Multi-area Load Frequency Control using IP Controller Tuned by Particle Swarm Optimization

Size: px
Start display at page:

Download "Multi-area Load Frequency Control using IP Controller Tuned by Particle Swarm Optimization"

Transcription

1 esearch Journal of Applied Sciences, Engineering and echnology (): 96-, ISSN: -767 axwell Scienific Organizaion, Submied: July, Acceped: Sepember 8, Published: ecember 6, uli-area Load Frequency Conrol using IP Conroller uned by Paricle Swarm Opimizaion Sayed ojaba Shirvani Boroujeni, Babak Keyvani Boroujeni, osafa Abdollahi and Hamideh elafkar eparmen of Elecrical Engineering, Boroujen Branch, Islamic Azad Universiy, Boroujen, Iran Absrac: In his sudy an opimal load frequency conroller for muli area elecric power sysems is presened. In muli area elecric power sysems if a large load is suddenly conneced (or disconneced) o he sysem, or if a generaing uni is suddenly disconneced by he proecion equipmen, here will be a long-erm disorion in he power balance beween ha delivered by he urbines and ha consumed by he loads. his imbalance is iniially covered from he kineic energy of roaing roors of urbines, generaors and moors and, as a resul, he frequency in he sysem will change. herefore he Load Frequency Conrol (LFC) problem is one of he mos imporan subjecs in he elecric power sysem operaion and conrol. In pracical sysems, he convenional PI ype conrollers are carried ou for LFC. In order o overcome he drawbacks of he convenional PI conrollers, numerous echniques have been proposed in lieraures. In his paper a IP ype conroller is considered for LFC problem. he parameers of he proposed IP conroller are uned using Paricle Swarm Opimizaion (PSO) mehod. A muli area elecric power sysem wih a wide range of parameric uncerainies is given o illusrae proposed mehod. o show effeciveness of he proposed mehod, a PI ype conroller opimized by PSO is incorporaed in order o comparison wih he proposed IP conroller. he simulaion resuls on a muli area elecric power sysem emphasis on he viabiliy and feasibiliy of he proposed mehod in LFC problem. Key words: IP conroller, load frequency conrol, paricle swarm opimizaion, muli area elecric power sysem INOUCION For large scale elecric power sysems wih inerconneced areas, Load Frequency Conrol (LFC) is imporan o keep he sysem frequency and he iner-area ie power as near o he scheduled values as possible. he inpu mechanical power o he generaors is used o conrol he frequency of oupu elecrical power and o mainain he power exchange beween he areas as scheduled. A well designed and operaed power sysem mus cope wih changes in he load and wih sysem disurbances, and i should provide accepable high level of power qualiy while mainaining boh volage and frequency wihin olerable limis. any conrol sraegies for Load Frequency Conrol in elecric power sysems have been proposed by researchers over he pas decades. his exensive research is due o fac ha LFC consiues an imporan funcion of power sysem operaion where he main objecive is o regulae he oupu power of each generaor a prescribed levels while keeping he frequency flucuaions wihin pre-specifies limis. A unified uning of PI load frequency conroller for power sysems via inernal mode conrol has been proposed by an (). In his paper he uning mehod is based on he wo-egree-of-freedom (F) inernal model conrol (IC) design mehod and a PI approximaion procedure. A new discree-ime sliding mode conroller for load-frequency conrol in areas conrol of a power sysem has been presened by Vrdoljak e al. (). In his sudy full-sae feedback is applied for LFC no only in conrol areas wih hermal power plans bu also in conrol areas wih hydro power plans, in spie of heir non minimum phase behaviors. o enable full-sae feedback, a sae esimaion mehod based on fas sampling of measured oupu variables has been applied. he applicaions of arificial neural nework, geneic algorihms and opimal conrol o LFC have been repored by Kocaarslan and Cam (5), erkpreedapong e al. () and Liu e al. (). An adapive decenralized load frequency conrol of muliarea power sysems has been presened by Zribi e al. (5). Also he applicaion of robus conrol mehods for load frequency conrol problem has been presened by Shayeghi e al. (7) and aher and Hemai (8). his sudy deals wih a design mehod for LFC in a muli area elecric power sysem using a IP ype conroller whose parameers are uned using PSO. In order o show effeciveness of he proposed mehod, his IP conroller is Corresponding Auhor: Sayed ojaba Shirvani Boroujeni, eparmen of Elecrical Engineering, Boroujen Branch, Islamic Azad Universiy, Boroujen, Iran, ell.: ; Fax

2 es. J. Appl. Sci. Eng. echnol., (): 96-, Fig. : Four-area elecric power sysem wih inerconnecions Fig. : Block diagram for one area of sysem (i h area) compared wih a PI ype conroller whose parameers are uned using PSO oo. Simulaion resuls show ha he IP conroller guaranees robus performance under a wide range of operaing condiions and sysem uncerainies. PLAN OEL A four-area elecric power sysem is considered as a es sysem and shown in Fig.. he block diagram for each area of inerconneced areas is shown in Fig. (Wood and Wollenberg, ). he parameers in Fig. are defined as follow: ) : eviaion from nominal value i = H : Consan of ineria of i h area i : amping consan of i h area i : Gain of speed droop feedback loop of i h area i : urbine ime consan of i h area gi G i : Governor ime consan of i h area : Conroller of i h area Pdi u i : Load change of i h area : eference load of i h area B i = (/ i )+ i : Frequency bias facor of i h area P ie ij : Iner area ie power inerchange from i h area o j h area. where, i =,,,, j =,,, and i j he iner-area ie power inerchange is as () (Wood and Wollenberg, ): C ie ij = () i - ) j ) ( ij /S). () where, ij = 77 (/X ie ij) (for a 6 Hz sysem); X ie ij: Impedance of ransmission line beween i and j areas he )P ie ij block diagram is shown as Fig.. Figure shows he block diagram of i h area and Fig. shows he mehod of inerconnecion beween i h and j h areas. he sae space model of four-area inerconneced power sysem is as () (Wood and Wollenberg, ): where, &X = AX + BU Y = CX () U = [ )P )P )P )P u u u u ] Y = [ ) ) ) ) ) C ie, )C ie, )C ie, )C ie, )C ie, )C ie,] X = [ )P G )P )P G )P )P G )P )P G )P ) )C ie, )C ie, )C ie, )C ie, )C ie, )C ie,] he marixes A and B in () and he ypical values of sysem parameers for he nominal operaing condiion are given in appendix. As refereed before, he IP ype conroller is incorporaed o LFC problem. IP ype conroller is inroduced in he nex secion. 97

