Design of a Controller for Load Frequency Control in a Power System

Size: px
Start display at page:

Download "Design of a Controller for Load Frequency Control in a Power System"

Transcription

1 4 NAIONAL POWER YEM CONFERENCE, NPC Desgn of Contolle fo Lod Fequency Contol n Powe ystem V..Ru A. ke Abstct: hs e descbes the desgn of contolle fo lod fequency contol n owe system. hs contolle s n ddtonl secondy contol whose gn metes e desgned to neutlze the stedy stte fequency eo nd te lne owe eo, when the system s subjected to dstubnce. he gns of PI nd PID contolles e otmzed usng enetc Algothm. hs e esents the desgn of contolle fo Hydo-heml ystem. Intoducton od fequency contol s vey motnt n Powe L ystem Oeton nd Contol fo ulyng suffcent nd elble electc owe wth good qulty. One of the mn equements of Lod Fequency Contol fo n Inteconnected Powe ystem s to ensue stsfctoy e fequences nd nte e te lne tnsfes. Eos n these qunttes se due to unedctble lod vtons, whch cuse msmtches between geneton nd lod demnd. Due to these lod vtons the oetng ont of the fequency vs. Powe outut cuves chnges, whch cuses the vtons n fequency. hus fxed contolle my no longe be sutble. In ode to ovecome the bove mentoned oblem, vble gn secondy contolle hs to be ncooted n the system whch kees the oetng ont fxed by chngng the fequency vs. owe outut cuve chctestcs. Contolles e of mny tyes. hs e esents the desgn of the gns of INERAL, PROPORIONAL INERAL, PROPORIONAL INERAL DERIVAIVE Contolles. enetc Algothm s used s the Otmzton echnque fo the desgn of contolle gns fo Hydo-heml system. ystem Modelng An nteconnected Powe system cn be consdeed s beng dvded nto contol es, whch e connected by te lnes. In ech contol e ll genetos e ssumed to fom coheent gou. he owe system s subjected to locl vtons of ndom mgntudes nd duton's. Hence t s equed to contol the devtons of fequency nd te lne owe of ech contol e.. Hydo-heml ystem Modelng he lock dgm model of Hydo-heml system s shown n the Fg. Whee g, t, owe system, e the tnsfe functons elted to theml system. g ( g) Powe system C (I contolle) ( ) ( d ) (PID contolle). t (fo Non Rehet tubne) ( t) ( αh) t (fo Rehet tubne) ( t)( h) s ( s) (PI contolle) Whee hrehet tme constnt αpe unt megwtt tng g, t, owe system, e the tnsfe functons elted to Hydo system. ( w) Plot vlve t Powe g ( ) (.5w) system ( s) δ eed doo σ Dsh ot ( ) C ( d (I contolle) ( ) ) (PID contolle) (PI contolle) V Ru s wth Electcl Engneeng Detment t Indn Insttute of echnology, hgu, 7 INDIA (telehone: -876, e-ml: vg@ee.tkg.enet.n). A k ws wth Electcl Engneeng Detment t Indn Insttute of echnology, hgu, 7 INDIA

2 INDIAN INIUE OF ECHNOLOY, HARAPUR 7, DECEMER 7-, 5 g ( ( ) ) g whee σ /R Pd C Pc g Pg t Pt Powe system f P te - - Pc C g Pg t Pt Pd Powe system f Fg. lock Dgm of Hydo-heml system ( ) σ σ ( g (σ δ )) σ ( w) (.5w) Powe ystem t ( s) s the e-lne tnsfe functon V V Whee cos( δ δ ) ynchonzng P X Coeffcent [] δ, δ e the owe ngles of equvlent mchnes of the two es. ycl vlues of vous tme constnts nd gns used fo efomnce comutton e: Ae (heml system): s t.5 g.4 R Pd. Ae (Hydo ystem) : s w.6 g..4 σ.5 Pd. δ Pefomnce Index he efomnce ndex (J) chosen s the INERAL QUARE ERROR (IE). Fo two Ae system Pefomnce Index s chosen s J t (( f f ) ( f f ) ( P P ))dt te te Resonse of Uncontolled ystem he contolle (C) s ssumed to hve gn vlue of zeo n ths tcul cse,.e. the feed bck loo connected to the contolle (C) s neglected n lottng ths esonse. he stte sce equtons of the bove model e fomulted n the fom X & AX U ('A' nd '' mtces e gven n Aendx). Whee 'A' s the ystem tte Mtx. 'X' s the stte vecto 'U' s the nut vecto (n the esent cse the ste dstubnce vecto). hese smultneous dffeentl equtons e solved usng Rung-utt (R) fouth ode method nd the vtons of stte vbles wth esect to tme e clculted.

3 6 NAIONAL POWER YEM CONFERENCE, NPC he stte vbles of fequency nd te lne owe (fo wo- Ae cse) e lotted wth esect to tme, whch gve us the uncontolled esonse. (Fg's -4) ths offset ncooton of secondy contolle (C) s metve. 4. yes of Contolles Contolles e of mny tyes. hs e esents the detemnton of contolle gns nd the esonse of contolled system wth thee bsc tyes of contolle confgutons. ) Integl Contolles, wth tnsfe functon of ( ) ) Pootonl Integl Contolles, wth tnsfe functon of ( ). ) Pootonl Integl Devtve Contolles, wth tnsfe functon of ( d ). 4. Otmzton he gns of the vous contolles e to be otmzed fo mnmzng the Pefomnce Index. Fo ue Integl Contolle wth only one gn to be otmzed no secl otmzton technque s equed. Fo otmzng the gns of PI nd PID contolles whee nd gns esectvely, hve to be otmzed we hve to esot to some otmzton technque. Afte tyng out l nd Eo technque, to otmze the gns, whch ws found to be comuttonlly exensve, the uthos doted enetc Algothm och s the otmzton technque fo mnmzng the Pefomnce Index. 4. enetc Algothm hs s the obust otmzng technque. A lot of ltetue s vlble on ths tcul toc []. he stewse ocedue fo the lcton of the genetc lgothm to the contolle desgn oblem s gven s follows. 4.4 enetc Algothm led to Contolle Desgn Poblem he followng e the stes nvolved: 4 Desgn of Contolle he esonses of the uncontolled system hve some offset. hs offset hs to be mnmzed. Fo mnmzton of. he vlues of,, d e chosen ndomly. A set of these vlues detemnes the oulton sze.. Ech vlue of,, d e nteolted wthn the nge secfed fo,, d.. Ech nteolted vlue of,, d e ssed on to subogm whch clcultes the objectve functon whch s the efomnce ndex. he vlue etuned fom the subogm s J. 4. Fo ech set of,, d the vlues of J e collected nd these vlues e ssed on the ftness functon. he

