels Eie: Yeh-Liang Hsu (998-9-2); ecommene: Yeh-Liang Hsu (2-9-26); las upae: Yeh-Liang Hsu (29--3). Noe: This is he couse maeial fo ME55 Geomeic moeling an compue gaphics, Yuan Ze

More information

Solutionbank Edexcel AS and A Level Modular Mathematics

Solutionbank Edexcel AS and A Level Modular Mathematics Page of 4 Soluionbank Edexcel AS and A Level Modular Mahemaics Exercise A, Quesion Quesion: Skech he graphs of (a) y = e x + (b) y = 4e x (c) y = e x 3 (d) y = 4 e x (e) y = 6 + 0e x (f) y = 00e x + 0

More information

Deviation probability bounds for fractional martingales and related remarks

Deviation probability bounds for fractional martingales and related remarks Deviaion pobabiliy bounds fo facional maingales and elaed emaks Buno Sausseeau Laboaoie de Mahémaiques de Besançon CNRS, UMR 6623 16 Roue de Gay 253 Besançon cedex, Fance Absac In his pape we pove exponenial

More information

The sudden release of a large amount of energy E into a background fluid of density

The sudden release of a large amount of energy E into a background fluid of density 10 Poin explosion The sudden elease of a lage amoun of enegy E ino a backgound fluid of densiy ceaes a song explosion, chaaceized by a song shock wave (a blas wave ) emanaing fom he poin whee he enegy

More information

Homework 6 AERE331 Spring 2019 Due 4/24(W) Name Sec. 1 / 2

Homework 6 AERE331 Spring 2019 Due 4/24(W) Name Sec. 1 / 2 Homework 6 AERE33 Spring 9 Due 4/4(W) Name Sec / PROBLEM (5p In PROBLEM 4 of HW4 we used he frequency domain o design a yaw/rudder feedback conrol sysem for a plan wih ransfer funcion 46 Gp () s The conroller

More information

A Study on Non-Binary Turbo Codes

A Study on Non-Binary Turbo Codes A Sudy on Non-Binay Tubo Codes Hoia BALTA, Maia KOVACI Univesiy Polyechnic of Timişoaa, Faculy of Eleconics and Telecommunicaions, Posal Addess, 3223 Timişoaa, ROMANIA, E-Mail: hoia.bala@ec.u.o, maia.kovaci@ec.u.o

More information

EN221 - Fall HW # 7 Solutions

EN221 - Fall HW # 7 Solutions EN221 - Fall2008 - HW # 7 Soluions Pof. Vivek Shenoy 1.) Show ha he fomulae φ v ( φ + φ L)v (1) u v ( u + u L)v (2) can be pu ino he alenaive foms φ φ v v + φv na (3) u u v v + u(v n)a (4) (a) Using v

More information

5. Response of Linear Time-Invariant Systems to Random Inputs

5. Response of Linear Time-Invariant Systems to Random Inputs Sysem: 5. Response of inear ime-invarian Sysems o Random Inpus 5.. Discree-ime linear ime-invarian (IV) sysems 5... Discree-ime IV sysem IV sysem xn ( ) yn ( ) [ xn ( )] Inpu Signal Sysem S Oupu Signal

More information

Physics 2001/2051 Moments of Inertia Experiment 1

Physics 2001/2051 Moments of Inertia Experiment 1 Physics 001/051 Momens o Ineia Expeimen 1 Pelab 1 Read he ollowing backgound/seup and ensue you ae amilia wih he heoy equied o he expeimen. Please also ill in he missing equaions 5, 7 and 9. Backgound/Seup

More information

Supplementary Information for On characterizing protein spatial clusters with correlation approaches

Supplementary Information for On characterizing protein spatial clusters with correlation approaches Supplementay Infomation fo On chaacteizing potein spatial clustes with coelation appoaches A. Shivananan, J. Unnikishnan, A. Raenovic Supplementay Notes Contents Deivation of expessions fo p = a t................................

