ESTIMATION OF POSITIONS OF VEHICLES WITH THE UNSCENETED KALMAN FILTER

Size: px
Start display at page:

Download "ESTIMATION OF POSITIONS OF VEHICLES WITH THE UNSCENETED KALMAN FILTER"

Transcription

1 ESIMAION O OSIIONS O VEICES I E UNSCENEED AMAN IER Masahro Ida DENSO CORORAION -, Showa-cho, arya-sh, Ach , Japan hone: , , adash omya Chba Insttute of echnology -7- sudanuma, Narashno-sh, Chba , Japan hone: , , roau Aahane rofessor, Chba Insttute of echnology -7- sudanuma, Narashno-sh, Chba , Japan hone: , , ABSRAC hs paper reports the effect of applcaton of the Unscented alman lter to estmaton of vehcle postons. GS/Dead Reconng DR navgaton systems have ordnarly adopted the Etended alman lter E due to the non-lnearty of the estmaton models. e appled the Unscented alman lter that s epected to gve us more precse nonlnear estmaton than the E and compared ts performances wth the E s. Our eperments at a test course where postons of an eperment car at every /3 second precsely surveyed as crtera of the valdaton showed that the proposed method was effectve especally the vehcle turns tghtly. eywords: Unscented alman lter, dead reconng, car navgaton system, vehcle postonng INRODUCION In IS, drver support systems that provde drvers wth safe nformaton, warnng or control are requred. In order to put the systems nto practce, more accurate vehcle postonng method s necessary. In ths study, among many approaches to the more accurate vehcle postonng, we focus on GS/DR navgaton algorthm. he Etended alman lter E s commonly appled for the GS/DR navgaton algorthm, but t s not suffcently accurate under the non-lnear systems such as vehcle postonng. In general the Unscented alman lter U provdes sgnfcant mprovement over the E, therefore we compared the accuracy of the vehcle poston estmaton by the U wth the accuracy by the E. --

2 OBSERVAION SYSEM he observaton system conssts of an epermental vehcle gure and an ntegrated processng system 3. he epermental vehcle s equpped wth R-GS recever, 3-ases gyro, 3-ases accelerometer and non-contact speed sensor to measure the accurate vehcle behavor. In ths system, data acquston cycle of R-GS recever s 5 and other sensors cycles are 3, and the vehcle can collect these data n synchroned at 3. In the ntegrated processng system, the Etend alman Smoother ES s appled to estmate three-dmensonal vehcle nematcs of translaton and rotaton gure. It was verfed by precse surveyng at test course that the horontal errors of the estmated postons of the epermental vehcle wth the ES were less than centmeters at every /3 second. gure. Epermental vehcle X XY-plane Z Y Vehcle υ θ φ ψ α Road surface gure. Vehcle moton model y IERING AGORIMS In ths study, for the real tme estmaton of postons of vehcles, flterng was evaluated. he E can be derved easly from the ES of the observaton system mentoned above. Equaton ndcates the state equaton and equaton ndcates the observaton equaton. he state vector s 3 dmensonal and t conssts of the world coordnate, 3D drectons, 3D speeds, 3D acceleratons, etc. f w y h e :state vector, y :observaton vector, w, e :whte noses f : state transton functon, h: observaton functon, :tme he algorthms of the E and the U of ths system are shown below. In ths system, the state equaton s lner and the observaton equaton s non-lner. In order to mae the condton even between the E and the U, dentcal values were used for the observaton nose and the ntal value of the covarance matr. Etended alman lter --

3 -3- me Update: w Measurement Update: e h here, h Unscented alman lter me Update: w Measurement Update: χ χ χ h χ γ s γ [ ][ ] s e γ γ

4 here, s c c s c [ χ ][ γ ] α β α κ s the dmenson of state. ESIMAION O OSIIONS BY EXERIMEN In ths eperment, several vehcle behavor data were acqured usng the epermental vehcle at a test course. he vehcle behavor data patterns are such as crcut trac data at varous speed, ban data, hyper slow speed, stop-and-go, turnng at an ntersecton and crclng. Because the test course s almost all open sy ecept several over paths, GS receve condton was good. And because there s no speed lmt n the test course, we could acqure hgh-speed data as n Japan. Epermental Results gure 3 to gure8 shows some results. One fgure ncludes a trajectory by the E and a trajectory by the U and GS postonng ponts. Because almost all data were taen under the open sy, GS postonng ponts are accurate. gure 3 shows a crcut trac trajectory and there s no dstnct dfference. gure 4 ndcates trajectores of a crclng date and gure 5 ndcates trajectores of turnng at an ntersecton. hese data show that the U estmates better trajectores than the E when the vehcle turns tghtly. -4-

5 gure 3. Crcut trac gure 4. Crclng gure 5. urnng at an ntersecton gure 6 shows a trajectory at a hyper slow speed, whch s lower than a creepng speed of an automatc transmsson car. And t s a dffcult stuaton for DR systems. hs data shows that the U estmates better trajectores than the E when the vehcle speed s very low. gure 6. yper slow speed -5-

6 or the demert of the U durng the analyss s the U tends to dverge on some occasons, e.g. GS sgnals were mssed. In order to deal wth ths problem, the UD factoraton algorthm s consderable le normal alman lter. CONCUSION he paper reports the effect of the Unscented alman lter that s appled to the vehcle poston estmaton, compared wth the Etended alman lter. As a result, the U s generally accurate especally tght turns but t s not stable and tends to dverge on some occasons. or further study, we wll survey the algorthms to deal wth the dvergence. And we wll evaluate the calculaton amounts n order to apply ths algorthm to embedded systems. ACNOEDGEMEN hs wor s a part of a research project "Collaboratve development of net-generaton IS sensng vehcle," by IS Center Collaboratve Research Center for advanced Moblty, Insttute of Industral Scence, he Unversty of oyo, Aero Asah Corp., Asa Ar Survey Co. td., oyota Mapmaster Inc., and DENSO COR. he authors would le to epress apprecaton to the nsttutes and the companes, especally to the members of the research project. REERENCES. Aahane, S. ataenaa, Successve Observatons of rajectores of Vehcles wth lural Vdeo Cameras, Internatonal Journal of IS Research, Vol., No., October 4. Dan Smon, Optmal State Estmaton: alman, Infnty, And Nonlnear Approaches, ley & Sons, 6, p Oguch,. Aahane, I. Nshawa and M. uwahara4.5: Development of an epermental vehcle for evaluatng hghway traffc composed of automotves wth and wthout adaptve cruse control systems. 3th ISIA 4 orld Automotve Congress Barcelona, number 4I46, p., CD-ROM. -6-

