APPLICATIONS OF RELIABILITY ANALYSIS TO POWER ELECTRONICS SYSTEMS

Size: px
Start display at page:

Download "APPLICATIONS OF RELIABILITY ANALYSIS TO POWER ELECTRONICS SYSTEMS"

Transcription

1 APPLICATIONS OF RELIABILITY ANALYSIS TO POWER ELECTRONICS SYSTEMS Chanan Sngh, Fellow IEEE Praad Enjet, Fellow IEEE Department o Electrcal Engneerng Texa A&M Unverty College Staton, Texa USA Joydeep Mtra, Sr. Member IEEE Department o Electrcal & Computer Engneerng North Dakota State Unverty Fargo, North Dakota USA ABSTRACT Relablty and cot conderaton play an mportant role n the choce o varou alternatve. Thee could be alternate degn to meet an objectve or could be alternate plannng cenaro. To be able to make tradeo between cot and relablty, relablty need to be quanted and there need to be method or predctng the relablty. Th paper decrbe three technque o relablty analy, a technque baed on Markov procee, cut et method and Monte Carlo mulaton. Thee technque are llutrated ung two example. The Markov proce llutrated by applcaton to tudy ault tolerant eature n PEBB baed converter conguraton. Smlarly the Monte Carlo mulaton and cut et technque are llutrated by applcaton to tandby power ytem ncludng unnterruptble power upply ytem. BACKGROUND Th ecton gve a bre ntroducton o the relablty evaluaton method. There are many method avalable n the lterature; here three method wll be revewed. The two analytcal method are the Markov procee and cut et and one orm o Monte Carlo Smulaton alo decrbed. ANALYTICAL METHOD The analytcal method decrbed here ue the concept o Markov chan and Markov cut-et. A detaled treatment o thee technque avalable n [1]; a ummary o the method preented here. Markov Chan A Markov chan a equence o event contng o the tranton o a component or ytem o component amongt a et o tate uch that the tate to whch the component or ytem trant n the uture depend only on the current tate o the component or ytem and not on the tate t ha tranted 1

2 through n the pat. I a ytem conorm to (or, more realtcally, approxmate) th behavor, then the theory o Markov chan may be appled to t. In th knd o analy, normaton o ntertate tranton rate ued to determne the rate o trantng to alure tate. The tranton rate rom tate to tate j the mean rate o the ytem pang rom tate to tate j. In th paper, the duraton o component tate are aumed exponentally dtrbuted, whch mean that the ntertate tranton rate are contant. Th explaned n the next ecton. The tate probablte can be obtaned by olvng BP = C (1) where B matrx obtaned rom A by replacng the element o an arbtrarly elected row k by 1; A matrx o tranton rate uch that the element a j = j and a = a ; j contant tranton rate rom tate to j; P column vector whoe th term p the teady-tate probablty o the ytem beng n tate ; C column vector wth kth element equal to one and other element et to zero. j j Once the teady-tate probablte have been calculated, the relablty ndce [1] can be computed ung the ollowng relatonhp. Frequency o ytem alure: The relatonhp or the requency o ytem alure [1] gven by Eq. (2) or Eq. (3) = p ( S F) = F j F j p (3) j j ( S F) (2) where the requency o the ytem alure, S the ytem tate pace and F the ubet o aled tate. Mean Down Tme: The expected tme o tay n F n one cycle where r P / = (4) 2

3 P = (5) p F Cut Set A cut et a et o component that, removed rom the ytem, reult n lo o power to the load pont. I th et doe not contan any cut et a a ubet, then t called a mnmal cut et. In th denton, component ued n a wder ene o hardware or a partcular ytem condton. In general cut et contanng m component are called m-order cut et. Generally up to econd order cut et are condered and the contrbuton rom hgher order cut et condered neglgble. The ollowng relatonhp are mportant n cut et calculaton. 1) Frequency and duraton o a cut et (a) Frt order cut et [6] : c = (6) r = r (7) c where, r = requency and mean duraton o cut et c c, r = alure rate and mean duraton o component comprng cut et (b) Second order cut et [6] = r + r) (8) c j( j r c = rr j/( r + rj) (9) where, = alure rate o component and j comprng cut et j r, r= mean alure duraton o component and j comprng cut et j (c) Condtonal econd order cut et [6]: Aumng that component al gven component j ha aled, c = r) (10) j ( j r c = rr j/( r + rj) (11) 3

4 The term alure requency and alure rate are oten ued nterchangeably. Strctly peakng alure rate the mean number o alure per unt o the up tme and alure requency the mean number o alure per unt o the total tme. I the probablty o ytem beng up cloe to unty, then thee two quantte are very cloe. In general, alure requency le than alure rate. 2) Frequency and duraton o nterrupton [6]: = requency o load nterrupton = (12) c r = mean duraton o load nterrupton = r / (13) c c The theory concernng Markov chan and mnmal cut-et dealt wth n greater detal n (4). Thee concept are ued a ollow to analyze the ample ytem. Monte Carlo mulaton Th another method o determnng relablty ndce. Th method decrbed n detal n [1], whle an applcaton o th method to the ample ytem gven n [9]. A ummary o the method preented here. The relablty ndce o an actual phycal ytem can be etmated by collectng data on the occurrence o alure and the duraton o repar. The Monte Carlo method mmc the alure and repar htory o the component and the ytem by ung the probablty dtrbuton o the component tate duraton. Stattc are then collected and ndce etmated ung tattcal nerence. Though there are derent way o mplementng Monte Carlo mulaton, the technque decrbed here the next event method and capable o mulatng dependent event. Th a equental mulaton method whch proceed by generatng a equence o event ung random number and probablty dtrbuton o random varable repreentng component tate duraton. A lowchart gven n Fg. 1. The nput data cont o the alure rate () and mean down tme (r) o every component. The alure rate the recprocal o the mean up tme. The mean down tme the recprocal o the repar rate (µ). The alure and repar rate, and µ, o a component wll be ued to determne how long the component wll reman n the UP tate and the DOWN tate. Smulaton could be tarted rom any ytem tate, but t cutomary to begn mulaton wth all the component n the UP tate. 4

5 START READ FAILURE RATE AND DURATION DATA FOR ALL COMPONENTS SET INITIAL STATE OF ALL COMPONENTS AS UP FOR EACH COMPONENT DRAW A RANDOM NUMBER AND COMPUTE THE TIME TO THE NEXT EVENT FIND THE MINIMUM TIME AND CHANGE THE STATE OF THE CORRESPONDING COMPONENT; UPDATE TOTAL TIME NO IS THERE A CHANGE IN SYSTEM STATUS? YES UPDATE INDICES SIMULATION CONVERGED? NO YES PRINT OUTPUT STOP Fg. 1. Flowchart or next-event mulaton. The tme to the next event generated by ung the nvere o probablty dtrbuton method. Th explaned a ollow. I the tranton tme o the component are aumed to be exponentally dtrbuted: t ( t) = ρe ρ (14) where ρ the tranton rate. The mean tranton tme, thereore, 0 1 ( t) dt= (15) ρ 5

6 Th mean that, or ntance, a component UP, then, regardle o how long t ha been n the UP tate, the expected tme to the next alure 1/,.e., the mean up tme. The probablty dtrbuton uncton o the tranton tme T would be F( t) t ρt = P( t T) = ρe dτ = 1 0 e ρt (16) Now F(t) can be regarded a a random varable, unormly dtrbuted between 0 and 1. Th mean that the urvvor uncton S ρt ( T) = 1 F( T) = e (17) alo unormly dtrbuted between 0 and 1. So a random number R generated, n 0 R 1, t can be aocated wth the event that the next tranton occur ater tme t r, gven by n ρt r R n = e, that, ln( Rn) tr = (18) ρ Th method ued to determne the tme to the next tranton or every component, ung or µ or ρ, dependng on whether the component UP or DOWN. At the end o any mulated tme nterval [0, t], where t = total up tme n [0, t] + total down tme n [0, t], the etmate o the relablty ndce are gven a ollow. alure rate: number o alure n [0, t] t = (19) totaluptmen [0, t] mean down tme: totaldown tmen [0, t] r t = (20) number o alure n [0, t] The value o and r at the ntant the mulaton converge are the relablty ndce or the ytem a obtaned rom the Monte Carlo method. The mulaton ad to have converged when the ndce attan table value. Th tablzaton o the value o an ndex meaured by t tandard error, dened a: σ η = (21) n c 6