4 INDIAN INIUE OF ECHNOLOY, HARAPUR 7, DECEMER 7-, 7 ftness functon s clculted usng Rowlett wheel method.[] 5. he mnmum vlue of J s chosen mong the fttest ndvduls (obtned fom ftness functon). hs mnmum vlue, long wth the coesondng,, d e stoed. 6. hese fttest vlues of J e ssed on to Cossove nd Mutton functons to fom set of new oulton. hese oulton e the new vlues of,, d obtned fte fst teton.(coss ove nd Mutton functons[] ). 7. he bove stes e eeted tll mxmum geneton. Mxmum geneton coesonds to the numbe of loos equed to otmze the Pefomnce Index. 8. Fom the stoed mnmum vlues of J the otmum vlue of J s obtned.. he coesondng vlues of,, d gves the otmum vlues of the contolle gns. 5 Resonse of Contolled ystem he vlues of contolle gns,, d e clculted usng enetc Algothm wth the stes outlned bove. Wth these vlues, the stte sce equtons fo the closed loo system fo Hydo-heml system n the fom of X & AX U ('A' nd '' mtces e gven n the Aendx)e fomulted. hese smultneous dffeentl equtons e solved usng Rung-utt fouth ode method nd the esonses e lotted. hese esonses (Fg's 5-) eesent the esonse of the comlete system wth contolle ncluded. Whle comutng the esonses some smlfed ssumtons e mde. 5. Assumtons. No eneton te constnts e consdeed.. Ded bnd of the oveno s neglected. Lod-fequency deendency s lne, menng tht the lod would ncese one- ecent fo once ecent fequency ncese.[] 6 Conclusons he esonses of the Hydo-heml system wth dffeent contolles vz. ) Integl contolle b) Pootonl Integl contolle contolle hve been evluted. he lcton of enetc Algothm fo the Otmzton of gns of the bove-mentoned contolles s vey effcent nd hs fste soluton fndng cblty. he dffeent tyes of contolles mentoned bove hve neutlzed the offset, whch eed n cse of n Uncontolled system. Acknowledgements he uthos exess the dee sense of gttude to the Decto, II hgu, fo ovdng ll the necessy fcltes. One of the uthos 'ke' s thnkful to hs collegue, M. Anukul hukl fo ote gudnce nd vluble suggestons gven to hm. he uthos e gteful to the Hed of the Detment of Electcl Engneeng, fo hs cooeton n comletng ths e. Refeences. O.I. Elged nd C.E.Fosh, "Otmum Megwtt-Fequency Contol of Multe Electc Enegy ystems," nd "he Megwtt-Fequency Contol Poblem: A New Aoch V Otml Contol heoy," IEEE tnsctons on Powe Atus nd system, Vol. PA-8, No.4, Al 7, D.. Rmey nd J.W. kooglund, "Detled Hydogoveno Reesentton fo ystem tblty tudes," IEEE tns. PA, Vol. PA-8, No., Jnuy 7, D.E.oldbeg, enetc Algothms n sech, Otmzton nd Mchne Lenng, Addson-Wesely C.. Chng, Wehul Fu, nd Fushun Wen, "Lod Fequency Contol usng enetc Algothm bsed fuzzy gn schedulng of PI contolles," Electc Mchnes nd Powe systems, vol. 6 8, IEEE Commttee Reot, "Dynmc Models fo tem nd Hydo ubnes n Powe ystem tudes". IEEE ns, PA -, 7, C.. Pn nd C.M. Lw, An Adtve contolle fo owe system lod fequency contol, IEEE nsctons on Powe systems, Vol. 4. No.. Febuy 8, Undestndng Automtc eneton Contol, Pe No. WM -5 PWR, esented t IEEE wnte Powe Meetng,. APPENDIX Hydo-heml ystem wth PI Contolle he stte vbles chosen e x f x Pt x Pg x4 f x5 Pt x Pg x Pte x Pc x Pc x x& 6 x x&

5 NAIONAL POWER YEM CONFERENCE, NPC 8 he 'A' mtx s w w s s s g g g R t t s s s Whee s s 78 s 5 4 s s 7 s 4 s s 5 s s 7 s s he '' mtx s 8 Pd s Pd s Whee 8 Pd s Pd s ) ( Pd s s

6 INDIAN INIUE OF ECHNOLOY, HARAPUR 7, DECEMER 7-, Fo obtnng the 'A' nd '' mtces fo n Integl contolle substtute. Fo obtnng the 'A' nd '' mtces fo n Uncontolled system substtute. f Fg 5. Fequency (heml e) vs. tme Hydo-heml system (I contolle) f x Fg 6. Fequency (Hydo e) vs. tme Hydo-heml system (I contolle).5 x.5 f Fg 7. Fequency (heml e) vs. tme Hydo-heml system (PI contolle) f Fg 8. Fequency (Hydo e) vs. tme Hydo-heml system (PI contolle) x x P te -.6 P te Fg..e lne owe vs. tme Hydo-heml system (I contolle) Fg. e lne owe vs. tme Hydo-heml system (PI contolle)

6.6 The Marquardt Algorithm

6.6 The Marquardt Algorithm 6.6 The Mqudt Algothm lmttons of the gdent nd Tylo expnson methods ecstng the Tylo expnson n tems of ch-sque devtves ecstng the gdent sech nto n tetve mtx fomlsm Mqudt's lgothm utomtclly combnes the gdent

More information

Chapter I Vector Analysis

Chapter I Vector Analysis . Chpte I Vecto nlss . Vecto lgeb j It s well-nown tht n vecto cn be wtten s Vectos obe the followng lgebc ules: scl s ) ( j v v cos ) ( e Commuttv ) ( ssoctve C C ) ( ) ( v j ) ( ) ( ) ( ) ( (v) he lw

More information

The Schur-Cohn Algorithm

The Schur-Cohn Algorithm Modelng, Estmton nd Otml Flterng n Sgnl Processng Mohmed Njm Coyrght 8, ISTE Ltd. Aendx F The Schur-Cohn Algorthm In ths endx, our m s to resent the Schur-Cohn lgorthm [] whch s often used s crteron for

More information

Lecture 5 Single factor design and analysis

Lecture 5 Single factor design and analysis Lectue 5 Sngle fcto desgn nd nlss Completel ndomzed desgn (CRD Completel ndomzed desgn In the desgn of expements, completel ndomzed desgns e fo studng the effects of one pm fcto wthout the need to tke

More information

COMP 465: Data Mining More on PageRank

COMP 465: Data Mining More on PageRank COMP 465: Dt Mnng Moe on PgeRnk Sldes Adpted Fo: www.ds.og (Mnng Mssve Dtsets) Powe Iteton: Set = 1/ 1: = 2: = Goto 1 Exple: d 1/3 1/3 5/12 9/24 6/15 = 1/3 3/6 1/3 11/24 6/15 1/3 1/6 3/12 1/6 3/15 Iteton