Tracking with Kalman Filter

Tracking with Kalman Filter Trackng wth Kalman Flter Scott T. Acton Vrgna Image and Vdeo Analyss (VIVA), Charles L. Brown Department of Electrcal and Computer Engneerng Department of Bomedcal Engneerng Unversty of Vrgna, Charlottesvlle,

More information

Study on Active Micro-vibration Isolation System with Linear Motor Actuator. Gong-yu PAN, Wen-yan GU and Dong LI

Study on Active Micro-vibration Isolation System with Linear Motor Actuator. Gong-yu PAN, Wen-yan GU and Dong LI 2017 2nd Internatonal Conference on Electrcal and Electroncs: echnques and Applcatons (EEA 2017) ISBN: 978-1-60595-416-5 Study on Actve Mcro-vbraton Isolaton System wth Lnear Motor Actuator Gong-yu PAN,

More information

6 Supplementary Materials

6 Supplementary Materials 6 Supplementar Materals 61 Proof of Theorem 31 Proof Let m Xt z 1:T : l m Xt X,z 1:t Wethenhave mxt z1:t ˆm HX Xt z 1:T mxt z1:t m HX Xt z 1:T + mxt z 1:T HX We consder each of the two terms n equaton

More information

Parameter Estimation for Dynamic System using Unscented Kalman filter

Parameter Estimation for Dynamic System using Unscented Kalman filter Parameter Estmaton for Dynamc System usng Unscented Kalman flter Jhoon Seung 1,a, Amr Atya F. 2,b, Alexander G.Parlos 3,c, and Klto Chong 1,4,d* 1 Dvson of Electroncs Engneerng, Chonbuk Natonal Unversty,

More information

Multiple Sound Source Location in 3D Space with a Synchronized Neural System

Multiple Sound Source Location in 3D Space with a Synchronized Neural System Multple Sound Source Locaton n D Space wth a Synchronzed Neural System Yum Takzawa and Atsush Fukasawa Insttute of Statstcal Mathematcs Research Organzaton of Informaton and Systems 0- Mdor-cho, Tachkawa,

More information

COMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD

COMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD COMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD Ákos Jósef Lengyel, István Ecsed Assstant Lecturer, Professor of Mechancs, Insttute of Appled Mechancs, Unversty of Mskolc, Mskolc-Egyetemváros,

More information

Suppose that there s a measured wndow of data fff k () ; :::; ff k g of a sze w, measured dscretely wth varable dscretzaton step. It s convenent to pl

Suppose that there s a measured wndow of data fff k () ; :::; ff k g of a sze w, measured dscretely wth varable dscretzaton step. It s convenent to pl RECURSIVE SPLINE INTERPOLATION METHOD FOR REAL TIME ENGINE CONTROL APPLICATIONS A. Stotsky Volvo Car Corporaton Engne Desgn and Development Dept. 97542, HA1N, SE- 405 31 Gothenburg Sweden. Emal: astotsky@volvocars.com

More information

SSRG International Journal of Electronics and Communication Engineering (SSRG-IJECE) Volume 2 Issue 5 May 2015

SSRG International Journal of Electronics and Communication Engineering (SSRG-IJECE) Volume 2 Issue 5 May 2015 SSRG Internatonal Journal of Electroncs and Communcaton Engneerng (SSRG-IJECE Volume 2 Issue 5 May 215 Navgatonal Error Control by Model based Flterng and Smoothng for GPS/INS Integraton Dr. S. S. Sreea

More information

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity Week3, Chapter 4 Moton n Two Dmensons Lecture Quz A partcle confned to moton along the x axs moves wth constant acceleraton from x =.0 m to x = 8.0 m durng a 1-s tme nterval. The velocty of the partcle

More information

See Book Chapter 11 2 nd Edition (Chapter 10 1 st Edition)

See Book Chapter 11 2 nd Edition (Chapter 10 1 st Edition) Count Data Models See Book Chapter 11 2 nd Edton (Chapter 10 1 st Edton) Count data consst of non-negatve nteger values Examples: number of drver route changes per week, the number of trp departure changes

More information

Adaptive RFID Indoor Positioning Technology for Wheelchair Home Health Care Robot. T. C. Kuo

Adaptive RFID Indoor Positioning Technology for Wheelchair Home Health Care Robot. T. C. Kuo Adaptve RFID Indoor Postonng Technology for Wheelchar Home Health Care Robot Contents Abstract Introducton RFID Indoor Postonng Method Fuzzy Neural Netor System Expermental Result Concluson -- Abstract

More information

Traffic Signal Timing: Basic Principles. Development of a Traffic Signal Phasing and Timing Plan. Two Phase and Three Phase Signal Operation

Traffic Signal Timing: Basic Principles. Development of a Traffic Signal Phasing and Timing Plan. Two Phase and Three Phase Signal Operation Traffc Sgnal Tmng: Basc Prncples 2 types of sgnals Pre-tmed Traffc actuated Objectves of sgnal tmng Reduce average delay of all vehcles Reduce probablty of accdents by mnmzng possble conflct ponts Objectves