7 where σ = tandard devaton o the ndex n = number o cycle mulated c Convergence ad to occur when the tandard error drop below a prepeced racton, ε, o the ndex,.e., when η ε (22) I, or ntance, the mean down tme r choen a the ndex to converge upon, then, ater every ytem retoraton mulated, the ollowng relaton teted or valdty: σ r ε r (23) n c I th crteron ated, the mulaton ad to have converged. Smulaton advantageou n that t not only allow the computaton o ndce at varou pont n the ytem, but alo permt the accumulaton o data pertanng to the dtrbuton o thee ndce, thereby aordng a better undertandng o the ytem behavor. APPLICATIONS The technque decrbed n the paper are llutrated by two applcaton. The rt applcaton to model ault tolerant eature n the PEBB- baed converter propoed n re. [3]. The econd applcaton the tudy o relablty mprovement by ung UPS a tandby power MODELING FAULT TOLERANT FEATURES IN THE PEBB-BASED CONVERTERS [3] In th ecton a modelng approach preented to analyze the ault tolerant behavor o PEBB baed converter propoed n [3]. Fg. 2 (a) how a detaled connecton dagram o combnng three, 3-phae nverter block wth 18 IGBT wtche. The nterconnecton nductance between the module lmt the hgh requency crculatng current. Fg. 2 (b) how the vector dagram o the undamental voltage generated by IGBT wtch par. 1. Fault Tolerant Feature & Relablty Analy: 7

8 From Fg. 2 (a) and (b) t clear that alure (open crcut) o IGBT wtche 3,6 and 7,10 or 2,5 and 13,16 or 15,18 and 8,11 reult n an open delta tuaton and the modular nverter are tll capable o upplyng the load at a reduced power level. However, the alure o IGBT wtch par 1,4 or 9,12 or 14,17 wll caue a crtcal alure and reult n a ytem hut down. The trade o between relablty and cot can be acheved by the knowledge o cot o nterrupton and contructng relablty model and computng the relablty ndce. The two ndce that are ueul n th tuaton are: 1. Frequency o alure: Th the mean number o alure per year. 2. Mean duraton o alure: Th the mean duraton o a alure event. The cot o nterrupton n ome applcaton depend on the total down tme wherea n other applcaton the requency o nterrupton alo mportant. A central problem n the optmzaton o the overall cot developng a relablty model that relect the actor that eect the relablty. Some approache or contructng th model are dcued n [8-10]. A utable approach would be to ue o Markov Procee to model thee conguraton. In th approach, varou tate reultng rom the alure and repar or replacement o component are dented. Then the ntertate tranton rate are agned that are uncton o the alure rate and repar tme o the component. The tate probablte and other ndce are then calculated ung the mathematcal technque decrbed n [1-2]. 2. State Tranton Dagram: The tate tranton dagram or the topology hown n Fg. 2 (a) hown n Fg. 3. The varou parameter are: = Falure rate o one leg o the nverter. µ = Repar rate when only one leg aled. 1 µ = Repar rate when two leg are aled. 2 µ = Repar rate when three leg are aled. 3 µ = Repar rate when alure detected a a reult o npecton beore the conguraton alure. I In developng th tate tranton model, ollowng aumpton are made: 1. Once the conguraton aled, there are no more component alure a the conguraton wll not be powered. 2. There ome proce o npecton or detecton o alure even beore the conguraton completely down. 3. The conguraton ether up or down. It, however, poble to model degraded mode o alure. 8

9 Vdc/2 Vdc/ o A Vdc/2 + - o + Vdc/2 ' - + Vdc/2 - o'' + Vdc/ ,4 o B 2, 3,6 5 13,1 7,10 o'' 6 o 14,17 8,11 ' 15,18 9,12 b) C A B C a) Fg. 2. (a) Detaled connecton dagram o the propoed modular nverter topology; (b) Vector dagram wth wtch par number The tate equaton can be wrtten ung the concept o requency balance [1, 2]: 9P1 µ 1P2 µ I P3 µ IP4 µ 2P5 µ 3P6 0 3 P 1+ µ 1P2 0 ( µ ) 3 6 P 1 + I + 8 P 0 ( µ ) 4 = (24) = (25) = (26) P 3 + I + 7 P = 0 (27) 7 P 3+ µ 2P5 0 7 P 4+ µ 3P6 0 = (28) = (29) Where P the probablty o tate. Any ve o the above equaton wth the ollowng equaton can be olved to nd the tate probablte, P 1 + P2 + P3 + P4 + P5 + P6 = 1 (30) The varou relablty ndce can now be ound ung the ollowng relatonhp [1]: Sytem Unavalablty = P 2 + P5 + P6 9

10 Frequency o ytem alure = 3 P1 + 7P3 + 7P4 Mean Down Tme = Sytem unavalablty / Frequency o ytem alure. µ 2 µ 3 1 µ I ALL COMPONENTS UP 3 (1,4) OR (9,12) OR (14,17) DOWN 2 µ 1 µ I 6 3 (2,5) OR (3,6) OR (7,10) OR (8,11) OR (13,16) OR (15,18) DOWN 5 ANY COMBINATION OF TWO LEGS OTHER THAN IN STATE [(3,6)&(7,10)] OR [(2,5)& (13,16)] OR [(8,11)&(15,18) DOWN 6 ONE MORE LEG THAN IN STATE 4, DOWN 7 CONFIGURATION FAILURE Fg. 3. State tranton dagram o conguraton decrbed n Fg. 2 (a) STANDBY POWER SYSTEM INCLUDING UPS Sytem Decrpton The tet ytem hown n Fg. 4. Th ytem the ame a the one analyzed n [8, 9]. The power normally uppled rom utlty nput power through the UPS. A ynchronzed bypa and tatc wtch protect the crtcal load n the event o an nverter alure. I voltage lot to the crtcal load, the STS reetablhe voltage n le than one quarter o a cycle. Th condered contnuou power or mot load. When the generator are n tandby mode, ther alure reman undetected except durng perodc npecton. Thereore, whle tartng, there probablty p that a generator may al to tart. Only one generatng unt taken out or planned mantenance. I a generator al whle the other on planned mantenance, t poble to accelerate the mantenance on the econd generator by a actor oα. I power al at bu A, the battery can utan the load or upto 4 hour. 10

11 UTILITY INPUT POWER SYNCHRONIZED BYPASS ATS BUS A RECTIFIER INVERTER STS BATTERY CRITICAL LOAD BUS G G Fg. 4. Parallel uppled non-redundant unnterruptble power upply TABLE I lt the data pertanng to the ytem. Smulaton Model The lowchart hown n Fg. 1 wa mplemented. In computng the tme to the next event, the method decrbed earler wa ued, but the ollowng dependence were alo ncluded: 1. A generator cannot al whle the utlty upply up 2. A generator cannot be taken out or mantenance the utlty down or the other generator down or under mantenance 3. The UPS cannot be taken out or mantenance unle power avalable at bu A TABLE I: SYSTEM DATA Equpment/Supply (/y) r (h/) Utlty Supply, ngle crcut Generator (per hour o ue) Inverter Recter ATS STS Battery Equpment Mantenance req (/y) dur (h) Generator UPS Other data: Battery can upply load or 4.0 h Common mode alure o generator ( cm ) 0.0 Acceleraton actor or planned mantenance o (α) 2.0 generator Probablty o alure to tart a generator (p )