More information

THE α-µ DISTRIBUTION: A GENERAL FADING DISTRIBUTION. Michel Daoud Yacoub

THE α-µ DISTRIBUTION: A GENERAL FADING DISTRIBUTION. Michel Daoud Yacoub TH - DISTRIBUTION: A GNRAL FADING DISTRIBUTION Mchel Doud Ycoub Unvest of Cmns, DCOM/FC/UNICAMP, C.P. 60, 3083-970, Cmns, SP, BRAZIL, mchel@decom.fee.uncm.b Abstct - Ths e esents genel fdng dstbuton the

More information

Homework 3 MAE 118C Problems 2, 5, 7, 10, 14, 15, 18, 23, 30, 31 from Chapter 5, Lamarsh & Baratta. The flux for a point source is:

Homework 3 MAE 118C Problems 2, 5, 7, 10, 14, 15, 18, 23, 30, 31 from Chapter 5, Lamarsh & Baratta. The flux for a point source is: . Homewok 3 MAE 8C Poblems, 5, 7, 0, 4, 5, 8, 3, 30, 3 fom Chpte 5, msh & Btt Point souces emit nuetons/sec t points,,, n 3 fin the flux cuent hlf wy between one sie of the tingle (blck ot). The flux fo

More information

Semi-empirical Evaluation of the Plasma Internal Inductance in Tokamaks

Semi-empirical Evaluation of the Plasma Internal Inductance in Tokamaks Jounl of Nucle nd Ptcle Physcs 14 4(3): 94-99 DO: 1.593/j.jn.1443. Sem-emcl Evluton of the Plsm ntenl nductnce n Tokmks A. Pknezhd 1* A. Sl Elh M. Ghonnevss 1 Physcs Detment Shest nch-slmc Azd Unvesty

More information

E-Companion: Mathematical Proofs

E-Companion: Mathematical Proofs E-omnon: Mthemtcl Poo Poo o emm : Pt DS Sytem y denton o t ey to vey tht t ncee n wth d ncee n We dene } ] : [ { M whee / We let the ttegy et o ech etle n DS e ]} [ ] [ : { M w whee M lge otve nume oth

More information

(a) Counter-Clockwise (b) Clockwise ()N (c) No rotation (d) Not enough information

(a) Counter-Clockwise (b) Clockwise ()N (c) No rotation (d) Not enough information m m m00 kg dult, m0 kg bby. he seesw stts fom est. Which diection will it ottes? ( Counte-Clockwise (b Clockwise ( (c o ottion ti (d ot enough infomtion Effect of Constnt et oque.3 A constnt non-zeo toque

More information

DCDM BUSINESS SCHOOL NUMERICAL METHODS (COS 233-8) Solutions to Assignment 3. x f(x)

DCDM BUSINESS SCHOOL NUMERICAL METHODS (COS 233-8) Solutions to Assignment 3. x f(x) DCDM BUSINESS SCHOOL NUMEICAL METHODS (COS -8) Solutons to Assgnment Queston Consder the followng dt: 5 f() 8 7 5 () Set up dfference tble through fourth dfferences. (b) Wht s the mnmum degree tht n nterpoltng

More information

PHYS 2421 Fields and Waves

PHYS 2421 Fields and Waves PHYS 242 Felds nd Wves Instucto: Joge A. López Offce: PSCI 29 A, Phone: 747-7528 Textook: Unvesty Physcs e, Young nd Feedmn 23. Electc potentl enegy 23.2 Electc potentl 23.3 Clcultng electc potentl 23.4

More information

The Shape of the Pair Distribution Function.

The Shape of the Pair Distribution Function. The Shpe of the P Dstbuton Functon. Vlentn Levshov nd.f. Thope Deptment of Phscs & stonom nd Cente fo Fundmentl tels Resech chgn Stte Unvest Sgnfcnt pogess n hgh-esoluton dffcton epements on powde smples

More information

Chapter 5: Your Program Asks for Advice.

Chapter 5: Your Program Asks for Advice. Chte 5: You Pogm Asks fo Advce. Pge 63 Chte 5: You Pogm Asks fo Advce. Ths chte ntoduces new tye of ves (stng ves) nd how to get text nd numec esonses fom the use. Anothe Tye of Ve The Stng Ve: In Chte

More information

7.5-Determinants in Two Variables

7.5-Determinants in Two Variables 7.-eteminnts in Two Vibles efinition of eteminnt The deteminnt of sque mti is el numbe ssocited with the mti. Eve sque mti hs deteminnt. The deteminnt of mti is the single ent of the mti. The deteminnt

More information

Machine Learning. Spectral Clustering. Lecture 23, April 14, Reading: Eric Xing 1

Machine Learning. Spectral Clustering. Lecture 23, April 14, Reading: Eric Xing 1 Machne Leanng -7/5 7/5-78, 78, Spng 8 Spectal Clusteng Ec Xng Lectue 3, pl 4, 8 Readng: Ec Xng Data Clusteng wo dffeent ctea Compactness, e.g., k-means, mxtue models Connectvty, e.g., spectal clusteng

More information

4. Eccentric axial loading, cross-section core

4. Eccentric axial loading, cross-section core . Eccentrc xl lodng, cross-secton core Introducton We re strtng to consder more generl cse when the xl force nd bxl bendng ct smultneousl n the cross-secton of the br. B vrtue of Snt-Vennt s prncple we

More information

Stability analysis of delayed system using Bode Integral

Stability analysis of delayed system using Bode Integral Stblty nlyss of elye system usng Boe Integl Ansh Ahy, Debt Mt. Detment of Instumentton n Eletons Engneeng, Jvu Unvesty, Slt-Lke Cmus, LB-8, Seto 3, Kolkt-798, In.. Detment of Eletons n ommunton Engneeng,

More information

Rigid Body Dynamics. CSE169: Computer Animation Instructor: Steve Rotenberg UCSD, Winter 2018

Rigid Body Dynamics. CSE169: Computer Animation Instructor: Steve Rotenberg UCSD, Winter 2018 Rg Bo Dnmcs CSE169: Compute Anmton nstucto: Steve Roteneg UCSD, Wnte 2018 Coss Pouct k j Popetes of the Coss Pouct Coss Pouct c c c 0 0 0 c Coss Pouct c c c c c c 0 0 0 0 0 0 Coss Pouct 0 0 0 ˆ ˆ 0 0 0

More information

4.2 Boussinesq s Theory. Contents

4.2 Boussinesq s Theory. Contents 00477 Pvement Stuctue 4. Stesses in Flexible vement Contents 4. Intoductions to concet of stess nd stin in continuum mechnics 4. Boussinesq s Theoy 4. Bumiste s Theoy 4.4 Thee Lye System Weekset Sung Chte