More information

STUDY OF A THREE-AXIS PIEZORESISTIVE ACCELEROMETER WITH UNIFORM AXIAL SENSITIVITIES

STUDY OF A THREE-AXIS PIEZORESISTIVE ACCELEROMETER WITH UNIFORM AXIAL SENSITIVITIES STUDY OF A THREE-AXIS PIEZORESISTIVE ACCELEROMETER WITH UNIFORM AXIAL SENSITIVITIES Abdelkader Benchou, PhD Canddate Nasreddne Benmoussa, PhD Kherreddne Ghaffour, PhD Unversty of Tlemcen/Unt of Materals

More information

The Study of Teaching-learning-based Optimization Algorithm

The Study of Teaching-learning-based Optimization Algorithm Advanced Scence and Technology Letters Vol. (AST 06), pp.05- http://dx.do.org/0.57/astl.06. The Study of Teachng-learnng-based Optmzaton Algorthm u Sun, Yan fu, Lele Kong, Haolang Q,, Helongang Insttute

More information

Pulse Coded Modulation

Pulse Coded Modulation Pulse Coded Modulaton PCM (Pulse Coded Modulaton) s a voce codng technque defned by the ITU-T G.711 standard and t s used n dgtal telephony to encode the voce sgnal. The frst step n the analog to dgtal

More information

Design and Optimization of Fuzzy Controller for Inverse Pendulum System Using Genetic Algorithm

Design and Optimization of Fuzzy Controller for Inverse Pendulum System Using Genetic Algorithm Desgn and Optmzaton of Fuzzy Controller for Inverse Pendulum System Usng Genetc Algorthm H. Mehraban A. Ashoor Unversty of Tehran Unversty of Tehran h.mehraban@ece.ut.ac.r a.ashoor@ece.ut.ac.r Abstract:

More information

EE 570: Location and Navigation: Theory & Practice

EE 570: Location and Navigation: Theory & Practice EE 570: Locaton and Navgaton: Theory & Practce Navgaton Sensors and INS Mechanzaton Tuesday 26 Fe 2013 NMT EE 570: Locaton and Navgaton: Theory & Practce Slde 1 of 14 Navgaton Sensors and INS Mechanzaton

More information

A MODIFIED METHOD FOR SOLVING SYSTEM OF NONLINEAR EQUATIONS

A MODIFIED METHOD FOR SOLVING SYSTEM OF NONLINEAR EQUATIONS Journal of Mathematcs and Statstcs 9 (1): 4-8, 1 ISSN 1549-644 1 Scence Publcatons do:1.844/jmssp.1.4.8 Publshed Onlne 9 (1) 1 (http://www.thescpub.com/jmss.toc) A MODIFIED METHOD FOR SOLVING SYSTEM OF

More information

SCALARS AND VECTORS All physical quantities in engineering mechanics are measured using either scalars or vectors.

SCALARS AND VECTORS All physical quantities in engineering mechanics are measured using either scalars or vectors. SCALARS AND ECTORS All phscal uanttes n engneerng mechancs are measured usng ether scalars or vectors. Scalar. A scalar s an postve or negatve phscal uantt that can be completel specfed b ts magntude.

More information

Physics 2A Chapter 3 HW Solutions

Physics 2A Chapter 3 HW Solutions Phscs A Chapter 3 HW Solutons Chapter 3 Conceptual Queston: 4, 6, 8, Problems: 5,, 8, 7, 3, 44, 46, 69, 70, 73 Q3.4. Reason: (a) C = A+ B onl A and B are n the same drecton. Sze does not matter. (b) C

More information

Image Processing for Bubble Detection in Microfluidics

Image Processing for Bubble Detection in Microfluidics Image Processng for Bubble Detecton n Mcrofludcs Introducton Chen Fang Mechancal Engneerng Department Stanford Unverst Startng from recentl ears, mcrofludcs devces have been wdel used to buld the bomedcal

More information

11. Dynamics in Rotating Frames of Reference

11. Dynamics in Rotating Frames of Reference Unversty of Rhode Island DgtalCommons@URI Classcal Dynamcs Physcs Course Materals 2015 11. Dynamcs n Rotatng Frames of Reference Gerhard Müller Unversty of Rhode Island, gmuller@ur.edu Creatve Commons

More information

1 Derivation of Point-to-Plane Minimization

1 Derivation of Point-to-Plane Minimization 1 Dervaton of Pont-to-Plane Mnmzaton Consder the Chen-Medon (pont-to-plane) framework for ICP. Assume we have a collecton of ponts (p, q ) wth normals n. We want to determne the optmal rotaton and translaton

More information

SOC Estimation of Lithium-ion Battery Packs Based on Thevenin Model Yuanqi Fang 1,a, Ximing Cheng 1,b, and Yilin Yin 1,c. Corresponding author

SOC Estimation of Lithium-ion Battery Packs Based on Thevenin Model Yuanqi Fang 1,a, Ximing Cheng 1,b, and Yilin Yin 1,c. Corresponding author Appled Mechancs and Materals Onlne: 2013-02-13 ISSN: 1662-7482, Vol. 299, pp 211-215 do:10.4028/www.scentfc.net/amm.299.211 2013 Trans Tech Publcatons, Swtzerland SOC Estmaton of Lthum-on Battery Pacs

More information

Army Ants Tunneling for Classical Simulations

Army Ants Tunneling for Classical Simulations Electronc Supplementary Materal (ESI) for Chemcal Scence. Ths journal s The Royal Socety of Chemstry 2014 electronc supplementary nformaton (ESI) for Chemcal Scence Army Ants Tunnelng for Classcal Smulatons

More information

Improvement of Histogram Equalization for Minimum Mean Brightness Error

Improvement of Histogram Equalization for Minimum Mean Brightness Error Proceedngs of the 7 WSEAS Int. Conference on Crcuts, Systems, Sgnal and elecommuncatons, Gold Coast, Australa, January 7-9, 7 3 Improvement of Hstogram Equalzaton for Mnmum Mean Brghtness Error AAPOG PHAHUA*,