3 es. J. Appl. Sci. Eng. echnol., (): 96-, Fig. : Block diagram of iner area ie power ()P ie ij) U i U i,ref U O + Pl K P K I s Fig. : Srucure of he IP conroller IP Fig. 5: Oupu of IP and PI regulaors wih he same damping coefficien (> = ) and he same band widh a he same sep inpu signal command IP conroller: As referred before, in his sudy IP ype conrollers are considered for LFC problem. Fig. shows he srucure of IP conroller. I has some clear differences wih PI conroller. In he case of IP regulaor, a he sep inpu, he oupu of he regulaor varies slowly and is magniude is smaller han he magniude of PI regulaor a he same sep inpu (Sul, ). Also as shown in Fig.5, If he oupus of he boh regulaors are limied as he same value by physical consrains, hen compared o he bandwidh of PI regulaor he bandwidh of IP regulaor can be exended wihou he sauraion of he regulaor oupu (Sul, ). + ESIGN EHOOLOGY he proposed IP conroller performance is evaluaed on he proposed es sysem given in secion. he parameers of he IP conrollers are obained using PSO. In he nex subsecion a brief inroducion abou PSO is presened. Paricle swarm opimizaion: PSO was formulaed by Edward and Kennedy in 995. he hough process U o behind he algorihm was inspired by he social behavior of animals, such as bird flocking or fish schooling. PSO is similar o he coninuous GA in ha i begins wih a random populaion marix. Unlike he GA, PSO has no evoluion operaors such as crossover and muaion. he rows in he marix are called paricles (same as he GA chromosome). hey conain he variable values and are no binary encoded. Each paricle moves abou he cos surface wih a velociy. he paricles updae heir velociies and posiions based on he local and global bes soluions as shown in () and () (andy and Sue, ): where, V m,n P m,n new V m,n old local bes old = w V m,n + ' r (P m,n -P m,n ) + global bes old ' r (P m,n -P m,n ) () P new m,n = P old new m,n + ' V m,n () W r, r ' = ' local bes P m,n global bes P m,n = paricle velociy = paricle variables = ineria weigh = independen uniform random numbers = learning facors = bes local soluion = bes global soluion he PSO algorihm updaes he velociy vecor for each paricle hen adds ha velociy o he paricle posiion or values. Velociy updaes are influenced by boh he bes global soluion associaed wih he lowes cos ever found by a paricle and he bes local soluion associaed wih he lowes cos in he presen populaion. If he bes local soluion has a cos less han he cos of he curren global soluion, hen he bes local soluion replaces he bes global soluion. he paricle velociy is reminiscen of local minimizes ha use derivaive informaion, because velociy is he derivaive of posiion. he advanages of PSO are ha i is easy o implemen and here are few parameers o adjus. he PSO is able o ackle ough cos funcions wih many local minima (andy and Sue, ). IP conroller uning using PSO: In his secion he parameers of he proposed IP conrollers are uned using PSO. he IP conroller has wo parameers denoed by K P and K I and for each area here is one IP conroller. herefore in four-area elecric power sysem wih four IP conrollers, here are 8 parameers for uning. hese K parameers are obained based on he PSO. In secion, he sysem conrollers showed in Fig. as G i. Here hese conrollers are subsiued by IP conrollers and he opimum values of K P and K I are accuraely compued using PSO. In opimizaion mehods, he firs sep is o 98

4 es. J. Appl. Sci. Eng. echnol., (): 96-, Speed deviaions (p.u) Speed deviaions (p.u) Speed deviaions (p.u) ime (sec) (a) ime (sec) (b) ime (sec) (c) Fig. 6: ynamic response ) following sep change in demand of firs area ()C )a: Nominal b: Heavy c: Very heavy Solid (IP conroller), ashed (PI conroller) define a performance index for opimal search. In his sudy he performance index is considered as (5). In fac, he performance index is he Inegral of he ime muliplied Absolue value of he Error (IAE). IAE = ω d + ω d + ω d + ω d (5) he parameer "" in IAE is he simulaion ime. I is clear o undersand ha he conroller wih lower IAE is beer han he oher conrollers. o compue he opimum parameer values, a % sep change in P is assumed able : Opimum values of K P and K I for IP conrollers Firs area IP parameers Second area IP parameers.68. hird area IP parameers Fourh area IP parameers.55. able : Opimum values of K P and K I for PI conrollers Firs area PI parameers Second area PI parameers.978. hird area PI parameers Fourh area PI parameers able : 5% Sep increase in demand of s area ( C ) he calculaed IAE PI IP Nominal operaing condiion.59.9 Heavy operaing condiion.9.8 Very heavy operaing condiion.7.55 able : 5% Sep increase in demand of s area ( C ) and % sep increase in demand of rd area ( C ) he calculaed IAE PI IP Nominal operaing condiion.8.77 Heavy operaing condiion Very heavy operaing condiion.9.79 and he performance index is minimized using PSO. In order o acquire beer performance, number of paricle, paricle size, number of ieraion, ', ' and ' are chosen as, 8,,, and, respecively. Also, he ineria weigh, w, is linearly decreasing from.9 o.. I should be noed ha PSO algorihm is run several imes and hen opimal se of parameers is seleced. he opimum values of he parameers K P and K I are obained using PSO and summarized in he able. K P K P ESULS AN ISCUSSION In his secion he proposed IP conroller is applied o he sysem for LFC. In order o comparison and show effeciveness of he proposed mehod, anoher PI ype conroller opimized by PSO is designed for LFC. he opimumvalueofhe IP conrollers Parameers are obained using geneic algorihms and summarized in he able. In order o sudy and analysis sysem performance under sysem uncerainies (conroller robusness), hree operaing condiions are considered as follow: C Nominal operaing condiion C Heavy operaing condiion (% changing parameers from heir ypical values) C Very heavy operaing condiion (% changing parameers from heir ypical values) In order o demonsrae he robusness performance of he proposed mehod, he IAE is calculaed following sep change in he differen demands ()P ) a all K I K I 99

5 es. J. Appl. Sci. Eng. echnol., (): 96-, = A G G G G G G G G = B G G G G able 5: ypical values of sysem parameers for he nominal operaing condiion s area parameers =.5 G =.8 =.667 =. =.8 B =. =.5 =.5 =. =.55 =.5 =.6 nd area parameers =.5 G =.9 =.55 =. =.9 B =. =.5 =.5 =. =.55 =.5 =.6 rd area parameers =. G =.7 =.78 =.9 =.7 B =.8 =.5 =.5 =. =.55 =.5 =.6 h area parameers =. G =.85 =.5 =.995 =.9 B =.98 =.5 =.5 =. =.55 =.5 =.6 operaing condiions (Nominal, Heavy and Very heavy) and resuls are shown a able -. Following sep change, he IP conroller has beer performance han he PI conroller a all operaing condiions (able 5). Figure 6 shows ) a nominal, heavy and very heavy operaing condiions following % sep change in he demand of firs area ()P ). I is seen ha he IP conroller has beer performance han he oher mehod a all operaing condiions. CONCLUSION In his sudy a new PSO based IP conroller has been successfully carried ou for Load Frequency Conrol problem. he proposed mehod was applied o a ypical four-area elecric power sysem conaining sysem parameric uncerainies and various loads condiions. Simulaion resuls demonsraed ha he IP conrollers capable o guaranee he robus sabiliy and robus performance under a wide range of uncerainies and load Appendix: he ypical values of sysem parameers for he nominal operaing condiion are presened in able 5. Also he marixes A and B in () are as follow:

6 es. J. Appl. Sci. Eng. echnol., (): 96-, condiions. Also, he simulaion resuls showed ha he IP conroller is robus o change in he sysem parameers and i has beer performance han he PI ype conroller a all operaing condiions. EFEENCES Kocaarslan, I. and E. Cam, 5. Fuzzy logic conroller in inerconneced elecrical power Sysems for loadfrequency conrol. Elecr. Power Energy Sys., 7: Liu, F., Y.H. Song, J. a, S. ai and Q. Lu,. Opimal load frequency conrol in resrucured power sysems. IEE Proceedings Generaion, rans. is., 5(): andy, L.H. and E.H. Sue,. Pracical Geneic Algorihms, nd Edn., John Wiley & Sons, pp: erkpreedapong,., A. Hasanovic and A. Feliachi,. obus load frequency conrol using geneic algorihms and linear mmarix inequaliies. IEEE. Power Sys., 8(): Shayeghi, H., H.A. Shayanfar and O.P. alik, 7. obus decenralized neural neworks based LFC in a deregulaed power sysem. Elecric. Power Sys. es., 77: -5. Sul, S.K.,. Conrol of Elecric achine rive Sysems, John Wiley & Sons, Inc., Hoboken, NewJersey. an, W.,. UniWed uning of PI load frequency conroller for power sysems via IC. IEEE rans. Power Sys., 5(): -5. aher, S.A. and. Hemai, 8. obus decenralized load frequency conrol using muli variable QF mehod in deregulaed power sysems. Am. J. Appl. Sci., 5(7): Vrdoljak, K., N. Peric and I. Perovic,. Sliding mode based load-frequency conrol in power sysems. Elecric. Power Sys. es., 8: Wood, A.J. and B.F. Wollenberg,. Power Generaion, Operaion and Conrol. John Wiley & Sons. Zribi,.,. Al-ashed and. Alrifai, 5. Adapive decenralized load frequency conrol of muli-area power sysems. Elecrical Power Energ. Sys., 7:

Robust decentralized load frequency control in multiarea electric power system using quantitative feedback theory

Robust decentralized load frequency control in multiarea electric power system using quantitative feedback theory Scienific Research and Essays Vol. 5(), pp. 8-9, 8 Ocober, Available online a hp://www.academicjournals.org/sre ISSN 99-8 Academic Journals Full Lengh Research aper Robus decenralized load freuency conrol

More information

Particle Swarm Optimization

Particle Swarm Optimization Paricle Swarm Opimizaion Speaker: Jeng-Shyang Pan Deparmen of Elecronic Engineering, Kaohsiung Universiy of Applied Science, Taiwan Email: jspan@cc.kuas.edu.w 7/26/2004 ppso 1 Wha is he Paricle Swarm Opimizaion

More information

STATE-SPACE MODELLING. A mass balance across the tank gives:

STATE-SPACE MODELLING. A mass balance across the tank gives: B. Lennox and N.F. Thornhill, 9, Sae Space Modelling, IChemE Process Managemen and Conrol Subjec Group Newsleer STE-SPACE MODELLING Inroducion: Over he pas decade or so here has been an ever increasing

More information

Optimal Control of Dc Motor Using Performance Index of Energy

Optimal Control of Dc Motor Using Performance Index of Energy American Journal of Engineering esearch AJE 06 American Journal of Engineering esearch AJE e-issn: 30-0847 p-issn : 30-0936 Volume-5, Issue-, pp-57-6 www.ajer.org esearch Paper Open Access Opimal Conrol

More information

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

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

More information

Modal identification of structures from roving input data by means of maximum likelihood estimation of the state space model

Modal identification of structures from roving input data by means of maximum likelihood estimation of the state space model Modal idenificaion of srucures from roving inpu daa by means of maximum likelihood esimaion of he sae space model J. Cara, J. Juan, E. Alarcón Absrac The usual way o perform a forced vibraion es is o fix

More information

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle Chaper 2 Newonian Mechanics Single Paricle In his Chaper we will review wha Newon s laws of mechanics ell us abou he moion of a single paricle. Newon s laws are only valid in suiable reference frames,

More information

Sliding Mode Controller for Unstable Systems

Sliding Mode Controller for Unstable Systems S. SIVARAMAKRISHNAN e al., Sliding Mode Conroller for Unsable Sysems, Chem. Biochem. Eng. Q. 22 (1) 41 47 (28) 41 Sliding Mode Conroller for Unsable Sysems S. Sivaramakrishnan, A. K. Tangirala, and M.

More information

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

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

More information

Particle Swarm Optimization Combining Diversification and Intensification for Nonlinear Integer Programming Problems

Particle Swarm Optimization Combining Diversification and Intensification for Nonlinear Integer Programming Problems Paricle Swarm Opimizaion Combining Diversificaion and Inensificaion for Nonlinear Ineger Programming Problems Takeshi Masui, Masaoshi Sakawa, Kosuke Kao and Koichi Masumoo Hiroshima Universiy 1-4-1, Kagamiyama,

More information

Testing for a Single Factor Model in the Multivariate State Space Framework

Testing for a Single Factor Model in the Multivariate State Space Framework esing for a Single Facor Model in he Mulivariae Sae Space Framework Chen C.-Y. M. Chiba and M. Kobayashi Inernaional Graduae School of Social Sciences Yokohama Naional Universiy Japan Faculy of Economics

More information

Optimal Path Planning for Flexible Redundant Robot Manipulators

Optimal Path Planning for Flexible Redundant Robot Manipulators 25 WSEAS In. Conf. on DYNAMICAL SYSEMS and CONROL, Venice, Ialy, November 2-4, 25 (pp363-368) Opimal Pah Planning for Flexible Redundan Robo Manipulaors H. HOMAEI, M. KESHMIRI Deparmen of Mechanical Engineering

More information

CHAPTER 10 VALIDATION OF TEST WITH ARTIFICAL NEURAL NETWORK

CHAPTER 10 VALIDATION OF TEST WITH ARTIFICAL NEURAL NETWORK 175 CHAPTER 10 VALIDATION OF TEST WITH ARTIFICAL NEURAL NETWORK 10.1 INTRODUCTION Amongs he research work performed, he bes resuls of experimenal work are validaed wih Arificial Neural Nework. From he

More information

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

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

More information

Chapter 3 Boundary Value Problem

Chapter 3 Boundary Value Problem Chaper 3 Boundary Value Problem A boundary value problem (BVP) is a problem, ypically an ODE or a PDE, which has values assigned on he physical boundary of he domain in which he problem is specified. Le

More information

RC, RL and RLC circuits

RC, RL and RLC circuits Name Dae Time o Complee h m Parner Course/ Secion / Grade RC, RL and RLC circuis Inroducion In his experimen we will invesigae he behavior of circuis conaining combinaions of resisors, capaciors, and inducors.