More information

Chapter Direct Method of Interpolation More Examples Mechanical Engineering

Chapter Direct Method of Interpolation More Examples Mechanical Engineering Chpte 5 iect Method o Intepoltion Moe Exmples Mechnicl Engineeing Exmple Fo the pupose o shinking tunnion into hub, the eduction o dimete o tunnion sht by cooling it though tempetue chnge o is given by

More information

Chapter Newton-Raphson Method of Solving a Nonlinear Equation

Chapter Newton-Raphson Method of Solving a Nonlinear Equation Chpter.4 Newton-Rphson Method of Solvng Nonlner Equton After redng ths chpter, you should be ble to:. derve the Newton-Rphson method formul,. develop the lgorthm of the Newton-Rphson method,. use the Newton-Rphson

More information

Rank One Update And the Google Matrix by Al Bernstein Signal Science, LLC

Rank One Update And the Google Matrix by Al Bernstein Signal Science, LLC Introducton Rnk One Updte And the Google Mtrx y Al Bernsten Sgnl Scence, LLC www.sgnlscence.net here re two dfferent wys to perform mtrx multplctons. he frst uses dot product formulton nd the second uses

More information

A Primer on Portfolio Theory

A Primer on Portfolio Theory Pt I: Some Bscs A Pme on Potolo Theoy The ottom lne th otolo constucton s lenng ho to del th uncetnty. To egn, let s stt th some dentons: A ndom vle s nume ssocted th n outcome tht s uncetn. Fo exmle,

More information

Uniform Circular Motion

Uniform Circular Motion Unfom Ccul Moton Unfom ccul Moton An object mong t constnt sped n ccle The ntude of the eloct emns constnt The decton of the eloct chnges contnuousl!!!! Snce cceleton s te of chnge of eloct:!! Δ Δt The

More information

Dennis Bricker, 2001 Dept of Industrial Engineering The University of Iowa. MDP: Taxi page 1

Dennis Bricker, 2001 Dept of Industrial Engineering The University of Iowa. MDP: Taxi page 1 Denns Brcker, 2001 Dept of Industrl Engneerng The Unversty of Iow MDP: Tx pge 1 A tx serves three djcent towns: A, B, nd C. Ech tme the tx dschrges pssenger, the drver must choose from three possble ctons:

More information

Data Structures. Element Uniqueness Problem. Hash Tables. Example. Hash Tables. Dana Shapira. 19 x 1. ) h(x 4. ) h(x 2. ) h(x 3. h(x 1. x 4. x 2.

Data Structures. Element Uniqueness Problem. Hash Tables. Example. Hash Tables. Dana Shapira. 19 x 1. ) h(x 4. ) h(x 2. ) h(x 3. h(x 1. x 4. x 2. Element Uniqueness Poblem Dt Stuctues Let x,..., xn < m Detemine whethe thee exist i j such tht x i =x j Sot Algoithm Bucket Sot Dn Shpi Hsh Tbles fo (i=;i

More information

Radial geodesics in Schwarzschild spacetime

Radial geodesics in Schwarzschild spacetime Rdil geodesics in Schwzschild spcetime Spheiclly symmetic solutions to the Einstein eqution tke the fom ds dt d dθ sin θdϕ whee is constnt. We lso hve the connection components, which now tke the fom using

More information

Chapter Runge-Kutta 2nd Order Method for Ordinary Differential Equations

Chapter Runge-Kutta 2nd Order Method for Ordinary Differential Equations Cter. Runge-Kutt nd Order Metod or Ordnr Derentl Eutons Ater redng ts cter ou sould be ble to:. understnd te Runge-Kutt nd order metod or ordnr derentl eutons nd ow to use t to solve roblems. Wt s te Runge-Kutt

More information

Detection and Estimation Theory

Detection and Estimation Theory ESE 54 Detecton and Etmaton Theoy Joeph A. O Sullvan Samuel C. Sach Pofeo Electonc Sytem and Sgnal Reeach Laboatoy Electcal and Sytem Engneeng Wahngton Unvety 411 Jolley Hall 314-935-4173 (Lnda anwe) jao@wutl.edu

More information

Model Fitting and Robust Regression Methods

Model Fitting and Robust Regression Methods Dertment o Comuter Engneerng Unverst o Clorn t Snt Cruz Model Fttng nd Robust Regresson Methods CMPE 64: Imge Anlss nd Comuter Vson H o Fttng lnes nd ellses to mge dt Dertment o Comuter Engneerng Unverst

More information

Math 4318 : Real Analysis II Mid-Term Exam 1 14 February 2013

Math 4318 : Real Analysis II Mid-Term Exam 1 14 February 2013 Mth 4318 : Rel Anlysis II Mid-Tem Exm 1 14 Febuy 2013 Nme: Definitions: Tue/Flse: Poofs: 1. 2. 3. 4. 5. 6. Totl: Definitions nd Sttements of Theoems 1. (2 points) Fo function f(x) defined on (, b) nd fo

More information

Chapter Linear Regression

Chapter Linear Regression Chpte 6.3 Le Regesso Afte edg ths chpte, ou should be ble to. defe egesso,. use sevel mmzg of esdul cte to choose the ght cteo, 3. deve the costts of le egesso model bsed o lest sques method cteo,. use

More information

Chapter Newton-Raphson Method of Solving a Nonlinear Equation

Chapter Newton-Raphson Method of Solving a Nonlinear Equation Chpter 0.04 Newton-Rphson Method o Solvng Nonlner Equton Ater redng ths chpter, you should be ble to:. derve the Newton-Rphson method ormul,. develop the lgorthm o the Newton-Rphson method,. use the Newton-Rphson

More information

c( 1) c(0) c(1) Note z 1 represents a unit interval delay Figure 85 3 Transmit equalizer functional model

c( 1) c(0) c(1) Note z 1 represents a unit interval delay Figure 85 3 Transmit equalizer functional model Relace 85.8.3.2 with the following: 85.8.3.2 Tansmitted outut wavefom The 40GBASE-CR4 and 100GBASE-CR10 tansmit function includes ogammable equalization to comensate fo the fequency-deendent loss of the

More information

8. INVERSE Z-TRANSFORM

8. INVERSE Z-TRANSFORM 8. INVERSE Z-TRANSFORM The proce by whch Z-trnform of tme ere, nmely X(), returned to the tme domn clled the nvere Z-trnform. The nvere Z-trnform defned by: Computer tudy Z X M-fle trn.m ued to fnd nvere

More information

Torque generation with Electrical Machines. Industrial Electrical Engineering and Automation Lund University, Sweden