More information

MODELING TRAFFIC LIGHTS IN INTERSECTION USING PETRI NETS

MODELING TRAFFIC LIGHTS IN INTERSECTION USING PETRI NETS The 3 rd Internatonal Conference on Mathematcs and Statstcs (ICoMS-3) Insttut Pertanan Bogor, Indonesa, 5-6 August 28 MODELING TRAFFIC LIGHTS IN INTERSECTION USING PETRI NETS 1 Deky Adzkya and 2 Subono

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

arxiv:cs.cv/ Jun 2000

arxiv:cs.cv/ Jun 2000 Correlaton over Decomposed Sgnals: A Non-Lnear Approach to Fast and Effectve Sequences Comparson Lucano da Fontoura Costa arxv:cs.cv/0006040 28 Jun 2000 Cybernetc Vson Research Group IFSC Unversty of São

More information

1 GSW Iterative Techniques for y = Ax

1 GSW Iterative Techniques for y = Ax 1 for y = A I m gong to cheat here. here are a lot of teratve technques that can be used to solve the general case of a set of smultaneous equatons (wrtten n the matr form as y = A), but ths chapter sn

More information

A Particle Filter Algorithm based on Mixing of Prior probability density and UKF as Generate Importance Function

A Particle Filter Algorithm based on Mixing of Prior probability density and UKF as Generate Importance Function Advanced Scence and Technology Letters, pp.83-87 http://dx.do.org/10.14257/astl.2014.53.20 A Partcle Flter Algorthm based on Mxng of Pror probablty densty and UKF as Generate Importance Functon Lu Lu 1,1,

More information

B and H sensors for 3-D magnetic property testing

B and H sensors for 3-D magnetic property testing B and H sensors for 3-D magnetc property testng Zh We Ln, Jan Guo Zhu, You Guang Guo, Jn Jang Zhong, and Ha We Lu Faculty of Engneerng, Unversty of Technology, Sydney, PO Bo 123, Broadway, SW 2007, Australa

More information

ECG Denoising Using the Extended Kalman Filtre EKF Based on a Dynamic ECG Model

ECG Denoising Using the Extended Kalman Filtre EKF Based on a Dynamic ECG Model ECG Denosng Usng the Extended Kalman Fltre EKF Based on a Dynamc ECG Model Mohammed Assam Oual, Khereddne Chafaa Department of Electronc. Unversty of Hadj Lahdar Batna,Algera. assam_oual@yahoo.com Moufd

More information

Uncertainty in measurements of power and energy on power networks

Uncertainty in measurements of power and energy on power networks Uncertanty n measurements of power and energy on power networks E. Manov, N. Kolev Department of Measurement and Instrumentaton, Techncal Unversty Sofa, bul. Klment Ohrdsk No8, bl., 000 Sofa, Bulgara Tel./fax:

More information

Synchronized Multi-sensor Tracks Association and Fusion

Synchronized Multi-sensor Tracks Association and Fusion Synchronzed Mult-sensor Tracks Assocaton and Fuson Dongguang Zuo Chongzhao an School of Electronc and nformaton Engneerng X an Jaotong Unversty Xan 749, P.R. Chna Zlz_3@sna.com.cn czhan@jtu.edu.cn Abstract

More information

DETERMINATION OF UNCERTAINTY ASSOCIATED WITH QUANTIZATION ERRORS USING THE BAYESIAN APPROACH

DETERMINATION OF UNCERTAINTY ASSOCIATED WITH QUANTIZATION ERRORS USING THE BAYESIAN APPROACH Proceedngs, XVII IMEKO World Congress, June 7, 3, Dubrovn, Croata Proceedngs, XVII IMEKO World Congress, June 7, 3, Dubrovn, Croata TC XVII IMEKO World Congress Metrology n the 3rd Mllennum June 7, 3,

More information

where v means the change in velocity, and t is the

where v means the change in velocity, and t is the 1 PHYS:100 LECTURE 4 MECHANICS (3) Ths lecture covers the eneral case of moton wth constant acceleraton and free fall (whch s one of the more mportant examples of moton wth constant acceleraton) n a more

More information

RBF Neural Network Model Training by Unscented Kalman Filter and Its Application in Mechanical Fault Diagnosis

RBF Neural Network Model Training by Unscented Kalman Filter and Its Application in Mechanical Fault Diagnosis Appled Mechancs and Materals Submtted: 24-6-2 ISSN: 662-7482, Vols. 62-65, pp 2383-2386 Accepted: 24-6- do:.428/www.scentfc.net/amm.62-65.2383 Onlne: 24-8- 24 rans ech Publcatons, Swtzerland RBF Neural

More information

5th International Conference on Measurement, Instrumentation and Automation (ICMIA 2016) Star image identification uninfluenced by rotation

5th International Conference on Measurement, Instrumentation and Automation (ICMIA 2016) Star image identification uninfluenced by rotation 5th Internatonal Conference on Measurement, Instrumentaton and Automaton (ICMIA 2016) Star mage dentfcaton unnfluenced by rotaton Jang D1,a, Zhang Ke1, Lv Mebo1 1 Nortwestern Polytechncal Unversty, X an,

More information

Lab 2e Thermal System Response and Effective Heat Transfer Coefficient

Lab 2e Thermal System Response and Effective Heat Transfer Coefficient 58:080 Expermental Engneerng 1 OBJECTIVE Lab 2e Thermal System Response and Effectve Heat Transfer Coeffcent Warnng: though the experment has educatonal objectves (to learn about bolng heat transfer, etc.),

More information

Polynomial Regression Models

Polynomial Regression Models LINEAR REGRESSION ANALYSIS MODULE XII Lecture - 6 Polynomal Regresson Models Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur Test of sgnfcance To test the sgnfcance