More information

Dual Current-Mode Control for Single-Switch Two-Output Switching Power Converters

Dual Current-Mode Control for Single-Switch Two-Output Switching Power Converters Dual Curren-Mode Conrol for Single-Swich Two-Oupu Swiching Power Converers S. C. Wong, C. K. Tse and K. C. Tang Deparmen of Elecronic and Informaion Engineering Hong Kong Polyechnic Universiy, Hunghom,

More information

3.1.3 INTRODUCTION TO DYNAMIC OPTIMIZATION: DISCRETE TIME PROBLEMS. A. The Hamiltonian and First-Order Conditions in a Finite Time Horizon

3.1.3 INTRODUCTION TO DYNAMIC OPTIMIZATION: DISCRETE TIME PROBLEMS. A. The Hamiltonian and First-Order Conditions in a Finite Time Horizon 3..3 INRODUCION O DYNAMIC OPIMIZAION: DISCREE IME PROBLEMS A. he Hamilonian and Firs-Order Condiions in a Finie ime Horizon Define a new funcion, he Hamilonian funcion, H. H he change in he oal value of

More information

Stability and Bifurcation in a Neural Network Model with Two Delays

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

More information

Electrical and current self-induction

Electrical and current self-induction Elecrical and curren self-inducion F. F. Mende hp://fmnauka.narod.ru/works.hml mende_fedor@mail.ru Absrac The aricle considers he self-inducance of reacive elemens. Elecrical self-inducion To he laws of

More information

Sliding Mode Extremum Seeking Control for Linear Quadratic Dynamic Game

Sliding Mode Extremum Seeking Control for Linear Quadratic Dynamic Game Sliding Mode Exremum Seeking Conrol for Linear Quadraic Dynamic Game Yaodong Pan and Ümi Özgüner ITS Research Group, AIST Tsukuba Eas Namiki --, Tsukuba-shi,Ibaraki-ken 5-856, Japan e-mail: pan.yaodong@ais.go.jp

More information

An introduction to the theory of SDDP algorithm

An introduction to the theory of SDDP algorithm An inroducion o he heory of SDDP algorihm V. Leclère (ENPC) Augus 1, 2014 V. Leclère Inroducion o SDDP Augus 1, 2014 1 / 21 Inroducion Large scale sochasic problem are hard o solve. Two ways of aacking

More information

Applying Genetic Algorithms for Inventory Lot-Sizing Problem with Supplier Selection under Storage Capacity Constraints

Applying Genetic Algorithms for Inventory Lot-Sizing Problem with Supplier Selection under Storage Capacity Constraints IJCSI Inernaional Journal of Compuer Science Issues, Vol 9, Issue 1, No 1, January 2012 wwwijcsiorg 18 Applying Geneic Algorihms for Invenory Lo-Sizing Problem wih Supplier Selecion under Sorage Capaciy

More information

Chapter 5 Digital PID control algorithm. Hesheng Wang Department of Automation,SJTU 2016,03

Chapter 5 Digital PID control algorithm. Hesheng Wang Department of Automation,SJTU 2016,03 Chaper 5 Digial PID conrol algorihm Hesheng Wang Deparmen of Auomaion,SJTU 216,3 Ouline Absrac Quasi-coninuous PID conrol algorihm Improvemen of sandard PID algorihm Choosing parameer of PID regulaor Brief

More information

Application of a Stochastic-Fuzzy Approach to Modeling Optimal Discrete Time Dynamical Systems by Using Large Scale Data Processing

Application of a Stochastic-Fuzzy Approach to Modeling Optimal Discrete Time Dynamical Systems by Using Large Scale Data Processing Applicaion of a Sochasic-Fuzzy Approach o Modeling Opimal Discree Time Dynamical Sysems by Using Large Scale Daa Processing AA WALASZE-BABISZEWSA Deparmen of Compuer Engineering Opole Universiy of Technology

More information

Block Diagram of a DCS in 411

Block Diagram of a DCS in 411 Informaion source Forma A/D From oher sources Pulse modu. Muliplex Bandpass modu. X M h: channel impulse response m i g i s i Digial inpu Digial oupu iming and synchronizaion Digial baseband/ bandpass

More information

Continuous Time. Time-Domain System Analysis. Impulse Response. Impulse Response. Impulse Response. Impulse Response. ( t) + b 0.

Continuous Time. Time-Domain System Analysis. Impulse Response. Impulse Response. Impulse Response. Impulse Response. ( t) + b 0. Time-Domain Sysem Analysis Coninuous Time. J. Robers - All Righs Reserved. Edied by Dr. Rober Akl 1. J. Robers - All Righs Reserved. Edied by Dr. Rober Akl 2 Le a sysem be described by a 2 y ( ) + a 1

More information

SOLUTIONS TO ECE 3084

SOLUTIONS TO ECE 3084 SOLUTIONS TO ECE 384 PROBLEM 2.. For each sysem below, specify wheher or no i is: (i) memoryless; (ii) causal; (iii) inverible; (iv) linear; (v) ime invarian; Explain your reasoning. If he propery is no

More information

Robust and Learning Control for Complex Systems

Robust and Learning Control for Complex Systems Robus and Learning Conrol for Complex Sysems Peer M. Young Sepember 13, 2007 & Talk Ouline Inroducion Robus Conroller Analysis and Design Theory Experimenal Applicaions Overview MIMO Robus HVAC Conrol

More information

Keywords Digital Infinite-Impulse Response (IIR) filter, Digital Finite-Impulse Response (FIR) filter, DE, exploratory move

Keywords Digital Infinite-Impulse Response (IIR) filter, Digital Finite-Impulse Response (FIR) filter, DE, exploratory move Volume 5, Issue 7, July 2015 ISSN: 2277 128X Inernaional Journal of Advanced Research in Compuer Science and Sofware Engineering Research Paper Available online a: www.ijarcsse.com A Hybrid Differenial

More information

A Primal-Dual Type Algorithm with the O(1/t) Convergence Rate for Large Scale Constrained Convex Programs

A Primal-Dual Type Algorithm with the O(1/t) Convergence Rate for Large Scale Constrained Convex Programs PROC. IEEE CONFERENCE ON DECISION AND CONTROL, 06 A Primal-Dual Type Algorihm wih he O(/) Convergence Rae for Large Scale Consrained Convex Programs Hao Yu and Michael J. Neely Absrac This paper considers