More information

On the Semi-Discrete Davey-Stewartson System with Self-Consistent Sources

On the Semi-Discrete Davey-Stewartson System with Self-Consistent Sources Jounal of Applied Mahemaics and Physics 25 3 478-487 Published Online May 25 in SciRes. hp://www.scip.og/jounal/jamp hp://dx.doi.og/.4236/jamp.25.356 On he Semi-Discee Davey-Sewason Sysem wih Self-Consisen

More information

An S-type singular value inclusion set for rectangular tensors

An S-type singular value inclusion set for rectangular tensors Sang Jounal of Inequaliies and Applicaions 2017) 2017:141 DOI 10.1186/s13660-017-1421-0 R E S E A R C H Open Access An S-ype singula value inclusion se fo ecangula ensos Caili Sang * * Coespondence: sangcl@126.com

More information

The Effect of the Metal Oxidation on the Vacuum Chamber Impedance

The Effect of the Metal Oxidation on the Vacuum Chamber Impedance SL-FL 9-5 The ffec of he Meal Oiaion on he Vacuum Chambe Impeance nani Tsaanian ambug Univesiy Main Dohlus, Igo agoonov Deusches leconen-sinchoon(dsy bsac The oiaion of he meallic vacuum chambe inenal

More information

Four Generations of Higher Order Sliding Mode Controllers. L. Fridman Universidad Nacional Autonoma de Mexico Aussois, June, 10th, 2015

Four Generations of Higher Order Sliding Mode Controllers. L. Fridman Universidad Nacional Autonoma de Mexico Aussois, June, 10th, 2015 Four Generaions of Higher Order Sliding Mode Conrollers L. Fridman Universidad Nacional Auonoma de Mexico Aussois, June, 1h, 215 Ouline 1 Generaion 1:Two Main Conceps of Sliding Mode Conrol 2 Generaion

More information

General Non-Arbitrage Model. I. Partial Differential Equation for Pricing A. Traded Underlying Security

General Non-Arbitrage Model. I. Partial Differential Equation for Pricing A. Traded Underlying Security 1 Geneal Non-Abiage Model I. Paial Diffeenial Equaion fo Picing A. aded Undelying Secuiy 1. Dynamics of he Asse Given by: a. ds = µ (S, )d + σ (S, )dz b. he asse can be eihe a sock, o a cuency, an index,

More information

Consider a Binary antipodal system which produces data of δ (t)

Consider a Binary antipodal system which produces data of δ (t) Modulaion Polem PSK: (inay Phae-hi keying) Conide a inay anipodal yem whih podue daa o δ ( o + δ ( o inay and epeively. Thi daa i paed o pule haping ile and he oupu o he pule haping ile i muliplied y o(

More information

2-d Motion: Constant Acceleration

2-d Motion: Constant Acceleration -d Moion: Consan Acceleaion Kinemaic Equaions o Moion (eco Fom Acceleaion eco (consan eloci eco (uncion o Posiion eco (uncion o The eloci eco and posiion eco ae a uncion o he ime. eloci eco a ime. Posiion

More information

EFFECT OF PERMISSIBLE DELAY ON TWO-WAREHOUSE INVENTORY MODEL FOR DETERIORATING ITEMS WITH SHORTAGES

EFFECT OF PERMISSIBLE DELAY ON TWO-WAREHOUSE INVENTORY MODEL FOR DETERIORATING ITEMS WITH SHORTAGES Volume, ssue 3, Mach 03 SSN 39-4847 EFFEC OF PERMSSBLE DELAY ON WO-WAREHOUSE NVENORY MODEL FOR DEERORANG EMS WH SHORAGES D. Ajay Singh Yadav, Ms. Anupam Swami Assisan Pofesso, Depamen of Mahemaics, SRM

More information

2.7. Some common engineering functions. Introduction. Prerequisites. Learning Outcomes

2.7. Some common engineering functions. Introduction. Prerequisites. Learning Outcomes Some common engineering funcions 2.7 Inroducion This secion provides a caalogue of some common funcions ofen used in Science and Engineering. These include polynomials, raional funcions, he modulus funcion

More information

Modelling Dynamic Conditional Correlations in the Volatility of Spot and Forward Oil Price Returns