More information

Finite Element Modelling of truss/cable structures

Finite Element Modelling of truss/cable structures Pet Schreurs Endhoven Unversty of echnology Department of Mechancal Engneerng Materals echnology November 3, 214 Fnte Element Modellng of truss/cable structures 1 Fnte Element Analyss of prestressed structures

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

Physics 5153 Classical Mechanics. Principle of Virtual Work-1

Physics 5153 Classical Mechanics. Principle of Virtual Work-1 P. Guterrez 1 Introducton Physcs 5153 Classcal Mechancs Prncple of Vrtual Work The frst varatonal prncple we encounter n mechancs s the prncple of vrtual work. It establshes the equlbrum condton of a mechancal

More information

Real-Time Systems. Multiprocessor scheduling. Multiprocessor scheduling. Multiprocessor scheduling

Real-Time Systems. Multiprocessor scheduling. Multiprocessor scheduling. Multiprocessor scheduling Real-Tme Systems Multprocessor schedulng Specfcaton Implementaton Verfcaton Multprocessor schedulng -- -- Global schedulng How are tasks assgned to processors? Statc assgnment The processor(s) used for

More information

ONE DIMENSIONAL TRIANGULAR FIN EXPERIMENT. Technical Advisor: Dr. D.C. Look, Jr. Version: 11/03/00

ONE DIMENSIONAL TRIANGULAR FIN EXPERIMENT. Technical Advisor: Dr. D.C. Look, Jr. Version: 11/03/00 ONE IMENSIONAL TRIANGULAR FIN EXPERIMENT Techncal Advsor: r..c. Look, Jr. Verson: /3/ 7. GENERAL OJECTIVES a) To understand a one-dmensonal epermental appromaton. b) To understand the art of epermental

More information

STATS 306B: Unsupervised Learning Spring Lecture 10 April 30

STATS 306B: Unsupervised Learning Spring Lecture 10 April 30 STATS 306B: Unsupervsed Learnng Sprng 2014 Lecture 10 Aprl 30 Lecturer: Lester Mackey Scrbe: Joey Arthur, Rakesh Achanta 10.1 Factor Analyss 10.1.1 Recap Recall the factor analyss (FA) model for lnear

More information

The Synchronous 8th-Order Differential Attack on 12 Rounds of the Block Cipher HyRAL

The Synchronous 8th-Order Differential Attack on 12 Rounds of the Block Cipher HyRAL The Synchronous 8th-Order Dfferental Attack on 12 Rounds of the Block Cpher HyRAL Yasutaka Igarash, Sej Fukushma, and Tomohro Hachno Kagoshma Unversty, Kagoshma, Japan Emal: {garash, fukushma, hachno}@eee.kagoshma-u.ac.jp

More information

An Algorithm to Solve the Inverse Kinematics Problem of a Robotic Manipulator Based on Rotation Vectors

An Algorithm to Solve the Inverse Kinematics Problem of a Robotic Manipulator Based on Rotation Vectors An Algorthm to Solve the Inverse Knematcs Problem of a Robotc Manpulator Based on Rotaton Vectors Mohamad Z. Al-az*, Mazn Z. Othman**, and Baker B. Al-Bahr* *AL-Nahran Unversty, Computer Eng. Dep., Baghdad,

More information

509. Dependence between stiffness of fixed foundation and blower supports

509. Dependence between stiffness of fixed foundation and blower supports 509. Dependence between stffness of fxed foundaton and blower supports P. Mažeka 1,a, J. Grgonen 1,b, A. Senuls 1,c 1 Klapeda Unversty, Bjunu str. 17, Klapeda LT-91225, Lthuana E-mal: a b pranasmazeka@centras.lt

More information

Week 9 Chapter 10 Section 1-5

Week 9 Chapter 10 Section 1-5 Week 9 Chapter 10 Secton 1-5 Rotaton Rgd Object A rgd object s one that s nondeformable The relatve locatons of all partcles makng up the object reman constant All real objects are deformable to some extent,

More information

CS 468 Lecture 16: Isometry Invariance and Spectral Techniques

CS 468 Lecture 16: Isometry Invariance and Spectral Techniques CS 468 Lecture 16: Isometry Invarance and Spectral Technques Justn Solomon Scrbe: Evan Gawlk Introducton. In geometry processng, t s often desrable to characterze the shape of an object n a manner that

More information

Automatic Object Trajectory- Based Motion Recognition Using Gaussian Mixture Models

Automatic Object Trajectory- Based Motion Recognition Using Gaussian Mixture Models Automatc Object Trajectory- Based Moton Recognton Usng Gaussan Mxture Models Fasal I. Bashr, Ashfaq A. Khokhar, Dan Schonfeld Electrcal and Computer Engneerng, Unversty of Illnos at Chcago. Chcago, IL,

More information

CIS526: Machine Learning Lecture 3 (Sept 16, 2003) Linear Regression. Preparation help: Xiaoying Huang. x 1 θ 1 output... θ M x M

CIS526: Machine Learning Lecture 3 (Sept 16, 2003) Linear Regression. Preparation help: Xiaoying Huang. x 1 θ 1 output... θ M x M CIS56: achne Learnng Lecture 3 (Sept 6, 003) Preparaton help: Xaoyng Huang Lnear Regresson Lnear regresson can be represented by a functonal form: f(; θ) = θ 0 0 +θ + + θ = θ = 0 ote: 0 s a dummy attrbute

More information

Supplemental Instruction sessions next week

Supplemental Instruction sessions next week Homework #4 Wrtten homework due now Onlne homework due on Tue Mar 3 by 8 am Exam 1 Answer keys and scores wll be posted by end of the week Supplemental Instructon sessons next week Wednesday 8:45 10:00

More information

Problem Points Score Total 100

Problem Points Score Total 100 Physcs 450 Solutons of Sample Exam I Problem Ponts Score 1 8 15 3 17 4 0 5 0 Total 100 All wor must be shown n order to receve full credt. Wor must be legble and comprehensble wth answers clearly ndcated.