Torque generation with Electrical Machines. Industrial Electrical Engineering and Automation Lund University, Sweden Toqe geneton wth Electcl Mchne Indtl Electcl Engneeng nd Atoton nd Unvet, Sweden Toqe genetng phenoen Indtl Electcl Engneeng nd Atoton Condcto n gnetc feld Ion hpe n gnetc feld 3 Electottc 4 Pezotcton

More information

Quality control. Final exam: 2012/1/12 (Thur), 9:00-12:00 Q1 Q2 Q3 Q4 Q5 YOUR NAME

Quality control. Final exam: 2012/1/12 (Thur), 9:00-12:00 Q1 Q2 Q3 Q4 Q5 YOUR NAME Qulity contol Finl exm: // (Thu), 9:-: Q Q Q3 Q4 Q5 YOUR NAME NOTE: Plese wite down the deivtion of you nswe vey clely fo ll questions. The scoe will be educed when you only wite nswe. Also, the scoe will

More information

EFFECTIVE THERMAL CONDUCTIVITY AND DIFFUSIVITY IN HETEROGENEOUS MATERIALS

EFFECTIVE THERMAL CONDUCTIVITY AND DIFFUSIVITY IN HETEROGENEOUS MATERIALS EFFECIVE HERMAL CONDUCIVIY AND DIFFUSIVIY IN HEEROGENEOUS MAERIALS Štefn Bt Detment of Physcs, Fculty of Electcl Enneen n Infomton echnoloy, Slovk Unvesty of echnoloy, Ilkovčov 3, SK-8 9 Btslv, Slovk Eml:

More information

Absolutely no collaboration allowed in any form

Absolutely no collaboration allowed in any form Toy Fnl Exm poste toy, ue n one week Tke home, open notes exm Absolutely no collboton llowe n ny fom Instuctos wll not nswe ny uestons elte to exm solutons o soluton ppoches Questons fo clfcton shoul be

More information

St Andrew s Academy Mathematics Department Higher Mathematics VECTORS

St Andrew s Academy Mathematics Department Higher Mathematics VECTORS St ndew s cdemy Mthemtics etment Highe Mthemtics VETORS St ndew's cdemy Mths et 0117 1 Vectos sics 1. = nd = () Sketch the vectos nd. () Sketch the vectos nd. (c) Given u = +, sketch the vecto u. (d) Given

More information

U>, and is negative. Electric Potential Energy

U>, and is negative. Electric Potential Energy Electic Potentil Enegy Think of gvittionl potentil enegy. When the lock is moved veticlly up ginst gvity, the gvittionl foce does negtive wok (you do positive wok), nd the potentil enegy (U) inceses. When

More information

EN2210: Continuum Mechanics. Homework 4: Balance laws, work and energy, virtual work Due 12:00 noon Friday February 4th

EN2210: Continuum Mechanics. Homework 4: Balance laws, work and energy, virtual work Due 12:00 noon Friday February 4th EN: Contnuum Mechncs Homewok 4: Blnce lws, wok nd enegy, vtul wok Due : noon Fdy Feuy 4th chool of Engneeng Bown Unvesty. how tht the locl mss lnce equton t cn e e-wtten n sptl fom s xconst v y v t yconst

More information

A Revision Article of Oil Wells Performance Methods

A Revision Article of Oil Wells Performance Methods A Revisin Aticle Oil Wells emnce Methds The ductivity inde well, dented y, is mesue the ility the well t duce. It is given y: Whee: Welle ductivity inde, STB/dy/sig Avege (sttic) esevi essue, sig Welle

More information

Neural Network Introduction. Hung-yi Lee

Neural Network Introduction. Hung-yi Lee Neu Neto Intoducton Hung- ee Reve: Supevsed enng Mode Hpothess Functon Set f, f : : (e) Tnng: Pc the est Functon f * Best Functon f * Testng: f Tnng Dt : functon nput : functon output, ˆ,, ˆ, Neu Neto

More information

19 The Born-Oppenheimer Approximation

19 The Born-Oppenheimer Approximation 9 The Bon-Oppenheme Appoxmaton The full nonelatvstc Hamltonan fo a molecule s gven by (n a.u.) Ĥ = A M A A A, Z A + A + >j j (883) Lets ewte the Hamltonan to emphasze the goal as Ĥ = + A A A, >j j M A

More information

Energy in Closed Systems

Energy in Closed Systems Enegy n Closed Systems Anamta Palt palt.anamta@gmal.com Abstact The wtng ndcates a beakdown of the classcal laws. We consde consevaton of enegy wth a many body system n elaton to the nvese squae law and

More information

If there are k binding constraints at x then re-label these constraints so that they are the first k constraints.

If there are k binding constraints at x then re-label these constraints so that they are the first k constraints. Mathematcal Foundatons -1- Constaned Optmzaton Constaned Optmzaton Ma{ f ( ) X} whee X {, h ( ), 1,, m} Necessay condtons fo to be a soluton to ths mamzaton poblem Mathematcally, f ag Ma{ f ( ) X}, then

More information

Lecture 4: Piecewise Cubic Interpolation

Lecture 4: Piecewise Cubic Interpolation Lecture notes on Vrtonl nd Approxmte Methods n Appled Mthemtcs - A Perce UBC Lecture 4: Pecewse Cubc Interpolton Compled 6 August 7 In ths lecture we consder pecewse cubc nterpolton n whch cubc polynoml

More information

Modeling, Estimation and Optimal Filtering in Signal Processing

Modeling, Estimation and Optimal Filtering in Signal Processing Modelng, Estmton nd Otml Flteng n Sgnl Pocessng Modelng, Estmton nd Otml Flteng n Sgnl Pocessng Mohmed jm Fst ublshed n Fnce n 6 b emes Scence/Lvose enttled Modélston, estmton et fltge otml en ttement

More information

Physics 11b Lecture #11

Physics 11b Lecture #11 Physics 11b Lectue #11 Mgnetic Fields Souces of the Mgnetic Field S&J Chpte 9, 3 Wht We Did Lst Time Mgnetic fields e simil to electic fields Only diffeence: no single mgnetic pole Loentz foce Moving chge

More information

Topics for Review for Final Exam in Calculus 16A

Topics for Review for Final Exam in Calculus 16A Topics fo Review fo Finl Em in Clculus 16A Instucto: Zvezdelin Stnkov Contents 1. Definitions 1. Theoems nd Poblem Solving Techniques 1 3. Eecises to Review 5 4. Chet Sheet 5 1. Definitions Undestnd the

More information

Lecture 10. Solution of Nonlinear Equations - II

Lecture 10. Solution of Nonlinear Equations - II Fied point Poblems Lectue Solution o Nonline Equtions - II Given unction g : R R, vlue such tht gis clled ied point o the unction g, since is unchnged when g is pplied to it. Whees with nonline eqution

More information

V. Principles of Irreversible Thermodynamics. s = S - S 0 (7.3) s = = - g i, k. "Flux": = da i. "Force": = -Â g a ik k = X i. Â J i X i (7.