12 The alure o a generator to tart wa modeled a ollow. A random number z wa generated, 0 z 1. I z p, the generator wa aumed to al. Reult In th ecton the ndce obtaned rom mulaton are compared wth thoe obtaned analytcally, ung cut et analy, n [8]. Cut Set Analy The relablty ndce o the tet ytem have been analytcally evaluated, ung the cut et approach, n [5]. A ummary o the oluton tep and the reult wll be preented here, to provde a ba or valdaton o the mulaton technque. Frt, the combnaton o the utlty upply and the two generator analyzed or alure mode. Fg. 5 how the poble tate th combnaton can aume, and the tranton rate between thee tate. Baed on thee tranton rate, the probablte and requence o occurrence o the aled tate are determned. Th enable computaton o the alure rate and duraton o the utlty-generator ubytem, whch are determned to be p = / y and rp = h The next tep nvolve computaton o the rate and duraton o power alure at bu A: A = p+ ATS = / y prp+ ATSrATS ra = = h p+ ATS The remander o the cut et analy perormed a hown n TABLE II. The ytem ndce,.e., rate and duraton o power lo at the Crtcal Load Bu (CLB) are determned to be = CLB = / cut et y r r CLB = = h 12

13 µ 9 S, 1 GEN MT 1 GEN READY TO START 2 g 1 r mg 4 S, BOTH GENS READY TO START µ p p _ 1 S, BOTH GENS UP 1 r mg µ g 10 S, 1 GEN MT OTHER DN µ 1 r mg µ g S, 1 GEN DN 5 2 µ g µ _ 2 p p _ p µ g 2 g _ 2 S, 1 GEN DN OTHER UP 2 µ g α r mg _ p _ 7 S, 1 GEN MT OTHER GEN UP µ g S, BOTH GENS DN 6 µ p p p g _ 3 S, BOTH GENS DN cm DOWN g _ 8 S, 1 GEN MT OTHER GEN DN p Fg. 5. State tranton dagram or utlty upply and generator I all dtrbuton are aumed exponental, then the tandard devaton o all the up tme and down tme would equal the correpondng mean up tme and down tme. Th mple that the tandard devaton o the alure rate would alo equal the correpondng mean computed. TABLE II: FREQUENCY AND DURATION OF POWER LOSS AT CRITICAL LOAD BUS (CLB) Cut Set (/y) r (h/) r Power lo at bu A > 4 h Power lo at bu A ( , 5.092) and Falure o [Inverter or battery or STS] (1.3729, ) Mantenance on UPS (1.0, 4) and Power lo at bu A ( , 5.092) Inverter alure(1.254, 107.0) and STS alure(0.0876, 24.0) Σ Smulaton Reult The mulaton method decrbed earler wa ued to compute the ollowng tattc or the tet ytem: 1. Frequency p and duraton r p o alure o the utlty-generator ubytem (Fg. 4); the tandard devaton o p and r p. 13

14 2. Frequency A and duraton r A o power alure at bu A; the tandard devaton o A and r A. 3. Frequency CLB and duraton r CLB o power alure at the crtcal load bu; the tandard devaton o CLB and r CLB. 4. Data or the Probablty Ma Functon o the number o ytem alure per year, N. 5. Data or the Probablty Dtrbuton Functon o the ytem down tme, T. TABLE III compare the ndce obtaned rom mulaton wth thoe obtaned analytcally. TABLE III: COMPARISON OF SIMULATED AND CALCULATED INDICES Smulated Calculated Index Mean SD Mean SD p (/y) r p (h/) A (/y) r A (h/) CLB (/y) r CLB (h/) TABLE IV compare the PMF o the number o ytem alure per year. Now or exponentally dtrbuted up tme the alure are Poon dtrbuted,.e., P( N k CLB CLBe = k) = (31) k! Th equaton ued to generate the calculated data or the PMF o N, n TABLE IV. Fg. 6 compare the PDF o the ytem down tme. For exponentally dtrbuted down tme T, the PDF gven by t/ r CLB F( t) = P( T t) = 1 e (32) Th equaton ued to generate the calculated data or the PDF o T, or Fg 5. 14

15 TABLE IV: PMF OF NUMBER OF FAILURES PER YEAR P( N = k) k Smulated Calculated CONCLUDING REMARKS Th paper ha decrbed how a gven conguraton can be analyzed or producng a quanttatve relablty ndex. The technque decrbed can help to quanty relablty o alternate degn conguraton or the ame degn but wth derent qualty o component, relectng derent alure rate.. Then the relablty can be traded o wth cot to produce conguraton whch have relablty that that conumer prepared to pay or probablty down tme (hour) mulated calculated Fg. 6. Probablty dtrbuton uncton o down tme 15

16 REFERENCES 1. C. Sngh, R. Bllnton, Sytem Relablty Modellng and Evaluaton, Hutchnon Educatonal, London, England, B. S. Dhllon, C. Sngh, Engneerng Relablty: New Tool and Applcaton, John Wley, New York, E. Cengelc, P. Enjet, C. Sngh, F. Blaabjerg, J. K. Pederon, New Medum Voltage PWM Inverter Topologe or Adjutable Speed AC Motor Drve Sytem, Proceedng o 1998 Appled Power Electronc Conerence and Expoton, pp IEEE Standard , IEEE Recommended Practce or Emergency and Standby Power Sytem or Indutral and Commercal Applcaton. 5. Alexander Kuko, Emergency/Standby Power Sytem, McGraw Hll Book Company, New York, IEEE Standard , Degn o Relable Indutral and Commercal Power Sytem. 7. C. Sngh, A. D. Patton, Relablty Evaluaton o Emergency and Standby Power Sytem, IEEE Tranacton on Indutry Applcaton, vol. 21, no. 2, Mar/Apr C. Sngh, N. Gubbala, N. Gubbala, Relablty Analy o Electrc Supply Includng Standby Generator and an Unnterruptble Power Supply Sytem, IEEE Tranacton on Indutry Applcaton, vol. 30, no. 5, Sep/Oct C. Sngh, J. Mtra, Relablty Analy o Emergency and Standby Power Sytem, IEEE Indutry Applcaton Socety Magazne, vol. 3, no. 5, pp , Sept./Oct

Monte Carlo Simulation for Reliability Analysis of Emergency and Standby Power Systems

Monte Carlo Simulation for Reliability Analysis of Emergency and Standby Power Systems Monte Carlo Simulation for Reliability Analysis of Emergency and Standby Power Systems Chanan Singh, Fellow, IEEE Joydeep Mitra, Student Member, IEEE Department of Electrical Engineering Texas A & M University

More information

of Emergency and Standby Power Systems

of Emergency and Standby Power Systems Monte Carlo Simulation for Reliability Analysis of Emergency and Standby Power Systems Chanan Singh, Fellow, EEE Joydeep Mitra, Student Member, EEE Department of Electrical Engineering Texas A & M University

More information

Additional File 1 - Detailed explanation of the expression level CPD

Additional File 1 - Detailed explanation of the expression level CPD Addtonal Fle - Detaled explanaton of the expreon level CPD A mentoned n the man text, the man CPD for the uterng model cont of two ndvdual factor: P( level gen P( level gen P ( level gen 2 (.).. CPD factor

More information

STOCHASTIC BEHAVIOUR OF COMMUNICATION SUBSYSTEM OF COMMUNICATION SATELLITE

STOCHASTIC BEHAVIOUR OF COMMUNICATION SUBSYSTEM OF COMMUNICATION SATELLITE IJS 4 () July Sharma & al ehavour of Subytem of ommuncaton Satellte SOHSI HVIOU O OMMUNIION SUSYSM O OMMUNIION SLLI SK Mttal eepankar Sharma & Neelam Sharma 3 S he author n th paper have dcued the tochatc

More information

Harmonic oscillator approximation

Harmonic oscillator approximation armonc ocllator approxmaton armonc ocllator approxmaton Euaton to be olved We are fndng a mnmum of the functon under the retrcton where W P, P,..., P, Q, Q,..., Q P, P,..., P, Q, Q,..., Q lnwgner functon

More information

CHAPTER 9 LINEAR MOMENTUM, IMPULSE AND COLLISIONS

CHAPTER 9 LINEAR MOMENTUM, IMPULSE AND COLLISIONS CHAPTER 9 LINEAR MOMENTUM, IMPULSE AND COLLISIONS 103 Phy 1 9.1 Lnear Momentum The prncple o energy conervaton can be ued to olve problem that are harder to olve jut ung Newton law. It ued to decrbe moton