More information

A Robust Method for Calculating the Correlation Coefficient

A Robust Method for Calculating the Correlation Coefficient A Robust Method for Calculatng the Correlaton Coeffcent E.B. Nven and C. V. Deutsch Relatonshps between prmary and secondary data are frequently quantfed usng the correlaton coeffcent; however, the tradtonal

More information

Rigid body simulation

Rigid body simulation Rgd bod smulaton Rgd bod smulaton Once we consder an object wth spacal etent, partcle sstem smulaton s no longer suffcent Problems Problems Unconstraned sstem rotatonal moton torques and angular momentum

More information

Composite Hypotheses testing

Composite Hypotheses testing Composte ypotheses testng In many hypothess testng problems there are many possble dstrbutons that can occur under each of the hypotheses. The output of the source s a set of parameters (ponts n a parameter

More information

Conservation of Angular Momentum = "Spin"

Conservation of Angular Momentum = Spin Page 1 of 6 Conservaton of Angular Momentum = "Spn" We can assgn a drecton to the angular velocty: drecton of = drecton of axs + rght hand rule (wth rght hand, curl fngers n drecton of rotaton, thumb ponts

More information

EN40: Dynamics and Vibrations. Homework 4: Work, Energy and Linear Momentum Due Friday March 1 st

EN40: Dynamics and Vibrations. Homework 4: Work, Energy and Linear Momentum Due Friday March 1 st EN40: Dynamcs and bratons Homework 4: Work, Energy and Lnear Momentum Due Frday March 1 st School of Engneerng Brown Unversty 1. The fgure (from ths publcaton) shows the energy per unt area requred to

More information

Three views of mechanics

Three views of mechanics Three vews of mechancs John Hubbard, n L. Gross s course February 1, 211 1 Introducton A mechancal system s manfold wth a Remannan metrc K : T M R called knetc energy and a functon V : M R called potental

More information

Identification of Instantaneous Modal Parameters of A Nonlinear Structure Via Amplitude-Dependent ARX Model

Identification of Instantaneous Modal Parameters of A Nonlinear Structure Via Amplitude-Dependent ARX Model Identfcaton of Instantaneous Modal Parameters of A Nonlnear Structure Va Ampltude-Dependent ARX Model We Chh Su(NCHC), Chung Shann Huang(NCU), Chng Yu Lu(NCU) Outlne INRODUCION MEHODOLOGY NUMERICAL VERIFICAION

More information

A Multi-Axis Force Measurement System for a Space Docking Mechanism

A Multi-Axis Force Measurement System for a Space Docking Mechanism 3rd Internatonal Conference on Materal, Mechancal and Manufacturng Engneerng (IC3ME 215) A Mult-Axs orce Measurement System for a Space Dockng Mechansm Gangfeng Lu a*, Changle L b and Zenghu Xe c Buldng

More information

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system Transfer Functons Convenent representaton of a lnear, dynamc model. A transfer functon (TF) relates one nput and one output: x t X s y t system Y s The followng termnology s used: x y nput output forcng

More information

De-noising Method Based on Kernel Adaptive Filtering for Telemetry Vibration Signal of the Vehicle Test Kejun ZENG

De-noising Method Based on Kernel Adaptive Filtering for Telemetry Vibration Signal of the Vehicle Test Kejun ZENG 6th Internatonal Conference on Mechatroncs, Materals, Botechnology and Envronment (ICMMBE 6) De-nosng Method Based on Kernel Adaptve Flterng for elemetry Vbraton Sgnal of the Vehcle est Kejun ZEG PLA 955

More information

AN IMPROVED PARTICLE FILTER ALGORITHM BASED ON NEURAL NETWORK FOR TARGET TRACKING

AN IMPROVED PARTICLE FILTER ALGORITHM BASED ON NEURAL NETWORK FOR TARGET TRACKING AN IMPROVED PARTICLE FILTER ALGORITHM BASED ON NEURAL NETWORK FOR TARGET TRACKING Qn Wen, Peng Qcong 40 Lab, Insttuton of Communcaton and Informaton Engneerng,Unversty of Electronc Scence and Technology

More information

Numerical Heat and Mass Transfer

Numerical Heat and Mass Transfer Master degree n Mechancal Engneerng Numercal Heat and Mass Transfer 06-Fnte-Dfference Method (One-dmensonal, steady state heat conducton) Fausto Arpno f.arpno@uncas.t Introducton Why we use models and

More information

DO NOT DO HOMEWORK UNTIL IT IS ASSIGNED. THE ASSIGNMENTS MAY CHANGE UNTIL ANNOUNCED.

DO NOT DO HOMEWORK UNTIL IT IS ASSIGNED. THE ASSIGNMENTS MAY CHANGE UNTIL ANNOUNCED. EE 539 Homeworks Sprng 08 Updated: Tuesday, Aprl 7, 08 DO NOT DO HOMEWORK UNTIL IT IS ASSIGNED. THE ASSIGNMENTS MAY CHANGE UNTIL ANNOUNCED. For full credt, show all work. Some problems requre hand calculatons.