More information

Vehicle Arrival Models : Headway

Vehicle Arrival Models : Headway Chaper 12 Vehicle Arrival Models : Headway 12.1 Inroducion Modelling arrival of vehicle a secion of road is an imporan sep in raffic flow modelling. I has imporan applicaion in raffic flow simulaion where

More information

10. State Space Methods

10. State Space Methods . Sae Space Mehods. Inroducion Sae space modelling was briefly inroduced in chaper. Here more coverage is provided of sae space mehods before some of heir uses in conrol sysem design are covered in he

More information

Lecture 9: September 25

Lecture 9: September 25 0-725: Opimizaion Fall 202 Lecure 9: Sepember 25 Lecurer: Geoff Gordon/Ryan Tibshirani Scribes: Xuezhi Wang, Subhodeep Moira, Abhimanu Kumar Noe: LaTeX emplae couresy of UC Berkeley EECS dep. Disclaimer:

More information

Air Quality Index Prediction Using Error Back Propagation Algorithm and Improved Particle Swarm Optimization

Air Quality Index Prediction Using Error Back Propagation Algorithm and Improved Particle Swarm Optimization Air Qualiy Index Predicion Using Error Back Propagaion Algorihm and Improved Paricle Swarm Opimizaion Jia Xu ( ) and Lang Pei College of Compuer Science, Wuhan Qinchuan Universiy, Wuhan, China 461406563@qq.com

More information

Lecture 2 October ε-approximation of 2-player zero-sum games

Lecture 2 October ε-approximation of 2-player zero-sum games Opimizaion II Winer 009/10 Lecurer: Khaled Elbassioni Lecure Ocober 19 1 ε-approximaion of -player zero-sum games In his lecure we give a randomized ficiious play algorihm for obaining an approximae soluion

More information

Lab 10: RC, RL, and RLC Circuits

Lab 10: RC, RL, and RLC Circuits Lab 10: RC, RL, and RLC Circuis In his experimen, we will invesigae he behavior of circuis conaining combinaions of resisors, capaciors, and inducors. We will sudy he way volages and currens change in

More information

Georey E. Hinton. University oftoronto. Technical Report CRG-TR February 22, Abstract

Georey E. Hinton. University oftoronto.   Technical Report CRG-TR February 22, Abstract Parameer Esimaion for Linear Dynamical Sysems Zoubin Ghahramani Georey E. Hinon Deparmen of Compuer Science Universiy oftorono 6 King's College Road Torono, Canada M5S A4 Email: zoubin@cs.orono.edu Technical

More information

Two Coupled Oscillators / Normal Modes

Two Coupled Oscillators / Normal Modes Lecure 3 Phys 3750 Two Coupled Oscillaors / Normal Modes Overview and Moivaion: Today we ake a small, bu significan, sep owards wave moion. We will no ye observe waves, bu his sep is imporan in is own

More information

The electromagnetic interference in case of onboard navy ships computers - a new approach

The electromagnetic interference in case of onboard navy ships computers - a new approach The elecromagneic inerference in case of onboard navy ships compuers - a new approach Prof. dr. ing. Alexandru SOTIR Naval Academy Mircea cel Bărân, Fulgerului Sree, Consanţa, soiralexandru@yahoo.com Absrac.

More information

STRUCTURAL CHANGE IN TIME SERIES OF THE EXCHANGE RATES BETWEEN YEN-DOLLAR AND YEN-EURO IN

STRUCTURAL CHANGE IN TIME SERIES OF THE EXCHANGE RATES BETWEEN YEN-DOLLAR AND YEN-EURO IN Inernaional Journal of Applied Economerics and Quaniaive Sudies. Vol.1-3(004) STRUCTURAL CHANGE IN TIME SERIES OF THE EXCHANGE RATES BETWEEN YEN-DOLLAR AND YEN-EURO IN 001-004 OBARA, Takashi * Absrac The

More information

Time Domain Transfer Function of the Induction Motor

Time Domain Transfer Function of the Induction Motor Sudies in Engineering and Technology Vol., No. ; Augus 0 ISSN 008 EISSN 006 Published by Redfame Publishing URL: hp://se.redfame.com Time Domain Transfer Funcion of he Inducion Moor N N arsoum Correspondence:

More information

Navneet Saini, Mayank Goyal, Vishal Bansal (2013); Term Project AML310; Indian Institute of Technology Delhi

Navneet Saini, Mayank Goyal, Vishal Bansal (2013); Term Project AML310; Indian Institute of Technology Delhi Creep in Viscoelasic Subsances Numerical mehods o calculae he coefficiens of he Prony equaion using creep es daa and Herediary Inegrals Mehod Navnee Saini, Mayank Goyal, Vishal Bansal (23); Term Projec

More information

Course Notes for EE227C (Spring 2018): Convex Optimization and Approximation

Course Notes for EE227C (Spring 2018): Convex Optimization and Approximation Course Noes for EE7C Spring 018: Convex Opimizaion and Approximaion Insrucor: Moriz Hard Email: hard+ee7c@berkeley.edu Graduae Insrucor: Max Simchowiz Email: msimchow+ee7c@berkeley.edu Ocober 15, 018 3

More information

BU Macro BU Macro Fall 2008, Lecture 4

BU Macro BU Macro Fall 2008, Lecture 4 Dynamic Programming BU Macro 2008 Lecure 4 1 Ouline 1. Cerainy opimizaion problem used o illusrae: a. Resricions on exogenous variables b. Value funcion c. Policy funcion d. The Bellman equaion and an

More information

Technical Report Doc ID: TR March-2013 (Last revision: 23-February-2016) On formulating quadratic functions in optimization models.

Technical Report Doc ID: TR March-2013 (Last revision: 23-February-2016) On formulating quadratic functions in optimization models. Technical Repor Doc ID: TR--203 06-March-203 (Las revision: 23-Februar-206) On formulaing quadraic funcions in opimizaion models. Auhor: Erling D. Andersen Convex quadraic consrains quie frequenl appear

More information

SZG Macro 2011 Lecture 3: Dynamic Programming. SZG macro 2011 lecture 3 1

SZG Macro 2011 Lecture 3: Dynamic Programming. SZG macro 2011 lecture 3 1 SZG Macro 2011 Lecure 3: Dynamic Programming SZG macro 2011 lecure 3 1 Background Our previous discussion of opimal consumpion over ime and of opimal capial accumulaion sugges sudying he general decision

More information

Computation of the Effect of Space Harmonics on Starting Process of Induction Motors Using TSFEM

Computation of the Effect of Space Harmonics on Starting Process of Induction Motors Using TSFEM Journal of elecrical sysems Special Issue N 01 : November 2009 pp: 48-52 Compuaion of he Effec of Space Harmonics on Saring Process of Inducion Moors Using TSFEM Youcef Ouazir USTHB Laboraoire des sysèmes