Modelling Dynamic Conditional Correlations in the Volatility of Spot and Forward Oil Price Returns Modelling Dynamic Condiional Coelaions in he Volailiy of Spo and Fowad Oil Pice Reuns Maeo Manea a, Michael McAlee b and Magheia Gasso c a Depamen of Saisics, Univesiy of Milan-Bicocca and FEEM, Milan,

More information

Settling Time Design and Parameter Tuning Methods for Finite-Time P-PI Control

Settling Time Design and Parameter Tuning Methods for Finite-Time P-PI Control Journal of Conrol Science an Engineering (6) - oi:.765/8-/6.. D DAVID PUBLISHING Seling ime Design an Parameer uning Mehos for Finie-ime P-PI Conrol Keigo Hiruma, Hisaazu Naamura an Yasuyui Saoh. Deparmen

More information

Chapter 2. First Order Scalar Equations

Chapter 2. First Order Scalar Equations Chaper. Firs Order Scalar Equaions We sar our sudy of differenial equaions in he same way he pioneers in his field did. We show paricular echniques o solve paricular ypes of firs order differenial equaions.

More information

Simulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010

Simulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010 Simulaion-Solving Dynamic Models ABE 5646 Week 2, Spring 2010 Week Descripion Reading Maerial 2 Compuer Simulaion of Dynamic Models Finie Difference, coninuous saes, discree ime Simple Mehods Euler Trapezoid

More information

Circular Motion. Radians. One revolution is equivalent to which is also equivalent to 2π radians. Therefore we can.

Circular Motion. Radians. One revolution is equivalent to which is also equivalent to 2π radians. Therefore we can. 1 Cicula Moion Radians One evoluion is equivalen o 360 0 which is also equivalen o 2π adians. Theefoe we can say ha 360 = 2π adians, 180 = π adians, 90 = π 2 adians. Hence 1 adian = 360 2π Convesions Rule

More information

State-Space Models. Initialization, Estimation and Smoothing of the Kalman Filter

State-Space Models. Initialization, Estimation and Smoothing of the Kalman Filter Sae-Space Models Iniializaion, Esimaion and Smoohing of he Kalman Filer Iniializaion of he Kalman Filer The Kalman filer shows how o updae pas predicors and he corresponding predicion error variances when

More information

Millennium Theory Equations Original Copyright 2002 Joseph A. Rybczyk Updated Copyright 2003 Joseph A. Rybczyk Updated March 16, 2006

Millennium Theory Equations Original Copyright 2002 Joseph A. Rybczyk Updated Copyright 2003 Joseph A. Rybczyk Updated March 16, 2006 Millennim heoy Eqaions Oiginal Copyigh 00 Joseph A. Rybzyk Updaed Copyigh 003 Joseph A. Rybzyk Updaed Mah 6, 006 Following is a omplee lis o he Millennim heoy o Relaiviy eqaions: Fo easy eeene, all eqaions

More information

The Asymptotic Behavior of Nonoscillatory Solutions of Some Nonlinear Dynamic Equations on Time Scales

The Asymptotic Behavior of Nonoscillatory Solutions of Some Nonlinear Dynamic Equations on Time Scales Advances in Dynamical Sysems and Applicaions. ISSN 0973-5321 Volume 1 Number 1 (2006, pp. 103 112 c Research India Publicaions hp://www.ripublicaion.com/adsa.hm The Asympoic Behavior of Nonoscillaory Soluions

More information

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients Secion 3.5 Nonhomogeneous Equaions; Mehod of Undeermined Coefficiens Key Terms/Ideas: Linear Differenial operaor Nonlinear operaor Second order homogeneous DE Second order nonhomogeneous DE Soluion o homogeneous

More information

MIMO Cognitive Radio Capacity in. Flat Fading Channel. Mohan Premkumar, Muthappa Perumal Chitra. 1. Introduction

MIMO Cognitive Radio Capacity in. Flat Fading Channel. Mohan Premkumar, Muthappa Perumal Chitra. 1. Introduction Inenaional Jounal of Wieless Communicaions, ewoking and Mobile Compuing 07; 4(6): 44-50 hp://www.aasci.og/jounal/wcnmc ISS: 38-37 (Pin); ISS: 38-45 (Online) MIMO Cogniive adio Capaciy in Fla Fading Channel