More information

Root Locus Techniques

Root Locus Techniques Root Locu Technque ELEC 32 Cloed-Loop Control The control nput u t ynthezed baed on the a pror knowledge of the ytem plant, the reference nput r t, and the error gnal, e t The control ytem meaure the output,

More information

Designing of Combined Continuous Lot By Lot Acceptance Sampling Plan

Designing of Combined Continuous Lot By Lot Acceptance Sampling Plan Internatonal Journal o Scentc Research Engneerng & Technology (IJSRET), ISSN 78 02 709 Desgnng o Combned Contnuous Lot By Lot Acceptance Samplng Plan S. Subhalakshm 1 Dr. S. Muthulakshm 2 1 Research Scholar,

More information

Distributed Control for the Parallel DC Linked Modular Shunt Active Power Filters under Distorted Utility Voltage Condition

Distributed Control for the Parallel DC Linked Modular Shunt Active Power Filters under Distorted Utility Voltage Condition Dtrbted Control for the Parallel DC Lnked Modlar Shnt Actve Power Flter nder Dtorted Utlty Voltage Condton Reearch Stdent: Adl Salman Spervor: Dr. Malabka Ba School of Electrcal and Electronc Engneerng

More information

Specification -- Assumptions of the Simple Classical Linear Regression Model (CLRM) 1. Introduction

Specification -- Assumptions of the Simple Classical Linear Regression Model (CLRM) 1. Introduction ECONOMICS 35* -- NOTE ECON 35* -- NOTE Specfcaton -- Aumpton of the Smple Clacal Lnear Regreon Model (CLRM). Introducton CLRM tand for the Clacal Lnear Regreon Model. The CLRM alo known a the tandard lnear

More information

Small signal analysis

Small signal analysis Small gnal analy. ntroducton Let u conder the crcut hown n Fg., where the nonlnear retor decrbed by the equaton g v havng graphcal repreentaton hown n Fg.. ( G (t G v(t v Fg. Fg. a D current ource wherea

More information

ELG3336: Op Amp-based Active Filters

ELG3336: Op Amp-based Active Filters ELG6: Op Amp-baed Actve Flter Advantage: educed ze and weght, and thereore paratc. Increaed relablty and mproved perormance. Smpler degn than or pave lter and can realze a wder range o uncton a well a

More information

OPTIMISATION. Introduction Single Variable Unconstrained Optimisation Multivariable Unconstrained Optimisation Linear Programming

OPTIMISATION. Introduction Single Variable Unconstrained Optimisation Multivariable Unconstrained Optimisation Linear Programming OPTIMIATION Introducton ngle Varable Unconstraned Optmsaton Multvarable Unconstraned Optmsaton Lnear Programmng Chapter Optmsaton /. Introducton In an engneerng analss, sometmes etremtes, ether mnmum or

More information

MODELLING OF TRANSIENT HEAT TRANSPORT IN TWO-LAYERED CRYSTALLINE SOLID FILMS USING THE INTERVAL LATTICE BOLTZMANN METHOD

MODELLING OF TRANSIENT HEAT TRANSPORT IN TWO-LAYERED CRYSTALLINE SOLID FILMS USING THE INTERVAL LATTICE BOLTZMANN METHOD Journal o Appled Mathematc and Computatonal Mechanc 7, 6(4), 57-65 www.amcm.pcz.pl p-issn 99-9965 DOI:.75/jamcm.7.4.6 e-issn 353-588 MODELLING OF TRANSIENT HEAT TRANSPORT IN TWO-LAYERED CRYSTALLINE SOLID

More information

Introduction to Interfacial Segregation. Xiaozhe Zhang 10/02/2015

Introduction to Interfacial Segregation. Xiaozhe Zhang 10/02/2015 Introducton to Interfacal Segregaton Xaozhe Zhang 10/02/2015 Interfacal egregaton Segregaton n materal refer to the enrchment of a materal conttuent at a free urface or an nternal nterface of a materal.

More information

MULTIPLE REGRESSION ANALYSIS For the Case of Two Regressors

MULTIPLE REGRESSION ANALYSIS For the Case of Two Regressors MULTIPLE REGRESSION ANALYSIS For the Cae of Two Regreor In the followng note, leat-quare etmaton developed for multple regreon problem wth two eplanator varable, here called regreor (uch a n the Fat Food

More information

On the SO 2 Problem in Thermal Power Plants. 2.Two-steps chemical absorption modeling

On the SO 2 Problem in Thermal Power Plants. 2.Two-steps chemical absorption modeling Internatonal Journal of Engneerng Reearch ISSN:39-689)(onlne),347-53(prnt) Volume No4, Iue No, pp : 557-56 Oct 5 On the SO Problem n Thermal Power Plant Two-tep chemcal aborpton modelng hr Boyadjev, P

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler -T Sytem: Ung Bode Plot EEE 30 Sgnal & Sytem Pro. Mark Fowler Note Set #37 /3 Bode Plot Idea an Help Vualze What rcut Do Lowpa Flter Break Pont = / H ( ) j /3 Hghpa Flter c = / L Bandpa Flter n nn ( a)

More information

Chapter 3 Differentiation and Integration

Chapter 3 Differentiation and Integration MEE07 Computer Modelng Technques n Engneerng Chapter Derentaton and Integraton Reerence: An Introducton to Numercal Computatons, nd edton, S. yakowtz and F. zdarovsky, Mawell/Macmllan, 990. Derentaton

More information

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS Avalable onlne at http://sck.org J. Math. Comput. Sc. 3 (3), No., 6-3 ISSN: 97-537 COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

More information

728. Mechanical and electrical elements in reduction of vibrations

728. Mechanical and electrical elements in reduction of vibrations 78. Mechancal and electrcal element n reducton of vbraton Katarzyna BIAŁAS The Slean Unverty of Technology, Faculty of Mechancal Engneerng Inttute of Engneerng Procee Automaton and Integrated Manufacturng

More information

Variable Structure Control ~ Basics

Variable Structure Control ~ Basics Varable Structure Control ~ Bac Harry G. Kwatny Department of Mechancal Engneerng & Mechanc Drexel Unverty Outlne A prelmnary example VS ytem, ldng mode, reachng Bac of dcontnuou ytem Example: underea

More information

Chapter 11. Supplemental Text Material. The method of steepest ascent can be derived as follows. Suppose that we have fit a firstorder

Chapter 11. Supplemental Text Material. The method of steepest ascent can be derived as follows. Suppose that we have fit a firstorder S-. The Method of Steepet cent Chapter. Supplemental Text Materal The method of teepet acent can be derved a follow. Suppoe that we have ft a frtorder model y = β + β x and we wh to ue th model to determne

More information

Department of Electrical and Computer Engineering FEEDBACK AMPLIFIERS

Department of Electrical and Computer Engineering FEEDBACK AMPLIFIERS Department o Electrcal and Computer Engneerng UNIT I EII FEEDBCK MPLIFIES porton the output sgnal s ed back to the nput o the ampler s called Feedback mpler. Feedback Concept: block dagram o an ampler

More information

On multivariate folded normal distribution

On multivariate folded normal distribution Sankhyā : The Indan Journal o Stattc 03, Volume 75-B, Part, pp. -5 c 03, Indan Stattcal Inttute On multvarate olded normal dtrbuton Ah Kumar Chakraborty and Moutuh Chatterjee Indan Stattcal Inttute, Kolkata,

More information

Method Of Fundamental Solutions For Modeling Electromagnetic Wave Scattering Problems

Method Of Fundamental Solutions For Modeling Electromagnetic Wave Scattering Problems Internatonal Workhop on MehFree Method 003 1 Method Of Fundamental Soluton For Modelng lectromagnetc Wave Scatterng Problem Der-Lang Young (1) and Jhh-We Ruan (1) Abtract: In th paper we attempt to contruct

More information

Digital Simulation of Power Systems and Power Electronics using the MATLAB Power System Blockset 筑龙网