More information

EE 301 Lab 2 Convolution

EE 301 Lab 2 Convolution EE 301 Lab 2 Convoluion 1 Inroducion In his lab we will gain some more experience wih he convoluion inegral and creae a scrip ha shows he graphical mehod of convoluion. 2 Wha you will learn This lab will

More information

T L. t=1. Proof of Lemma 1. Using the marginal cost accounting in Equation(4) and standard arguments. t )+Π RB. t )+K 1(Q RB

T L. t=1. Proof of Lemma 1. Using the marginal cost accounting in Equation(4) and standard arguments. t )+Π RB. t )+K 1(Q RB Elecronic Companion EC.1. Proofs of Technical Lemmas and Theorems LEMMA 1. Le C(RB) be he oal cos incurred by he RB policy. Then we have, T L E[C(RB)] 3 E[Z RB ]. (EC.1) Proof of Lemma 1. Using he marginal

More information

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

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

More information

OPTIMIZATION OF POWER SYSTEM STABILIZER BY GENETIC ALGORITHM. Ján Murgaš, Ivan Sekaj, Martin Foltin and Eva Miklovičová

OPTIMIZATION OF POWER SYSTEM STABILIZER BY GENETIC ALGORITHM. Ján Murgaš, Ivan Sekaj, Martin Foltin and Eva Miklovičová OPTIMIZATION OF POWER SYSTEM STABILIZER BY GENETIC ALGORITHM Ján Murgaš, Ivan Sekaj, Marin Folin and Eva Miklovičová Deparmen of Auomaic Conrol Sysems, Faculy of Elecrical Engineering and Informaion Technology,

More information

Single-Pass-Based Heuristic Algorithms for Group Flexible Flow-shop Scheduling Problems

Single-Pass-Based Heuristic Algorithms for Group Flexible Flow-shop Scheduling Problems Single-Pass-Based Heurisic Algorihms for Group Flexible Flow-shop Scheduling Problems PEI-YING HUANG, TZUNG-PEI HONG 2 and CHENG-YAN KAO, 3 Deparmen of Compuer Science and Informaion Engineering Naional

More information

Robust estimation based on the first- and third-moment restrictions of the power transformation model

Robust estimation based on the first- and third-moment restrictions of the power transformation model h Inernaional Congress on Modelling and Simulaion, Adelaide, Ausralia, 6 December 3 www.mssanz.org.au/modsim3 Robus esimaion based on he firs- and hird-momen resricions of he power ransformaion Nawaa,

More information

Online Appendix to Solution Methods for Models with Rare Disasters

Online Appendix to Solution Methods for Models with Rare Disasters Online Appendix o Soluion Mehods for Models wih Rare Disasers Jesús Fernández-Villaverde and Oren Levinal In his Online Appendix, we presen he Euler condiions of he model, we develop he pricing Calvo block,

More information

An Optimal Dynamic Generation Scheduling for a Wind-Thermal Power System *

An Optimal Dynamic Generation Scheduling for a Wind-Thermal Power System * Energy and Power Engineering, 2013, 5, 1016-1021 doi:10.4236/epe.2013.54b194 Published Online July 2013 (hp://www.scirp.org/journal/epe) An Opimal Dynamic Generaion Scheduling for a Wind-Thermal Power

More information

Notes on Kalman Filtering

Notes on Kalman Filtering Noes on Kalman Filering Brian Borchers and Rick Aser November 7, Inroducion Daa Assimilaion is he problem of merging model predicions wih acual measuremens of a sysem o produce an opimal esimae of he curren

More information

INVERSE RESPONSE COMPENSATION BY ESTIMATING PARAMETERS OF A PROCESS COMPRISING OF TWO FIRST ORDER SYSTEMS

INVERSE RESPONSE COMPENSATION BY ESTIMATING PARAMETERS OF A PROCESS COMPRISING OF TWO FIRST ORDER SYSTEMS Inernaional Journal of Informaion Technology and nowledge Managemen July-December 0, Volume 5, No., pp. 433-438 INVERSE RESPONSE COMPENSATION BY ESTIMATING PARAMETERS OF A PROCESS COMPRISING OF TWO FIRST

More information

Chapter 2. First Order Scalar Equations

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

More information

MODULE - 9 LECTURE NOTES 2 GENETIC ALGORITHMS

MODULE - 9 LECTURE NOTES 2 GENETIC ALGORITHMS 1 MODULE - 9 LECTURE NOTES 2 GENETIC ALGORITHMS INTRODUCTION Mos real world opimizaion problems involve complexiies like discree, coninuous or mixed variables, muliple conflicing objecives, non-lineariy,

More information

The Potential Effectiveness of the Detection of Pulsed Signals in the Non-Uniform Sampling

The Potential Effectiveness of the Detection of Pulsed Signals in the Non-Uniform Sampling The Poenial Effeciveness of he Deecion of Pulsed Signals in he Non-Uniform Sampling Arhur Smirnov, Sanislav Vorobiev and Ajih Abraham 3, 4 Deparmen of Compuer Science, Universiy of Illinois a Chicago,

More information

L07. KALMAN FILTERING FOR NON-LINEAR SYSTEMS. NA568 Mobile Robotics: Methods & Algorithms

L07. KALMAN FILTERING FOR NON-LINEAR SYSTEMS. NA568 Mobile Robotics: Methods & Algorithms L07. KALMAN FILTERING FOR NON-LINEAR SYSTEMS NA568 Mobile Roboics: Mehods & Algorihms Today s Topic Quick review on (Linear) Kalman Filer Kalman Filering for Non-Linear Sysems Exended Kalman Filer (EKF)

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION DOI: 0.038/NCLIMATE893 Temporal resoluion and DICE * Supplemenal Informaion Alex L. Maren and Sephen C. Newbold Naional Cener for Environmenal Economics, US Environmenal Proecion

More information

Random Walk with Anti-Correlated Steps

Random Walk with Anti-Correlated Steps Random Walk wih Ani-Correlaed Seps John Noga Dirk Wagner 2 Absrac We conjecure he expeced value of random walks wih ani-correlaed seps o be exacly. We suppor his conjecure wih 2 plausibiliy argumens and

More information

Application Note AN Software release of SemiSel version 3.1. New semiconductor available. Temperature ripple at low inverter output frequencies

Application Note AN Software release of SemiSel version 3.1. New semiconductor available. Temperature ripple at low inverter output frequencies Applicaion Noe AN-8004 Revision: Issue Dae: Prepared by: 00 2008-05-21 Dr. Arend Winrich Ke y Words: SemiSel, Semiconducor Selecion, Loss Calculaion Sofware release of SemiSel version 3.1 New semiconducor

More information

6.01: Introduction to EECS I Lecture 8 March 29, 2011

6.01: Introduction to EECS I Lecture 8 March 29, 2011 6.01: Inroducion o EES I Lecure 8 March 29, 2011 6.01: Inroducion o EES I Op-Amps Las Time: The ircui Absracion ircuis represen sysems as connecions of elemens hrough which currens (hrough variables) flow