More information

d 1 = c 1 b 2 - b 1 c 2 d 2 = c 1 b 3 - b 1 c 3

d 1 = c 1 b 2 - b 1 c 2 d 2 = c 1 b 3 - b 1 c 3 and d = c b - b c c d = c b - b c c This process is coninued unil he nh row has been compleed. The complee array of coefficiens is riangular. Noe ha in developing he array an enire row may be divided or

More information

A GENERAL METHOD TO STUDY THE MOTION IN A NON-INERTIAL REFERENCE FRAME

A GENERAL METHOD TO STUDY THE MOTION IN A NON-INERTIAL REFERENCE FRAME The Inenaional onfeence on opuaional Mechanics an Viual Engineeing OME 9 9 OTOBER 9, Basov, Roania A GENERAL METHOD TO STUDY THE MOTION IN A NON-INERTIAL REFERENE FRAME Daniel onuache, Vlaii Mainusi Technical

More information

SLIDING MODE CONTROL SYNTHESIS OF UNCERTAIN TIME-DELAY SYSTEMS

SLIDING MODE CONTROL SYNTHESIS OF UNCERTAIN TIME-DELAY SYSTEMS 568 Asian Jounal of Conol, Vol. 5, No. 4, pp. 568-577 Decembe 3 SLIDING MODE CONROL SYNHESIS OF UNCERAIN IME-DELAY SYSEMS Y. Olov, W. Peuquei, and J.P. Richad ABSRAC Sliding mode conol synhesis is developed

More information

ADJOINT MONTE CARLO PHOTON TRANSPORT IN CONTINUOUS ENERGY MODE WITH DISCRETE PHOTONS FROM ANNIHILATION

ADJOINT MONTE CARLO PHOTON TRANSPORT IN CONTINUOUS ENERGY MODE WITH DISCRETE PHOTONS FROM ANNIHILATION ADJOINT MONT ARLO HOTON TRANSORT IN ONTINUOUS NRGY MOD WITH DISRT HOTONS FROM ANNIHILATION J. ua Hoogenboom Inefaculy Reaco Insiue Delf Univesiy of Technology Mekelweg 5 69 JB Delf The Nehelans j.e.hoogenboom@ii.uelf.nl

More information

Lecture 17: Kinetics of Phase Growth in a Two-component System:

Lecture 17: Kinetics of Phase Growth in a Two-component System: Lecue 17: Kineics of Phase Gowh in a Two-componen Sysem: descipion of diffusion flux acoss he α/ ineface Today s opics Majo asks of oday s Lecue: how o deive he diffusion flux of aoms. Once an incipien

More information

On a Fractional Stochastic Landau-Ginzburg Equation

On a Fractional Stochastic Landau-Ginzburg Equation Applied Mahemaical Sciences, Vol. 4, 1, no. 7, 317-35 On a Fracional Sochasic Landau-Ginzburg Equaion Nguyen Tien Dung Deparmen of Mahemaics, FPT Universiy 15B Pham Hung Sree, Hanoi, Vienam dungn@fp.edu.vn

More information

Topic 4a Introduction to Root Finding & Bracketing Methods

Topic 4a Introduction to Root Finding & Bracketing Methods /8/18 Couse Instucto D. Raymond C. Rumpf Office: A 337 Phone: (915) 747 6958 E Mail: cumpf@utep.edu Topic 4a Intoduction to Root Finding & Backeting Methods EE 4386/531 Computational Methods in EE Outline

More information

Anti-Disturbance Control for Multiple Disturbances

Anti-Disturbance Control for Multiple Disturbances Workshop a 3 ACC Ani-Disurbance Conrol for Muliple Disurbances Lei Guo (lguo@buaa.edu.cn) Naional Key Laboraory on Science and Technology on Aircraf Conrol, Beihang Universiy, Beijing, 9, P.R. China. Presened

More information

UNIVERSITY OF CINCINNATI

UNIVERSITY OF CINCINNATI UNIVERSITY OF CINCINNATI Dae: I,, heeby submi his wok as pa of he equiemens fo he egee of: in: I is enile: This wok an is efense appove by: Chai: Ceaive Leaning fo Inelligen Robos A isseaion submie o he

More information