Digital Simulation of Power Systems and Power Electronics using the MATLAB Power System Blockset 筑龙网 Dgtal Smulaton of Power Sytem and Power Electronc ung the MATAB Power Sytem Blocket Power Sytem Blocket Htory Deeloped by IREQ (HydroQuébec) n cooperaton wth Teqm, Unerté aal (Québec), and École de Technologe

More information

Absorbing Markov Chain Models to Determine Optimum Process Target Levels in Production Systems with Rework and Scrapping

Absorbing Markov Chain Models to Determine Optimum Process Target Levels in Production Systems with Rework and Scrapping Archve o SID Journal o Industral Engneerng 6(00) -6 Absorbng Markov Chan Models to Determne Optmum Process Target evels n Producton Systems wth Rework and Scrappng Mohammad Saber Fallah Nezhad a, Seyed

More information

Confidence intervals for the difference and the ratio of Lognormal means with bounded parameters

Confidence intervals for the difference and the ratio of Lognormal means with bounded parameters Songklanakarn J. Sc. Technol. 37 () 3-40 Mar.-Apr. 05 http://www.jt.pu.ac.th Orgnal Artcle Confdence nterval for the dfference and the rato of Lognormal mean wth bounded parameter Sa-aat Nwtpong* Department

More information

KEY POINTS FOR NUMERICAL SIMULATION OF INCLINATION OF BUILDINGS ON LIQUEFIABLE SOIL LAYERS

KEY POINTS FOR NUMERICAL SIMULATION OF INCLINATION OF BUILDINGS ON LIQUEFIABLE SOIL LAYERS KY POINTS FOR NUMRICAL SIMULATION OF INCLINATION OF BUILDINGS ON LIQUFIABL SOIL LAYRS Jn Xu 1, Xaomng Yuan, Jany Zhang 3,Fanchao Meng 1 1 Student, Dept. of Geotechncal ngneerng, Inttute of ngneerng Mechanc,

More information

Prof. Paolo Colantonio a.a

Prof. Paolo Colantonio a.a Pro. Paolo olantono a.a. 3 4 Let s consder a two ports network o Two ports Network o L For passve network (.e. wthout nternal sources or actve devces), a general representaton can be made by a sutable

More information

Estimation of Finite Population Total under PPS Sampling in Presence of Extra Auxiliary Information

Estimation of Finite Population Total under PPS Sampling in Presence of Extra Auxiliary Information Internatonal Journal of Stattc and Analy. ISSN 2248-9959 Volume 6, Number 1 (2016), pp. 9-16 Reearch Inda Publcaton http://www.rpublcaton.com Etmaton of Fnte Populaton Total under PPS Samplng n Preence

More information

Scattering of two identical particles in the center-of. of-mass frame. (b)

Scattering of two identical particles in the center-of. of-mass frame. (b) Lecture # November 5 Scatterng of two dentcal partcle Relatvtc Quantum Mechanc: The Klen-Gordon equaton Interpretaton of the Klen-Gordon equaton The Drac equaton Drac repreentaton for the matrce α and

More information

Alpha Risk of Taguchi Method with L 18 Array for NTB Type QCH by Simulation

Alpha Risk of Taguchi Method with L 18 Array for NTB Type QCH by Simulation Proceedng of the World Congre on Engneerng 00 Vol II WCE 00, July -, 00, London, U.K. Alpha Rk of Taguch Method wth L Array for NTB Type QCH by Smulaton A. Al-Refae and M.H. L Abtract Taguch method a wdely

More information

Two Approaches to Proving. Goldbach s Conjecture

Two Approaches to Proving. Goldbach s Conjecture Two Approache to Provng Goldbach Conecture By Bernard Farley Adved By Charle Parry May 3 rd 5 A Bref Introducton to Goldbach Conecture In 74 Goldbach made h mot famou contrbuton n mathematc wth the conecture

More information

Control Strategy of Cascade STATCOM Based on Internal Model Theory

Control Strategy of Cascade STATCOM Based on Internal Model Theory TEKOMNIKA Indonean Journal of Electrcal Engneerng Vol.12, No.3, March 2014, pp. 1687 ~ 1694 DOI: http://dx.do.org/10.11591/telkomnka.v123.4452 1687 Control Strategy of Cacade STATCOM Baed on Internal Model

More information

No! Yes! Only if reactions occur! Yes! Ideal Gas, change in temperature or pressure. Survey Results. Class 15. Is the following possible?

No! Yes! Only if reactions occur! Yes! Ideal Gas, change in temperature or pressure. Survey Results. Class 15. Is the following possible? Survey Reult Chapter 5-6 (where we are gong) % of Student 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% Hour Spent on ChE 273 1-2 3-4 5-6 7-8 9-10 11+ Hour/Week 2008 2009 2010 2011 2012 2013 2014 2015 2017 F17

More information

Team. Outline. Statistics and Art: Sampling, Response Error, Mixed Models, Missing Data, and Inference

Team. Outline. Statistics and Art: Sampling, Response Error, Mixed Models, Missing Data, and Inference Team Stattc and Art: Samplng, Repone Error, Mxed Model, Mng Data, and nference Ed Stanek Unverty of Maachuett- Amhert, USA 9/5/8 9/5/8 Outlne. Example: Doe-repone Model n Toxcology. ow to Predct Realzed

More information

Chapter 6 The Effect of the GPS Systematic Errors on Deformation Parameters

Chapter 6 The Effect of the GPS Systematic Errors on Deformation Parameters Chapter 6 The Effect of the GPS Sytematc Error on Deformaton Parameter 6.. General Beutler et al., (988) dd the frt comprehenve tudy on the GPS ytematc error. Baed on a geometrc approach and aumng a unform

More information

Electrical Circuits II (ECE233b)

Electrical Circuits II (ECE233b) Electrcal Crcut II (ECE33b) Applcaton of Laplace Tranform to Crcut Analy Anet Dounav The Unverty of Wetern Ontaro Faculty of Engneerng Scence Crcut Element Retance Tme Doman (t) v(t) R v(t) = R(t) Frequency

More information

DEADLOCK INDEX ANALYSIS OF MULTI-LEVEL QUEUE SCHEDULING IN OPERATING SYSTEM USING DATA MODEL APPROACH

DEADLOCK INDEX ANALYSIS OF MULTI-LEVEL QUEUE SCHEDULING IN OPERATING SYSTEM USING DATA MODEL APPROACH GESJ: Computer Scence and Telecommuncaton 2 No.(29 ISSN 2-232 DEADLOCK INDEX ANALYSIS OF MULTI-LEVEL QUEUE SCHEDULING IN OPERATING SYSTEM USING DATA MODEL APPROACH D. Shukla, Shweta Ojha 2 Deptt. of Mathematc

More information

2.3 Least-Square regressions

2.3 Least-Square regressions .3 Leat-Square regreon Eample.10 How do chldren grow? The pattern of growth vare from chld to chld, o we can bet undertandng the general pattern b followng the average heght of a number of chldren. Here

More information

Verification of Selected Precision Parameters of the Trimble S8 DR Plus Robotic Total Station

Verification of Selected Precision Parameters of the Trimble S8 DR Plus Robotic Total Station 81 Verfcaton of Selected Precon Parameter of the Trmble S8 DR Plu Robotc Total Staton Sokol, Š., Bajtala, M. and Ježko, J. Slovak Unverty of Technology, Faculty of Cvl Engneerng, Radlnkého 11, 81368 Bratlava,

More information

Basic Statistical Analysis and Yield Calculations

Basic Statistical Analysis and Yield Calculations October 17, 007 Basc Statstcal Analyss and Yeld Calculatons Dr. José Ernesto Rayas Sánchez 1 Outlne Sources of desgn-performance uncertanty Desgn and development processes Desgn for manufacturablty A general

More information

Comparative Study on Electromagnetic and Electromechanical Transient Model for Grid-connected Photovoltaic Power System

Comparative Study on Electromagnetic and Electromechanical Transient Model for Grid-connected Photovoltaic Power System Energy and Power Engneerng, 13, 5, 47-5 do:1.436/epe.13.54b48 Publhed Onlne July 13 (http://www.crp.org/journal/epe) Comparatve Study on and Tranent Model for Grd-connected Photovoltac Power Sytem Man

More information

Not at Steady State! Yes! Only if reactions occur! Yes! Ideal Gas, change in temperature or pressure. Yes! Class 15. Is the following possible?