More information

Scheduling of Crude Oil Movements at Refinery Front-end

Scheduling of Crude Oil Movements at Refinery Front-end Scheduling of Crude Oil Movemens a Refinery Fron-end Ramkumar Karuppiah and Ignacio Grossmann Carnegie Mellon Universiy ExxonMobil Case Sudy: Dr. Kevin Furman Enerprise-wide Opimizaion Projec March 15,

More information

Linear Response Theory: The connection between QFT and experiments

Linear Response Theory: The connection between QFT and experiments Phys540.nb 39 3 Linear Response Theory: The connecion beween QFT and experimens 3.1. Basic conceps and ideas Q: How do we measure he conduciviy of a meal? A: we firs inroduce a weak elecric field E, and

More information

Embedded Systems and Software. A Simple Introduction to Embedded Control Systems (PID Control)

Embedded Systems and Software. A Simple Introduction to Embedded Control Systems (PID Control) Embedded Sysems and Sofware A Simple Inroducion o Embedded Conrol Sysems (PID Conrol) Embedded Sysems and Sofware, ECE:3360. The Universiy of Iowa, 2016 Slide 1 Acknowledgemens The maerial in his lecure

More information

LAPLACE TRANSFORM AND TRANSFER FUNCTION

LAPLACE TRANSFORM AND TRANSFER FUNCTION CHBE320 LECTURE V LAPLACE TRANSFORM AND TRANSFER FUNCTION Professor Dae Ryook Yang Spring 2018 Dep. of Chemical and Biological Engineering 5-1 Road Map of he Lecure V Laplace Transform and Transfer funcions

More information

Let us start with a two dimensional case. We consider a vector ( x,

Let us start with a two dimensional case. We consider a vector ( x, Roaion marices We consider now roaion marices in wo and hree dimensions. We sar wih wo dimensions since wo dimensions are easier han hree o undersand, and one dimension is a lile oo simple. However, our

More information

PENALIZED LEAST SQUARES AND PENALIZED LIKELIHOOD

PENALIZED LEAST SQUARES AND PENALIZED LIKELIHOOD PENALIZED LEAST SQUARES AND PENALIZED LIKELIHOOD HAN XIAO 1. Penalized Leas Squares Lasso solves he following opimizaion problem, ˆβ lasso = arg max β R p+1 1 N y i β 0 N x ij β j β j (1.1) for some 0.

More information

Optimal Design of LQR Weighting Matrices based on Intelligent Optimization Methods

Optimal Design of LQR Weighting Matrices based on Intelligent Optimization Methods Opimal Design of LQR Weighing Marices based on Inelligen Opimizaion Mehods Inernaional Journal of Inelligen Informaion Processing, Volume, Number, March Opimal Design of LQR Weighing Marices based on Inelligen

More information

Improved Approximate Solutions for Nonlinear Evolutions Equations in Mathematical Physics Using the Reduced Differential Transform Method

Improved Approximate Solutions for Nonlinear Evolutions Equations in Mathematical Physics Using the Reduced Differential Transform Method Journal of Applied Mahemaics & Bioinformaics, vol., no., 01, 1-14 ISSN: 179-660 (prin), 179-699 (online) Scienpress Ld, 01 Improved Approimae Soluions for Nonlinear Evoluions Equaions in Mahemaical Physics

More information

Lecture -14: Chopper fed DC Drives

Lecture -14: Chopper fed DC Drives Lecure -14: Chopper fed DC Drives Chopper fed DC drives o A chopper is a saic device ha convers fixed DC inpu volage o a variable dc oupu volage direcly o A chopper is a high speed on/off semiconducor

More information

A Specification Test for Linear Dynamic Stochastic General Equilibrium Models

A Specification Test for Linear Dynamic Stochastic General Equilibrium Models Journal of Saisical and Economeric Mehods, vol.1, no.2, 2012, 65-70 ISSN: 2241-0384 (prin), 2241-0376 (online) Scienpress Ld, 2012 A Specificaion Tes for Linear Dynamic Sochasic General Equilibrium Models

More information

ECE 2100 Circuit Analysis

ECE 2100 Circuit Analysis ECE 1 Circui Analysis Lesson 35 Chaper 8: Second Order Circuis Daniel M. Liynski, Ph.D. ECE 1 Circui Analysis Lesson 3-34 Chaper 7: Firs Order Circuis (Naural response RC & RL circuis, Singulariy funcions,

More information

EXPLICIT TIME INTEGRATORS FOR NONLINEAR DYNAMICS DERIVED FROM THE MIDPOINT RULE

EXPLICIT TIME INTEGRATORS FOR NONLINEAR DYNAMICS DERIVED FROM THE MIDPOINT RULE Version April 30, 2004.Submied o CTU Repors. EXPLICIT TIME INTEGRATORS FOR NONLINEAR DYNAMICS DERIVED FROM THE MIDPOINT RULE Per Krysl Universiy of California, San Diego La Jolla, California 92093-0085,

More information

( ) ( ) if t = t. It must satisfy the identity. So, bulkiness of the unit impulse (hyper)function is equal to 1. The defining characteristic is

( ) ( ) if t = t. It must satisfy the identity. So, bulkiness of the unit impulse (hyper)function is equal to 1. The defining characteristic is UNIT IMPULSE RESPONSE, UNIT STEP RESPONSE, STABILITY. Uni impulse funcion (Dirac dela funcion, dela funcion) rigorously defined is no sricly a funcion, bu disribuion (or measure), precise reamen requires

More information

Article from. Predictive Analytics and Futurism. July 2016 Issue 13

Article from. Predictive Analytics and Futurism. July 2016 Issue 13 Aricle from Predicive Analyics and Fuurism July 6 Issue An Inroducion o Incremenal Learning By Qiang Wu and Dave Snell Machine learning provides useful ools for predicive analyics The ypical machine learning

More information

MATH 5720: Gradient Methods Hung Phan, UMass Lowell October 4, 2018

MATH 5720: Gradient Methods Hung Phan, UMass Lowell October 4, 2018 MATH 5720: Gradien Mehods Hung Phan, UMass Lowell Ocober 4, 208 Descen Direcion Mehods Consider he problem min { f(x) x R n}. The general descen direcions mehod is x k+ = x k + k d k where x k is he curren

More information

Open Access Modeling and Optimization Control for Aircraft AC Generator Brushless Excitation System Based on Improved Adaptive PSO

Open Access Modeling and Optimization Control for Aircraft AC Generator Brushless Excitation System Based on Improved Adaptive PSO Send Orders for Reprins o reprins@benhamscience.ae The Open Auomaion and Conrol Sysems Journal, 2015, 7, 21-30 21 Open Access Modeling and Opimizaion Conrol for Aircraf AC Generaor Brushless Exciaion Sysem