V. Principles of Irreversible Thermodynamics. s = S - S 0 (7.3) s = = - g i, k. Flux: = da i. Force: = -Â g a ik k = X i. Â J i X i (7. Themodynamcs and Knetcs of Solds 71 V. Pncples of Ievesble Themodynamcs 5. Onsage s Teatment s = S - S 0 = s( a 1, a 2,...) a n = A g - A n (7.6) Equlbum themodynamcs detemnes the paametes of an equlbum

More information

ME306 Dynamics, Spring HW1 Solution Key. AB, where θ is the angle between the vectors A and B, the proof

ME306 Dynamics, Spring HW1 Solution Key. AB, where θ is the angle between the vectors A and B, the proof ME6 Dnms, Spng HW Slutn Ke - Pve, gemetll.e. usng wngs sethes n nltll.e. usng equtns n nequltes, tht V then V. Nte: qunttes n l tpee e vets n n egul tpee e sls. Slutn: Let, Then V V V We wnt t pve tht:

More information

UNIT10 PLANE OF REGRESSION

UNIT10 PLANE OF REGRESSION UIT0 PLAE OF REGRESSIO Plane of Regesson Stuctue 0. Intoducton Ojectves 0. Yule s otaton 0. Plane of Regesson fo thee Vaales 0.4 Popetes of Resduals 0.5 Vaance of the Resduals 0.6 Summay 0.7 Solutons /

More information

Set of square-integrable function 2 L : function space F

Set of square-integrable function 2 L : function space F Set of squae-ntegable functon L : functon space F Motvaton: In ou pevous dscussons we have seen that fo fee patcles wave equatons (Helmholt o Schödnge) can be expessed n tems of egenvalue equatons. H E,

More information

Lecture 9-3/8/10-14 Spatial Description and Transformation

Lecture 9-3/8/10-14 Spatial Description and Transformation Letue 9-8- tl Deton nd nfomton Homewo No. Due 9. Fme ngement onl. Do not lulte...8..7.8 Otonl et edt hot oof tht = - Homewo No. egned due 9 tud eton.-.. olve oblem:.....7.8. ee lde 6 7. e Mtlb on. f oble.

More information

Solution of Tutorial 5 Drive dynamics & control

Solution of Tutorial 5 Drive dynamics & control ELEC463 Unversty of New South Wles School of Electrcl Engneerng & elecommunctons ELEC463 Electrc Drve Systems Queston Motor Soluton of utorl 5 Drve dynmcs & control 500 rev/mn = 5.3 rd/s 750 rted 4.3 Nm

More information

Fluids & Bernoulli s Equation. Group Problems 9

Fluids & Bernoulli s Equation. Group Problems 9 Goup Poblems 9 Fluids & Benoulli s Eqution Nme This is moe tutoil-like thn poblem nd leds you though conceptul development of Benoulli s eqution using the ides of Newton s 2 nd lw nd enegy. You e going

More information

FI 2201 Electromagnetism

FI 2201 Electromagnetism FI 1 Electomgnetism Alexnde A. Isknd, Ph.D. Physics of Mgnetism nd Photonics Resech Goup Electosttics ELECTRIC PTENTIALS 1 Recll tht we e inteested to clculte the electic field of some chge distiution.

More information

Optimization. x = 22 corresponds to local maximum by second derivative test

Optimization. x = 22 corresponds to local maximum by second derivative test Optimiztion Lectue 17 discussed the exteme vlues of functions. This lectue will pply the lesson fom Lectue 17 to wod poblems. In this section, it is impotnt to emembe we e in Clculus I nd e deling one-vible

More information

Discrete Model Parametrization

Discrete Model Parametrization Poceedings of Intentionl cientific Confeence of FME ession 4: Automtion Contol nd Applied Infomtics Ppe 9 Discete Model Pmetition NOKIEVIČ, Pet Doc,Ing,Cc Deptment of Contol ystems nd Instumenttion, Fculty

More information

M/G/1/GD/ / System. ! Pollaczek-Khinchin (PK) Equation. ! Steady-state probabilities. ! Finding L, W q, W. ! π 0 = 1 ρ

M/G/1/GD/ / System. ! Pollaczek-Khinchin (PK) Equation. ! Steady-state probabilities. ! Finding L, W q, W. ! π 0 = 1 ρ M/G//GD/ / System! Pollcze-Khnchn (PK) Equton L q 2 2 λ σ s 2( + ρ ρ! Stedy-stte probbltes! π 0 ρ! Fndng L, q, ) 2 2 M/M/R/GD/K/K System! Drw the trnston dgrm! Derve the stedy-stte probbltes:! Fnd L,L

More information

School of Electrical and Computer Engineering, Cornell University. ECE 303: Electromagnetic Fields and Waves. Fall 2007

School of Electrical and Computer Engineering, Cornell University. ECE 303: Electromagnetic Fields and Waves. Fall 2007 School of Electicl nd Compute Engineeing, Conell Univesity ECE 303: Electomgnetic Fields nd Wves Fll 007 Homewok 4 Due on Sep. 1, 007 by 5:00 PM Reding Assignments: i) Review the lectue notes. ii) Relevnt

More information

MATHEMATICS II PUC VECTOR ALGEBRA QUESTIONS & ANSWER

MATHEMATICS II PUC VECTOR ALGEBRA QUESTIONS & ANSWER MATHEMATICS II PUC VECTOR ALGEBRA QUESTIONS & ANSWER I One M Queston Fnd the unt veto n the deton of Let ˆ ˆ 9 Let & If Ae the vetos & equl? But vetos e not equl sne the oespondng omponents e dstnt e detons

More information

Investigation phase in case of Bragg coupling

Investigation phase in case of Bragg coupling Journl of Th-Qr Unversty No.3 Vol.4 December/008 Investgton phse n cse of Brgg couplng Hder K. Mouhmd Deprtment of Physcs, College of Scence, Th-Qr, Unv. Mouhmd H. Abdullh Deprtment of Physcs, College

More information

3. A Review of Some Existing AW (BT, CT) Algorithms

3. A Review of Some Existing AW (BT, CT) Algorithms 3. A Revew of Some Exstng AW (BT, CT) Algothms In ths secton, some typcal ant-wndp algothms wll be descbed. As the soltons fo bmpless and condtoned tansfe ae smla to those fo ant-wndp, the pesented algothms

More information

Remember: Project Proposals are due April 11.

Remember: Project Proposals are due April 11. Bonformtcs ecture Notes Announcements Remember: Project Proposls re due Aprl. Clss 22 Aprl 4, 2002 A. Hdden Mrov Models. Defntons Emple - Consder the emple we tled bout n clss lst tme wth the cons. However,

More information

This immediately suggests an inverse-square law for a "piece" of current along the line.