Not at Steady State! Yes! Only if reactions occur! Yes! Ideal Gas, change in temperature or pressure. Yes! Class 15. Is the following possible? Chapter 5-6 (where we are gong) Ideal gae and lqud (today) Dente Partal preure Non-deal gae (next tme) Eqn. of tate Reduced preure and temperature Compreblty chart (z) Vapor-lqud ytem (Ch. 6) Vapor preure

More information

OPTIMAL COMPUTING BUDGET ALLOCATION FOR MULTI-OBJECTIVE SIMULATION MODELS. David Goldsman

OPTIMAL COMPUTING BUDGET ALLOCATION FOR MULTI-OBJECTIVE SIMULATION MODELS. David Goldsman Proceedng of the 004 Wnter Smulaton Conference R.G. Ingall, M. D. Roett, J. S. Smth, and B. A. Peter, ed. OPTIMAL COMPUTING BUDGET ALLOCATION FOR MULTI-OBJECTIVE SIMULATION MODELS Loo Hay Lee Ek Peng Chew

More information

Solution Methods for Time-indexed MIP Models for Chemical Production Scheduling

Solution Methods for Time-indexed MIP Models for Chemical Production Scheduling Ian Davd Lockhart Bogle and Mchael Farweather (Edtor), Proceedng of the 22nd European Sympoum on Computer Aded Proce Engneerng, 17-2 June 212, London. 212 Elever B.V. All rght reerved. Soluton Method for

More information

Lecture 2 Solution of Nonlinear Equations ( Root Finding Problems )

Lecture 2 Solution of Nonlinear Equations ( Root Finding Problems ) Lecture Soluton o Nonlnear Equatons Root Fndng Problems Dentons Classcaton o Methods Analytcal Solutons Graphcal Methods Numercal Methods Bracketng Methods Open Methods Convergence Notatons Root Fndng

More information

EE 330 Lecture 24. Small Signal Analysis Small Signal Analysis of BJT Amplifier

EE 330 Lecture 24. Small Signal Analysis Small Signal Analysis of BJT Amplifier EE 0 Lecture 4 Small Sgnal Analss Small Sgnal Analss o BJT Ampler Eam Frda March 9 Eam Frda Aprl Revew Sesson or Eam : 6:00 p.m. on Thursda March 8 n Room Sweene 6 Revew rom Last Lecture Comparson o Gans

More information

Modeling of Wave Behavior of Substrate Noise Coupling for Mixed-Signal IC Design

Modeling of Wave Behavior of Substrate Noise Coupling for Mixed-Signal IC Design Modelng of Wave Behavor of Subtrate Noe Couplng for Mxed-Sgnal IC Degn Georgo Veron, Y-Chang Lu, and Robert W. Dutton Center for Integrated Sytem, Stanford Unverty, Stanford, CA 9435 yorgo@gloworm.tanford.edu

More information

ENTROPY BOUNDS USING ARITHMETIC- GEOMETRIC-HARMONIC MEAN INEQUALITY. Guru Nanak Dev University Amritsar, , INDIA

ENTROPY BOUNDS USING ARITHMETIC- GEOMETRIC-HARMONIC MEAN INEQUALITY. Guru Nanak Dev University Amritsar, , INDIA Internatonal Journal of Pure and Appled Mathematc Volume 89 No. 5 2013, 719-730 ISSN: 1311-8080 prnted veron; ISSN: 1314-3395 on-lne veron url: http://.jpam.eu do: http://dx.do.org/10.12732/jpam.v895.8

More information

Computational Biology Lecture 8: Substitution matrices Saad Mneimneh

Computational Biology Lecture 8: Substitution matrices Saad Mneimneh Computatonal Bology Lecture 8: Substtuton matrces Saad Mnemneh As we have ntroduced last tme, smple scorng schemes lke + or a match, - or a msmatch and -2 or a gap are not justable bologcally, especally

More information

A LINEAR PROGRAM TO COMPARE MULTIPLE GROSS CREDIT LOSS FORECASTS. Dr. Derald E. Wentzien, Wesley College, (302) ,

A LINEAR PROGRAM TO COMPARE MULTIPLE GROSS CREDIT LOSS FORECASTS. Dr. Derald E. Wentzien, Wesley College, (302) , A LINEAR PROGRAM TO COMPARE MULTIPLE GROSS CREDIT LOSS FORECASTS Dr. Derald E. Wentzen, Wesley College, (302) 736-2574, wentzde@wesley.edu ABSTRACT A lnear programmng model s developed and used to compare

More information

Start Point and Trajectory Analysis for the Minimal Time System Design Algorithm

Start Point and Trajectory Analysis for the Minimal Time System Design Algorithm Start Pont and Trajectory Analy for the Mnmal Tme Sytem Degn Algorthm ALEXANDER ZEMLIAK, PEDRO MIRANDA Department of Phyc and Mathematc Puebla Autonomou Unverty Av San Claudo /n, Puebla, 757 MEXICO Abtract:

More information

This appendix presents the derivations and proofs omitted from the main text.

This appendix presents the derivations and proofs omitted from the main text. Onlne Appendx A Appendx: Omtted Dervaton and Proof Th appendx preent the dervaton and proof omtted from the man text A Omtted dervaton n Secton Mot of the analy provded n the man text Here, we formally

More information

3 Implementation and validation of analysis methods

3 Implementation and validation of analysis methods 3 Implementaton and valdaton of anal method 3. Preface When mplementng new method bacall three cae can be dfferentated: - Implementaton of offcal method (nternatonall approved, valdated method, e.g. method

More information

Resonant FCS Predictive Control of Power Converter in Stationary Reference Frame

Resonant FCS Predictive Control of Power Converter in Stationary Reference Frame Preprnt of the 9th World Congre The Internatonal Federaton of Automatc Control Cape Town, South Afrca. Augut -9, Reonant FCS Predctve Control of Power Converter n Statonary Reference Frame Lupng Wang K

More information

CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE

CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE Analytcal soluton s usually not possble when exctaton vares arbtrarly wth tme or f the system s nonlnear. Such problems can be solved by numercal tmesteppng

More information

m = 4 n = 9 W 1 N 1 x 1 R D 4 s x i

m = 4 n = 9 W 1 N 1 x 1 R D 4 s x i GREEDY WIRE-SIZING IS LINEAR TIME Chr C. N. Chu D. F. Wong cnchu@c.utexa.edu wong@c.utexa.edu Department of Computer Scence, Unverty of Texa at Autn, Autn, T 787. ABSTRACT In nterconnect optmzaton by wre-zng,

More information

A Novel Approach for Testing Stability of 1-D Recursive Digital Filters Based on Lagrange Multipliers

A Novel Approach for Testing Stability of 1-D Recursive Digital Filters Based on Lagrange Multipliers Amercan Journal of Appled Scence 5 (5: 49-495, 8 ISSN 546-939 8 Scence Publcaton A Novel Approach for Tetng Stablty of -D Recurve Dgtal Flter Baed on Lagrange ultpler KRSanth, NGangatharan and Ponnavakko

More information

Extended Prigogine Theorem: Method for Universal Characterization of Complex System Evolution

Extended Prigogine Theorem: Method for Universal Characterization of Complex System Evolution Extended Prgogne Theorem: Method for Unveral Characterzaton of Complex Sytem Evoluton Sergey amenhchkov* Mocow State Unverty of M.V. Lomonoov, Phycal department, Rua, Mocow, Lennke Gory, 1/, 119991 Publhed

More information

Computer Control Systems

Computer Control Systems Computer Control ytem In th chapter we preent the element and the bac concept of computercontrolled ytem. The dcretaton and choce of amplng frequency wll be frt examned, followed by a tudy of dcrete-tme

More information

: Numerical Analysis Topic 2: Solution of Nonlinear Equations Lectures 5-11:

: Numerical Analysis Topic 2: Solution of Nonlinear Equations Lectures 5-11: 764: Numercal Analyss Topc : Soluton o Nonlnear Equatons Lectures 5-: UIN Malang Read Chapters 5 and 6 o the tetbook 764_Topc Lecture 5 Soluton o Nonlnear Equatons Root Fndng Problems Dentons Classcaton

More information

Physics 111. CQ1: springs. con t. Aristocrat at a fixed angle. Wednesday, 8-9 pm in NSC 118/119 Sunday, 6:30-8 pm in CCLIR 468.