More information

Chapter 8. Potential Energy and Conservation of Energy

Chapter 8. Potential Energy and Conservation of Energy Chapter 8 Potental Energy and Conservaton of Energy In ths chapter we wll ntroduce the followng concepts: Potental Energy Conservatve and non-conservatve forces Mechancal Energy Conservaton of Mechancal

More information

AP Physics 1 & 2 Summer Assignment

AP Physics 1 & 2 Summer Assignment AP Physcs 1 & 2 Summer Assgnment AP Physcs 1 requres an exceptonal profcency n algebra, trgonometry, and geometry. It was desgned by a select group of college professors and hgh school scence teachers

More information

Parking Demand Forecasting in Airport Ground Transportation System: Case Study in Hongqiao Airport

Parking Demand Forecasting in Airport Ground Transportation System: Case Study in Hongqiao Airport Internatonal Symposum on Computers & Informatcs (ISCI 25) Parkng Demand Forecastng n Arport Ground Transportaton System: Case Study n Hongqao Arport Ln Chang, a, L Wefeng, b*, Huanh Yan 2, c, Yang Ge,

More information

Chapter 3. r r. Position, Velocity, and Acceleration Revisited

Chapter 3. r r. Position, Velocity, and Acceleration Revisited Chapter 3 Poston, Velocty, and Acceleraton Revsted The poston vector of a partcle s a vector drawn from the orgn to the locaton of the partcle. In two dmensons: r = x ˆ+ yj ˆ (1) The dsplacement vector

More information

Indeterminate pin-jointed frames (trusses)

Indeterminate pin-jointed frames (trusses) Indetermnate pn-jonted frames (trusses) Calculaton of member forces usng force method I. Statcal determnacy. The degree of freedom of any truss can be derved as: w= k d a =, where k s the number of all

More information

Short Term Load Forecasting using an Artificial Neural Network

Short Term Load Forecasting using an Artificial Neural Network Short Term Load Forecastng usng an Artfcal Neural Network D. Kown 1, M. Km 1, C. Hong 1,, S. Cho 2 1 Department of Computer Scence, Sangmyung Unversty, Seoul, Korea 2 Department of Energy Grd, Sangmyung

More information

Physics 111: Mechanics Lecture 11

Physics 111: Mechanics Lecture 11 Physcs 111: Mechancs Lecture 11 Bn Chen NJIT Physcs Department Textbook Chapter 10: Dynamcs of Rotatonal Moton q 10.1 Torque q 10. Torque and Angular Acceleraton for a Rgd Body q 10.3 Rgd-Body Rotaton

More information

Microwave Diversity Imaging Compression Using Bioinspired

Microwave Diversity Imaging Compression Using Bioinspired Mcrowave Dversty Imagng Compresson Usng Bonspred Neural Networks Youwe Yuan 1, Yong L 1, Wele Xu 1, Janghong Yu * 1 School of Computer Scence and Technology, Hangzhou Danz Unversty, Hangzhou, Zhejang,

More information

Over-Temperature protection for IGBT modules

Over-Temperature protection for IGBT modules Over-Temperature protecton for IGBT modules Ke Wang 1, Yongjun Lao 2, Gaosheng Song 1, Xanku Ma 1 1 Mtsubsh Electrc & Electroncs (Shangha) Co., Ltd., Chna Room2202, Tower 3, Kerry Plaza, No.1-1 Zhongxns

More information

EN40: Dynamics and Vibrations. Homework 7: Rigid Body Kinematics

EN40: Dynamics and Vibrations. Homework 7: Rigid Body Kinematics N40: ynamcs and Vbratons Homewor 7: Rgd Body Knematcs School of ngneerng Brown Unversty 1. In the fgure below, bar AB rotates counterclocwse at 4 rad/s. What are the angular veloctes of bars BC and C?.

More information

Statistical Energy Analysis for High Frequency Acoustic Analysis with LS-DYNA

Statistical Energy Analysis for High Frequency Acoustic Analysis with LS-DYNA 14 th Internatonal Users Conference Sesson: ALE-FSI Statstcal Energy Analyss for Hgh Frequency Acoustc Analyss wth Zhe Cu 1, Yun Huang 1, Mhamed Soul 2, Tayeb Zeguar 3 1 Lvermore Software Technology Corporaton

More information

Global Sensitivity. Tuesday 20 th February, 2018

Global Sensitivity. Tuesday 20 th February, 2018 Global Senstvty Tuesday 2 th February, 28 ) Local Senstvty Most senstvty analyses [] are based on local estmates of senstvty, typcally by expandng the response n a Taylor seres about some specfc values

More information

Invariant deformation parameters from GPS permanent networks using stochastic interpolation

Invariant deformation parameters from GPS permanent networks using stochastic interpolation Invarant deformaton parameters from GPS permanent networks usng stochastc nterpolaton Ludovco Bag, Poltecnco d Mlano, DIIAR Athanasos Dermans, Arstotle Unversty of Thessalonk Outlne Startng hypotheses

More information

Week 11: Chapter 11. The Vector Product. The Vector Product Defined. The Vector Product and Torque. More About the Vector Product

Week 11: Chapter 11. The Vector Product. The Vector Product Defined. The Vector Product and Torque. More About the Vector Product The Vector Product Week 11: Chapter 11 Angular Momentum There are nstances where the product of two vectors s another vector Earler we saw where the product of two vectors was a scalar Ths was called the

More information

5.62 Physical Chemistry II Spring 2008

5.62 Physical Chemistry II Spring 2008 MIT OpenCourseWare http://ocw.mt.edu 5.62 Physcal Chemstry II Sprng 2008 For nformaton about ctng these materals or our Terms of Use, vst: http://ocw.mt.edu/terms. 5.62 Sprng 2008 Lecture 34 Page Transton

More information

χ x B E (c) Figure 2.1.1: (a) a material particle in a body, (b) a place in space, (c) a configuration of the body

χ x B E (c) Figure 2.1.1: (a) a material particle in a body, (b) a place in space, (c) a configuration of the body Secton.. Moton.. The Materal Body and Moton hyscal materals n the real world are modeled usng an abstract mathematcal entty called a body. Ths body conssts of an nfnte number of materal partcles. Shown

More information

MATH 829: Introduction to Data Mining and Analysis The EM algorithm (part 2)

MATH 829: Introduction to Data Mining and Analysis The EM algorithm (part 2) 1/16 MATH 829: Introducton to Data Mnng and Analyss The EM algorthm (part 2) Domnque Gullot Departments of Mathematcal Scences Unversty of Delaware Aprl 20, 2016 Recall 2/16 We are gven ndependent observatons