This immediately suggests an inverse-square law for a piece of current along the line. Electomgnetic Theoy (EMT) Pof Rui, UNC Asheville, doctophys on YouTube Chpte T Notes The iot-svt Lw T nvese-sque Lw fo Mgnetism Compe the mgnitude of the electic field t distnce wy fom n infinite line

More information

Demand. Demand and Comparative Statics. Graphically. Marshallian Demand. ECON 370: Microeconomic Theory Summer 2004 Rice University Stanley Gilbert

Demand. Demand and Comparative Statics. Graphically. Marshallian Demand. ECON 370: Microeconomic Theory Summer 2004 Rice University Stanley Gilbert Demnd Demnd nd Comrtve Sttcs ECON 370: Mcroeconomc Theory Summer 004 Rce Unversty Stnley Glbert Usng the tools we hve develoed u to ths ont, we cn now determne demnd for n ndvdul consumer We seek demnd

More information

Week 10: DTMC Applications Ranking Web Pages & Slotted ALOHA. Network Performance 10-1

Week 10: DTMC Applications Ranking Web Pages & Slotted ALOHA. Network Performance 10-1 Week : DTMC Alictions Rnking Web ges & Slotted ALOHA etwok efonce - Outline Aly the theoy of discete tie Mkov chins: Google s nking of web-ges Wht ge is the use ost likely seching fo? Foulte web-gh s Mkov

More information

Multistage Median Ranked Set Sampling for Estimating the Population Median

Multistage Median Ranked Set Sampling for Estimating the Population Median Jounal of Mathematcs and Statstcs 3 (: 58-64 007 ISSN 549-3644 007 Scence Publcatons Multstage Medan Ranked Set Samplng fo Estmatng the Populaton Medan Abdul Azz Jeman Ame Al-Oma and Kamaulzaman Ibahm

More information

COMPLEMENTARY ENERGY METHOD FOR CURVED COMPOSITE BEAMS

COMPLEMENTARY ENERGY METHOD FOR CURVED COMPOSITE BEAMS ultscence - XXX. mcocd Intenatonal ultdscplnay Scentfc Confeence Unvesty of skolc Hungay - pl 06 ISBN 978-963-358-3- COPLEENTRY ENERGY ETHOD FOR CURVED COPOSITE BES Ákos József Lengyel István Ecsed ssstant

More information

A Method of Reliability Target Setting for Electric Power Distribution Systems Using Data Envelopment Analysis

A Method of Reliability Target Setting for Electric Power Distribution Systems Using Data Envelopment Analysis 27 กก ก 9 2-3 2554 ก ก ก A Method of Relablty aget Settng fo Electc Powe Dstbuton Systems Usng Data Envelopment Analyss ก 2 ก ก ก ก ก 0900 2 ก ก ก ก ก 0900 E-mal: penjan262@hotmal.com Penjan Sng-o Psut

More information

ELECTROMAGNETISM. at a point whose position vector with respect to a current element i d l is r. According to this law :

ELECTROMAGNETISM. at a point whose position vector with respect to a current element i d l is r. According to this law : ELECTROMAGNETISM ot-svt Lw: Ths w s used to fnd the gnetc fed d t pont whose poston vecto wth espect to cuent eeent d s. Accodng to ths w : µ d ˆ d = 4π d d The tot fed = d θ P whee ˆ s unt vecto n the

More information

Previously. Extensions to backstepping controller designs. Tracking using backstepping Suppose we consider the general system

Previously. Extensions to backstepping controller designs. Tracking using backstepping Suppose we consider the general system 436-459 Advnced contol nd utomtion Extensions to bckstepping contolle designs Tcking Obseves (nonline dmping) Peviously Lst lectue we looked t designing nonline contolles using the bckstepping technique

More information

Generalized q-integrals via neutrices: Application to the q-beta function

Generalized q-integrals via neutrices: Application to the q-beta function Flomt 7:8 3), 473 483 DOI.98/FIL38473S Publshed by Fculty of Scences nd Mthemtcs, Unvesty of Nš, Seb Avlble t: http://www.pmf.n.c.s/flomt Genelzed q-ntegls v neutces: Applcton to the q-bet functon Ahmed

More information

CHAPTER 18: ELECTRIC CHARGE AND ELECTRIC FIELD

CHAPTER 18: ELECTRIC CHARGE AND ELECTRIC FIELD ollege Physics Student s Mnul hpte 8 HAPTR 8: LTRI HARG AD LTRI ILD 8. STATI LTRIITY AD HARG: OSRVATIO O HARG. ommon sttic electicity involves chges nging fom nnocoulombs to micocoulombs. () How mny electons

More information

Electric Potential. and Equipotentials

Electric Potential. and Equipotentials Electic Potentil nd Euipotentils U Electicl Potentil Review: W wok done y foce in going fom to long pth. l d E dl F W dl F θ Δ l d E W U U U Δ Δ l d E W U U U U potentil enegy electic potentil Potentil

More information

Effects of polarization on the reflected wave

Effects of polarization on the reflected wave Lecture Notes. L Ros PPLIED OPTICS Effects of polrzton on the reflected wve Ref: The Feynmn Lectures on Physcs, Vol-I, Secton 33-6 Plne of ncdence Z Plne of nterfce Fg. 1 Y Y r 1 Glss r 1 Glss Fg. Reflecton

More information

Chapter Fifiteen. Surfaces Revisited

Chapter Fifiteen. Surfaces Revisited Chapte Ffteen ufaces Revsted 15.1 Vecto Descpton of ufaces We look now at the vey specal case of functons : D R 3, whee D R s a nce subset of the plane. We suppose s a nce functon. As the pont ( s, t)

More information

DEPARTMENT OF CIVIL AND ENVIRONMENTAL ENGINEERING FLUID MECHANICS III Solutions to Problem Sheet 3

DEPARTMENT OF CIVIL AND ENVIRONMENTAL ENGINEERING FLUID MECHANICS III Solutions to Problem Sheet 3 DEPATMENT OF CIVIL AND ENVIONMENTAL ENGINEEING FLID MECHANICS III Solutions to Poblem Sheet 3 1. An tmospheic vote is moelle s combintion of viscous coe otting s soli boy with ngul velocity Ω n n iottionl

More information

Distinct 8-QAM+ Perfect Arrays Fanxin Zeng 1, a, Zhenyu Zhang 2,1, b, Linjie Qian 1, c

Distinct 8-QAM+ Perfect Arrays Fanxin Zeng 1, a, Zhenyu Zhang 2,1, b, Linjie Qian 1, c nd Intenatonal Confeence on Electcal Compute Engneeng and Electoncs (ICECEE 15) Dstnct 8-QAM+ Pefect Aays Fanxn Zeng 1 a Zhenyu Zhang 1 b Lnje Qan 1 c 1 Chongqng Key Laboatoy of Emegency Communcaton Chongqng

More information

(8) Gain Stage and Simple Output Stage

(8) Gain Stage and Simple Output Stage EEEB23 Electoncs Analyss & Desgn (8) Gan Stage and Smple Output Stage Leanng Outcome Able to: Analyze an example of a gan stage and output stage of a multstage amplfe. efeence: Neamen, Chapte 11 8.0) ntoducton

More information

SPA7010U/SPA7010P: THE GALAXY. Solutions for Coursework 1. Questions distributed on: 25 January 2018.