Physics 111. CQ1: springs. con t. Aristocrat at a fixed angle. Wednesday, 8-9 pm in NSC 118/119 Sunday, 6:30-8 pm in CCLIR 468. c Announcement day, ober 8, 004 Ch 8: Ch 10: Work done by orce at an angle Power Rotatonal Knematc angular dplacement angular velocty angular acceleraton Wedneday, 8-9 pm n NSC 118/119 Sunday, 6:30-8 pm

More information

PROBABILITY-CONSISTENT SCENARIO EARTHQUAKE AND ITS APPLICATION IN ESTIMATION OF GROUND MOTIONS

PROBABILITY-CONSISTENT SCENARIO EARTHQUAKE AND ITS APPLICATION IN ESTIMATION OF GROUND MOTIONS PROBABILITY-COSISTET SCEARIO EARTHQUAKE AD ITS APPLICATIO I ESTIATIO OF GROUD OTIOS Q-feng LUO SUARY Th paper preent a new defnton of probablty-content cenaro earthquae PCSE and an evaluaton method of

More information

FEEDBACK AMPLIFIERS. v i or v s v 0

FEEDBACK AMPLIFIERS. v i or v s v 0 FEEDBCK MPLIFIERS Feedback n mplers FEEDBCK IS THE PROCESS OF FEEDING FRCTION OF OUTPUT ENERGY (VOLTGE OR CURRENT) BCK TO THE INPUT CIRCUIT. THE CIRCUIT EMPLOYED FOR THIS PURPOSE IS CLLED FEEDBCK NETWORK.

More information

Probability, Statistics, and Reliability for Engineers and Scientists SIMULATION

Probability, Statistics, and Reliability for Engineers and Scientists SIMULATION CHATER robablty, Statstcs, and Relablty or Engneers and Scentsts Second Edton SIULATIO A. J. Clark School o Engneerng Department o Cvl and Envronmental Engneerng 7b robablty and Statstcs or Cvl Engneers

More information

Chapter 6. Operational Amplifier. inputs can be defined as the average of the sum of the two signals.

Chapter 6. Operational Amplifier.  inputs can be defined as the average of the sum of the two signals. 6 Operatonal mpler Chapter 6 Operatonal mpler CC Symbol: nput nput Output EE () Non-nvertng termnal, () nvertng termnal nput mpedance : Few mega (ery hgh), Output mpedance : Less than (ery low) Derental

More information

A New Inverse Reliability Analysis Method Using MPP-Based Dimension Reduction Method (DRM)

A New Inverse Reliability Analysis Method Using MPP-Based Dimension Reduction Method (DRM) roceedng of the ASME 007 Internatonal Degn Engneerng Techncal Conference & Computer and Informaton n Engneerng Conference IDETC/CIE 007 September 4-7, 007, La Vega, eada, USA DETC007-35098 A ew Inere Relablty

More information

A NOVEL FAMILY OF WEIGHTED AVERAGE VOTERS FOR FAULT-TOLERANT COMPUTER CONTROL SYSTEMS

A NOVEL FAMILY OF WEIGHTED AVERAGE VOTERS FOR FAULT-TOLERANT COMPUTER CONTROL SYSTEMS A OVEL FAMILY OF WEIGHTED AVERAGE VOTERS FOR FAULT-TOLERAT COMPUTER COTROL SYSTEMS G. Latf-Shabgah *, A. J. Hrt *, and S. Bennett + * Department of Telematc, Open Unverty Walton Hall, Mlton Keyne, MK7

More information

Comparison of the Population Variance Estimators. of 2-Parameter Exponential Distribution Based on. Multiple Criteria Decision Making Method

Comparison of the Population Variance Estimators. of 2-Parameter Exponential Distribution Based on. Multiple Criteria Decision Making Method Appled Mathematcal Scences, Vol. 7, 0, no. 47, 07-0 HIARI Ltd, www.m-hkar.com Comparson of the Populaton Varance Estmators of -Parameter Exponental Dstrbuton Based on Multple Crtera Decson Makng Method

More information

Chapter 13: Multiple Regression

Chapter 13: Multiple Regression Chapter 13: Multple Regresson 13.1 Developng the multple-regresson Model The general model can be descrbed as: It smplfes for two ndependent varables: The sample ft parameter b 0, b 1, and b are used to

More information

8 Waves in Uniform Magnetized Media

8 Waves in Uniform Magnetized Media 8 Wave n Unform Magnetzed Meda 81 Suceptblte The frt order current can be wrtten j = j = q d 3 p v f 1 ( r, p, t) = ɛ 0 χ E For Maxwellan dtrbuton Y n (λ) = f 0 (v, v ) = 1 πvth exp (v V ) v th 1 πv th

More information

Chapter 5 rd Law of Thermodynamics

Chapter 5 rd Law of Thermodynamics Entropy and the nd and 3 rd Chapter 5 rd Law o hermodynamcs homas Engel, hlp Red Objectves Introduce entropy. Derve the condtons or spontanety. Show how S vares wth the macroscopc varables,, and. Chapter

More information

NUMERICAL DIFFERENTIATION

NUMERICAL DIFFERENTIATION NUMERICAL DIFFERENTIATION 1 Introducton Dfferentaton s a method to compute the rate at whch a dependent output y changes wth respect to the change n the ndependent nput x. Ths rate of change s called the

More information

University of Washington Department of Chemistry Chemistry 452/456 Summer Quarter 2014

University of Washington Department of Chemistry Chemistry 452/456 Summer Quarter 2014 Lecture 16 8/4/14 Unversty o Washngton Department o Chemstry Chemstry 452/456 Summer Quarter 214. Real Vapors and Fugacty Henry s Law accounts or the propertes o extremely dlute soluton. s shown n Fgure

More information

Pythagorean triples. Leen Noordzij.

Pythagorean triples. Leen Noordzij. Pythagorean trple. Leen Noordz Dr.l.noordz@leennoordz.nl www.leennoordz.me Content A Roadmap for generatng Pythagorean Trple.... Pythagorean Trple.... 3 Dcuon Concluon.... 5 A Roadmap for generatng Pythagorean

More information

Foresighted Resource Reciprocation Strategies in P2P Networks

Foresighted Resource Reciprocation Strategies in P2P Networks Foreghted Reource Recprocaton Stratege n PP Networ Hyunggon Par and Mhaela van der Schaar Electrcal Engneerng Department Unverty of Calforna Lo Angele (UCLA) Emal: {hgpar mhaela@ee.ucla.edu Abtract We

More information

ECEN 5005 Crystals, Nanocrystals and Device Applications Class 19 Group Theory For Crystals

ECEN 5005 Crystals, Nanocrystals and Device Applications Class 19 Group Theory For Crystals ECEN 5005 Crystals, Nanocrystals and Devce Applcatons Class 9 Group Theory For Crystals Dee Dagram Radatve Transton Probablty Wgner-Ecart Theorem Selecton Rule Dee Dagram Expermentally determned energy

More information

CHAPTER 8 OBSERVER BASED REDUCED ORDER CONTROLLER DESIGN FOR LARGE SCALE LINEAR DISCRETE-TIME CONTROL SYSTEMS

CHAPTER 8 OBSERVER BASED REDUCED ORDER CONTROLLER DESIGN FOR LARGE SCALE LINEAR DISCRETE-TIME CONTROL SYSTEMS CHAPTER 8 OBSERVER BASED REDUCED ORDER CONTROLLER DESIGN FOR LARGE SCALE LINEAR DISCRETE-TIME CONTROL SYSTEMS 8.1 INTRODUCTION 8.2 REDUCED ORDER MODEL DESIGN FOR LINEAR DISCRETE-TIME CONTROL SYSTEMS 8.3