More information

23.5. Half-Range Series. Introduction. Prerequisites. Learning Outcomes

23.5. Half-Range Series. Introduction. Prerequisites. Learning Outcomes Half-Range Series 2.5 Inroducion In his Secion we address he following problem: Can we find a Fourier series expansion of a funcion defined over a finie inerval? Of course we recognise ha such a funcion

More information

A Shooting Method for A Node Generation Algorithm

A Shooting Method for A Node Generation Algorithm A Shooing Mehod for A Node Generaion Algorihm Hiroaki Nishikawa W.M.Keck Foundaion Laboraory for Compuaional Fluid Dynamics Deparmen of Aerospace Engineering, Universiy of Michigan, Ann Arbor, Michigan

More information

INDEX. Transient analysis 1 Initial Conditions 1

INDEX. Transient analysis 1 Initial Conditions 1 INDEX Secion Page Transien analysis 1 Iniial Condiions 1 Please inform me of your opinion of he relaive emphasis of he review maerial by simply making commens on his page and sending i o me a: Frank Mera

More information

R.#W.#Erickson# Department#of#Electrical,#Computer,#and#Energy#Engineering# University#of#Colorado,#Boulder#

R.#W.#Erickson# Department#of#Electrical,#Computer,#and#Energy#Engineering# University#of#Colorado,#Boulder# .#W.#Erickson# Deparmen#of#Elecrical,#Compuer,#and#Energy#Engineering# Universiy#of#Colorado,#Boulder# Chaper 2 Principles of Seady-Sae Converer Analysis 2.1. Inroducion 2.2. Inducor vol-second balance,

More information

Problemas das Aulas Práticas

Problemas das Aulas Práticas Mesrado Inegrado em Engenharia Elecroécnica e de Compuadores Conrolo em Espaço de Esados Problemas das Aulas Práicas J. Miranda Lemos Fevereiro de 3 Translaed o English by José Gaspar, 6 J. M. Lemos, IST

More information

Spring Ammar Abu-Hudrouss Islamic University Gaza

Spring Ammar Abu-Hudrouss Islamic University Gaza Chaper 7 Reed-Solomon Code Spring 9 Ammar Abu-Hudrouss Islamic Universiy Gaza ١ Inroducion A Reed Solomon code is a special case of a BCH code in which he lengh of he code is one less han he size of he

More information

Policy regimes Theory

Policy regimes Theory Advanced Moneary Theory and Policy EPOS 2012/13 Policy regimes Theory Giovanni Di Barolomeo giovanni.dibarolomeo@uniroma1.i The moneary policy regime The simple model: x = - s (i - p e ) + x e + e D p

More information

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients

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

More information

Determination of the Sampling Period Required for a Fast Dynamic Response of DC-Motors

Determination of the Sampling Period Required for a Fast Dynamic Response of DC-Motors Deerminaion of he Sampling Period Required for a Fas Dynamic Response of DC-Moors J. A. GA'EB, Deparmen of Elecrical and Compuer Eng, The Hashemie Universiy, P.O.Box 15459, Posal code 13115, Zerka, JORDAN

More information

Lecture 4 Kinetics of a particle Part 3: Impulse and Momentum

Lecture 4 Kinetics of a particle Part 3: Impulse and Momentum MEE Engineering Mechanics II Lecure 4 Lecure 4 Kineics of a paricle Par 3: Impulse and Momenum Linear impulse and momenum Saring from he equaion of moion for a paricle of mass m which is subjeced o an

More information

Multi-scale 2D acoustic full waveform inversion with high frequency impulsive source

Multi-scale 2D acoustic full waveform inversion with high frequency impulsive source Muli-scale D acousic full waveform inversion wih high frequency impulsive source Vladimir N Zubov*, Universiy of Calgary, Calgary AB vzubov@ucalgaryca and Michael P Lamoureux, Universiy of Calgary, Calgary

More information

Reading from Young & Freedman: For this topic, read sections 25.4 & 25.5, the introduction to chapter 26 and sections 26.1 to 26.2 & 26.4.

Reading from Young & Freedman: For this topic, read sections 25.4 & 25.5, the introduction to chapter 26 and sections 26.1 to 26.2 & 26.4. PHY1 Elecriciy Topic 7 (Lecures 1 & 11) Elecric Circuis n his opic, we will cover: 1) Elecromoive Force (EMF) ) Series and parallel resisor combinaions 3) Kirchhoff s rules for circuis 4) Time dependence

More information

Some Basic Information about M-S-D Systems

Some Basic Information about M-S-D Systems Some Basic Informaion abou M-S-D Sysems 1 Inroducion We wan o give some summary of he facs concerning unforced (homogeneous) and forced (non-homogeneous) models for linear oscillaors governed by second-order,

More information

Math 315: Linear Algebra Solutions to Assignment 6

Math 315: Linear Algebra Solutions to Assignment 6 Mah 35: Linear Algebra s o Assignmen 6 # Which of he following ses of vecors are bases for R 2? {2,, 3, }, {4,, 7, 8}, {,,, 3}, {3, 9, 4, 2}. Explain your answer. To generae he whole R 2, wo linearly independen

More information

Open loop vs Closed Loop. Example: Open Loop. Example: Feedforward Control. Advanced Control I

Open loop vs Closed Loop. Example: Open Loop. Example: Feedforward Control. Advanced Control I Open loop vs Closed Loop Advanced I Moor Command Movemen Overview Open Loop vs Closed Loop Some examples Useful Open Loop lers Dynamical sysems CPG (biologically inspired ), Force Fields Feedback conrol

More information

Subway stations energy and air quality management

Subway stations energy and air quality management Subway saions energy and air qualiy managemen wih sochasic opimizaion Trisan Rigau 1,2,4, Advisors: P. Carpenier 3, J.-Ph. Chancelier 2, M. De Lara 2 EFFICACITY 1 CERMICS, ENPC 2 UMA, ENSTA 3 LISIS, IFSTTAR

More information

Comparative study between two models of a linear oscillating tubular motor

Comparative study between two models of a linear oscillating tubular motor IOSR Journal of Elecrical and Elecronics Engineering (IOSR-JEEE) e-issn: 78-676,p-ISSN: 3-333, Volume 9, Issue Ver. IV (Feb. 4), PP 77-83 Comparaive sudy beween wo models of a linear oscillaing ubular

More information

Continuous Time Linear Time Invariant (LTI) Systems. Dr. Ali Hussein Muqaibel. Introduction

Continuous Time Linear Time Invariant (LTI) Systems. Dr. Ali Hussein Muqaibel. Introduction /9/ Coninuous Time Linear Time Invarian (LTI) Sysems Why LTI? Inroducion Many physical sysems. Easy o solve mahemaically Available informaion abou analysis and design. We can apply superposiion LTI Sysem

More information