SPA7010U/SPA7010P: THE GALAXY. Solutions for Coursework 1. Questions distributed on: 25 January 2018. SPA7U/SPA7P: THE GALAXY Solutions fo Cousewok Questions distibuted on: 25 Jnuy 28. Solution. Assessed question] We e told tht this is fint glxy, so essentilly we hve to ty to clssify it bsed on its spectl

More information

The Backpropagation Algorithm

The Backpropagation Algorithm The Backpopagaton Algothm Achtectue of Feedfowad Netwok Sgmodal Thehold Functon Contuctng an Obectve Functon Tanng a one-laye netwok by teepet decent Tanng a two-laye netwok by teepet decent Copyght Robet

More information

A Heuristic Algorithm for the Scheduling Problem of Parallel Machines with Mold Constraints

A Heuristic Algorithm for the Scheduling Problem of Parallel Machines with Mold Constraints A Heustc Algothm fo the Schedulng Poblem of Pllel Mchnes wth Mold Constnts TZUNG-PEI HONG 1, PEI-CHEN SUN 2, nd SHIN-DAI LI 2 1 Deptment of Compute Scence nd Infomton Engneeng Ntonl Unvesty of Kohsung

More information

Lecture (10) Reactor Sizing and Design

Lecture (10) Reactor Sizing and Design Lectue ( Rect Szng nd esgn. Genel Mle lnce Equtn Mle blnce n speces t ny nstnce n tme t ; lumn system te f flw te f genetn te f flw te f ccumultn f nt system f n systemby xn f ut f system f wthn system

More information

Tian Zheng Department of Statistics Columbia University

Tian Zheng Department of Statistics Columbia University Haplotype Tansmsson Assocaton (HTA) An "Impotance" Measue fo Selectng Genetc Makes Tan Zheng Depatment of Statstcs Columba Unvesty Ths s a jont wok wth Pofesso Shaw-Hwa Lo n the Depatment of Statstcs at

More information

NP-Completeness : Proofs

NP-Completeness : Proofs NP-Completeness : Proofs Proof Methods A method to show a decson problem Π NP-complete s as follows. (1) Show Π NP. (2) Choose an NP-complete problem Π. (3) Show Π Π. A method to show an optmzaton problem

More information

STD: XI MATHEMATICS Total Marks: 90. I Choose the correct answer: ( 20 x 1 = 20 ) a) x = 1 b) x =2 c) x = 3 d) x = 0

STD: XI MATHEMATICS Total Marks: 90. I Choose the correct answer: ( 20 x 1 = 20 ) a) x = 1 b) x =2 c) x = 3 d) x = 0 STD: XI MATHEMATICS Totl Mks: 90 Time: ½ Hs I Choose the coect nswe: ( 0 = 0 ). The solution of is ) = b) = c) = d) = 0. Given tht the vlue of thid ode deteminnt is then the vlue of the deteminnt fomed

More information

Using Predictions in Online Optimization: Looking Forward with an Eye on the Past

Using Predictions in Online Optimization: Looking Forward with an Eye on the Past Usng Predctons n Onlne Optmzton: Lookng Forwrd wth n Eye on the Pst Nngjun Chen Jont work wth Joshu Comden, Zhenhu Lu, Anshul Gndh, nd Adm Wermn 1 Predctons re crucl for decson mkng 2 Predctons re crucl

More information

The analysis of dynamic response of rock mass around tunnel under dynamic unloading. Xian Li1, a

The analysis of dynamic response of rock mass around tunnel under dynamic unloading. Xian Li1, a 4th Intentonl Confeence on Sustnble Enegy nd Envonmentl Engneeng (ICSEEE 5) The nlyss of dynmc esponse of ock mss ound tunnel unde dynmc unlodng Xn L, Fculty of Cvl Engneeng nd Mechncs, Kunmng Unvesty

More information

Partially Observable Systems. 1 Partially Observable Markov Decision Process (POMDP) Formalism

Partially Observable Systems. 1 Partially Observable Markov Decision Process (POMDP) Formalism CS294-40 Lernng for Rootcs nd Control Lecture 10-9/30/2008 Lecturer: Peter Aeel Prtlly Oservle Systems Scre: Dvd Nchum Lecture outlne POMDP formlsm Pont-sed vlue terton Glol methods: polytree, enumerton,

More information

Applied Statistics Qualifier Examination

Applied Statistics Qualifier Examination Appled Sttstcs Qulfer Exmnton Qul_june_8 Fll 8 Instructons: () The exmnton contns 4 Questons. You re to nswer 3 out of 4 of them. () You my use ny books nd clss notes tht you mght fnd helpful n solvng

More information

Chapter 17. Least Square Regression

Chapter 17. Least Square Regression The Islmc Uvest of Gz Fcult of Egeeg Cvl Egeeg Deptmet Numecl Alss ECIV 336 Chpte 7 Lest que Regesso Assocte Pof. Mze Abultef Cvl Egeeg Deptmet, The Islmc Uvest of Gz Pt 5 - CURVE FITTING Descbes techques

More information

Answers to test yourself questions

Answers to test yourself questions Answes to test youself questions opic Descibing fields Gm Gm Gm Gm he net field t is: g ( d / ) ( 4d / ) d d Gm Gm Gm Gm Gm Gm b he net potentil t is: V d / 4d / d 4d d d V e 4 7 9 49 J kg 7 7 Gm d b E

More information

Quiz: Experimental Physics Lab-I

Quiz: Experimental Physics Lab-I Mxmum Mrks: 18 Totl tme llowed: 35 mn Quz: Expermentl Physcs Lb-I Nme: Roll no: Attempt ll questons. 1. In n experment, bll of mss 100 g s dropped from heght of 65 cm nto the snd contner, the mpct s clled

More information

9.4 The response of equilibrium to temperature (continued)

9.4 The response of equilibrium to temperature (continued) 9.4 The esponse of equilibium to tempetue (continued) In the lst lectue, we studied how the chemicl equilibium esponds to the vition of pessue nd tempetue. At the end, we deived the vn t off eqution: d

More information