More information

Discrete Simultaneous Perturbation Stochastic Approximation on Loss Function with Noisy Measurements

Discrete Simultaneous Perturbation Stochastic Approximation on Loss Function with Noisy Measurements 0 Amercan Control Conference on O'Farrell Street San Francco CA USA June 9 - July 0 0 Dcrete Smultaneou Perturbaton Stochatc Approxmaton on Lo Functon wth Noy Meaurement Q Wang and Jame C Spall Abtract

More information

MODELLING OF STOCHASTIC PARAMETERS FOR CONTROL OF CITY ELECTRIC TRANSPORT SYSTEMS USING EVOLUTIONARY ALGORITHM

MODELLING OF STOCHASTIC PARAMETERS FOR CONTROL OF CITY ELECTRIC TRANSPORT SYSTEMS USING EVOLUTIONARY ALGORITHM MODELLING OF STOCHASTIC PARAMETERS FOR CONTROL OF CITY ELECTRIC TRANSPORT SYSTEMS USING EVOLUTIONARY ALGORITHM Mkhal Gorobetz, Anatoly Levchenkov Inttute of Indutral Electronc and Electrotechnc, Rga Techncal

More information

AP Statistics Ch 3 Examining Relationships

AP Statistics Ch 3 Examining Relationships Introducton To tud relatonhp between varable, we mut meaure the varable on the ame group of ndvdual. If we thnk a varable ma eplan or even caue change n another varable, then the eplanator varable and

More information

Stability Analysis of Inverter for Renewable Energy

Stability Analysis of Inverter for Renewable Energy vance n Power an Energy Sytem Stablty naly of nverter for Renewable Energy TOORU MOR, JUNCH R Electrcal Engneerng an Electronc ogakun Unverty 1-24-2 Nh-hnjuku, Shnjuku-ku, Tokyo 163-8677 JPN cm1134@n.kogakun.ac.jp

More information

Electric and magnetic field sensor and integrator equations

Electric and magnetic field sensor and integrator equations Techncal Note - TN12 Electrc and magnetc feld enor and ntegrator uaton Bertrand Da, montena technology, 1728 oen, Swtzerland Table of content 1. Equaton of the derate electrc feld enor... 1 2. Integraton

More information

Analysis of the induction machines sensitivity to voltage sags. F. Córcoles and J. Pedra Ll. Guasch

Analysis of the induction machines sensitivity to voltage sags. F. Córcoles and J. Pedra Ll. Guasch Analyss of the nducton machnes senstvty to voltage sags F Córcoles and J Pedra Ll Guasch Dep d Eng Elèctrca ETSEIB UPC Dep d Eng Elèctrca Mec ESTE URV Dagonal, 7 88 Barcelona Span Ctra Salou, s/n Tarragona

More information

OPTIMAL CONTROL FOR THREE-PHASE POWER CONVERTERS SVPWM BASED ON LINEAR QUADRATIC REGULATOR

OPTIMAL CONTROL FOR THREE-PHASE POWER CONVERTERS SVPWM BASED ON LINEAR QUADRATIC REGULATOR INERNAIONA JOURNA o ACADEMIC RESEARCH Vol. 4. No. 3. May, 0 OPIMA CONRO FOR HREE-PHASE POWER CONVERERS SVPWM BASED ON INEAR QUADRAIC REGUAOR Har Sutkno, e Jaa, Mochamad Ahar 3, Maurdh Hery Purnomo 3 Sekolah

More information

S-Domain Analysis. s-domain Circuit Analysis. EE695K VLSI Interconnect. Time domain (t domain) Complex frequency domain (s domain) Laplace Transform L

S-Domain Analysis. s-domain Circuit Analysis. EE695K VLSI Interconnect. Time domain (t domain) Complex frequency domain (s domain) Laplace Transform L EE695K S nterconnect S-Doman naly -Doman rcut naly Tme doman t doman near rcut aplace Tranform omplex frequency doman doman Tranformed rcut Dfferental equaton lacal technque epone waveform aplace Tranform

More information

Simulated Power of the Discrete Cramér-von Mises Goodness-of-Fit Tests

Simulated Power of the Discrete Cramér-von Mises Goodness-of-Fit Tests Smulated of the Cramér-von Mses Goodness-of-Ft Tests Steele, M., Chaselng, J. and 3 Hurst, C. School of Mathematcal and Physcal Scences, James Cook Unversty, Australan School of Envronmental Studes, Grffth

More information

A NUMERICAL MODELING OF MAGNETIC FIELD PERTURBATED BY THE PRESENCE OF SCHIP S HULL

A NUMERICAL MODELING OF MAGNETIC FIELD PERTURBATED BY THE PRESENCE OF SCHIP S HULL A NUMERCAL MODELNG OF MAGNETC FELD PERTURBATED BY THE PRESENCE OF SCHP S HULL M. Dennah* Z. Abd** * Laboratory Electromagnetc Sytem EMP BP b Ben-Aknoun 606 Alger Algera ** Electronc nttute USTHB Alger

More information

Two-Layered Model of Blood Flow through Composite Stenosed Artery

Two-Layered Model of Blood Flow through Composite Stenosed Artery Avalable at http://pvamu.edu/aam Appl. Appl. Math. ISSN: 93-9466 Vol. 4, Iue (December 9), pp. 343 354 (Prevouly, Vol. 4, No.) Applcaton Appled Mathematc: An Internatonal Journal (AAM) Two-ayered Model

More information

Image Registration for a Series of Chest Radiograph Images

Image Registration for a Series of Chest Radiograph Images Proceedng of the 5th WE Internatonal Conference on gnal Proceng, Itanbul, Turkey, May 7-9, 006 (pp179-184) Image Regtraton for a ere of Chet Radograph Image Omar Mohd. Rjal*, Norlza Mohd. Noor, hee Lee

More information

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

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

More information

Approximating the Sum Operation for Marginal-MAP Inference

Approximating the Sum Operation for Marginal-MAP Inference Approxmatng the Sum Operaton or Margnal-MAP Inerence Qang Cheng, Feng Chen, Janwu Dong, Wenl Xu Alexander Ihler Tnghua Natonal Laboratory or Inormaton Scence and Technology Inormaton and Computer Scence

More information

Chapter 9: Controller design. Controller design. Controller design

Chapter 9: Controller design. Controller design. Controller design Chapter 9. Controller Deign 9.. Introduction 9.2. Eect o negative eedback on the network traner unction 9.2.. Feedback reduce the traner unction rom diturbance to the output 9.2.2. Feedback caue the traner

More information

CISE301: Numerical Methods Topic 2: Solution of Nonlinear Equations

CISE301: Numerical Methods Topic 2: Solution of Nonlinear Equations CISE3: Numercal Methods Topc : Soluton o Nonlnear Equatons Dr. Amar Khoukh Term Read Chapters 5 and 6 o the tetbook CISE3_Topc c Khoukh_ Lecture 5 Soluton o Nonlnear Equatons Root ndng Problems Dentons

More information

bounds compared to SB and SBB bounds as the former two have an index parameter, while the latter two

bounds compared to SB and SBB bounds as the former two have an index parameter, while the latter two 1 Queung Procee n GPS and PGPS wth LRD Traffc Input Xang Yu, Ian L-Jn Thng, Yumng Jang and Chunmng Qao Department of Computer Scence and Engneerng State Unverty of New York at Buffalo Department of Electrcal

More information

The gravitational field energy density for symmetrical and asymmetrical systems

The gravitational field energy density for symmetrical and asymmetrical systems The ravtatonal eld enery denty or yetrcal and ayetrcal yte Roald Sonovy Techncal Unverty 90 St. Peterbur Rua E-al:roov@yandex Abtract. The relatvtc theory o ravtaton ha the conderable dculte by decrpton

More information

Lesson 16: Basic Control Modes

Lesson 16: Basic Control Modes 0/8/05 Lesson 6: Basc Control Modes ET 438a Automatc Control Systems Technology lesson6et438a.tx Learnng Objectves Ater ths resentaton you wll be able to: Descrbe the common control modes used n analog

More information