More information

Unscented Particle Filtering Algorithm for Optical-Fiber Sensing Intrusion Localization Based on Particle Swarm Optimization

Unscented Particle Filtering Algorithm for Optical-Fiber Sensing Intrusion Localization Based on Particle Swarm Optimization TELKOMNIKA, Vol13, No1, March 015, pp 349~356 ISSN: 1693-6930, accredted A by DIKTI, Decree No: 58/DIKTI/Kep/013 DOI: 10198/TELKOMNIKAv13117 349 Unscented Partcle Flterng Algorthm for Optcal-Fber Sensng

More information

Spin-rotation coupling of the angularly accelerated rigid body

Spin-rotation coupling of the angularly accelerated rigid body Spn-rotaton couplng of the angularly accelerated rgd body Loua Hassan Elzen Basher Khartoum, Sudan. Postal code:11123 E-mal: louaelzen@gmal.com November 1, 2017 All Rghts Reserved. Abstract Ths paper s

More information

Kinematics in 2-Dimensions. Projectile Motion

Kinematics in 2-Dimensions. Projectile Motion Knematcs n -Dmensons Projectle Moton A medeval trebuchet b Kolderer, c1507 http://members.net.net.au/~rmne/ht/ht0.html#5 Readng Assgnment: Chapter 4, Sectons -6 Introducton: In medeval das, people had

More information

Research on the Fuzzy Control for Vehicle Semi-active Suspension. Xiaoming Hu 1, a, Wanli Li 1,b

Research on the Fuzzy Control for Vehicle Semi-active Suspension. Xiaoming Hu 1, a, Wanli Li 1,b Advanced Materals Research Onlne: 0-0- ISSN: -9, Vol., pp -9 do:0.0/www.scentfc.net/amr.. 0 Trans Tech Publcatons, Swterland Research on the Fuy Control for Vehcle Sem-actve Suspenson Xaomng Hu, a, Wanl

More information

APPLICATION OF EDDY CURRENT PRINCIPLES FOR MEASUREMENT OF TUBE CENTERLINE

APPLICATION OF EDDY CURRENT PRINCIPLES FOR MEASUREMENT OF TUBE CENTERLINE APPLICATION OF EDDY CURRENT PRINCIPLES FOR MEASUREMENT OF TUBE CENTERLINE DEFLECTION E. J. Chern Martn Maretta Laboratores 1450 South Rollng Road Baltmore, MD 21227 INTRODUCTION Tubes are a vtal component

More information

Physics 141. Lecture 14. Frank L. H. Wolfs Department of Physics and Astronomy, University of Rochester, Lecture 14, Page 1

Physics 141. Lecture 14. Frank L. H. Wolfs Department of Physics and Astronomy, University of Rochester, Lecture 14, Page 1 Physcs 141. Lecture 14. Frank L. H. Wolfs Department of Physcs and Astronomy, Unversty of Rochester, Lecture 14, Page 1 Physcs 141. Lecture 14. Course Informaton: Lab report # 3. Exam # 2. Mult-Partcle

More information

Module 11 Design of Joints for Special Loading. Version 2 ME, IIT Kharagpur

Module 11 Design of Joints for Special Loading. Version 2 ME, IIT Kharagpur Module 11 Desgn o Jonts or Specal Loadng Verson ME, IIT Kharagpur Lesson 1 Desgn o Eccentrcally Loaded Bolted/Rveted Jonts Verson ME, IIT Kharagpur Instructonal Objectves: At the end o ths lesson, the

More information

Nodal analysis of finite square resistive grids and the teaching effectiveness of students projects

Nodal analysis of finite square resistive grids and the teaching effectiveness of students projects 2 nd World Conference on Technology and Engneerng Educaton 2 WIETE Lublana Slovena 5-8 September 2 Nodal analyss of fnte square resstve grds and the teachng effectveness of students proects P. Zegarmstrz

More information

Study on Non-Linear Dynamic Characteristic of Vehicle. Suspension Rubber Component

Study on Non-Linear Dynamic Characteristic of Vehicle. Suspension Rubber Component Study on Non-Lnear Dynamc Characterstc of Vehcle Suspenson Rubber Component Zhan Wenzhang Ln Y Sh GuobaoJln Unversty of TechnologyChangchun, Chna Wang Lgong (MDI, Chna [Abstract] The dynamc characterstc

More information

ENGN 40 Dynamics and Vibrations Homework # 7 Due: Friday, April 15

ENGN 40 Dynamics and Vibrations Homework # 7 Due: Friday, April 15 NGN 40 ynamcs and Vbratons Homework # 7 ue: Frday, Aprl 15 1. Consder a concal hostng drum used n the mnng ndustry to host a mass up/down. A cable of dameter d has the mass connected at one end and s wound/unwound

More information

Robert Eisberg Second edition CH 09 Multielectron atoms ground states and x-ray excitations

Robert Eisberg Second edition CH 09 Multielectron atoms ground states and x-ray excitations Quantum Physcs 量 理 Robert Esberg Second edton CH 09 Multelectron atoms ground states and x-ray exctatons 9-01 By gong through the procedure ndcated n the text, develop the tme-ndependent Schroednger equaton

More information

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity LINEAR REGRESSION ANALYSIS MODULE IX Lecture - 31 Multcollnearty Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur 6. Rdge regresson The OLSE s the best lnear unbased

More information

STAT 511 FINAL EXAM NAME Spring 2001

STAT 511 FINAL EXAM NAME Spring 2001 STAT 5 FINAL EXAM NAME Sprng Instructons: Ths s a closed book exam. No notes or books are allowed. ou may use a calculator but you are not allowed to store notes or formulas n the calculator. Please wrte

More information

Prediction of Driving Behavior through Probabilistic Inference

Prediction of Driving Behavior through Probabilistic Inference Held n Torremolnos, Malaga (SPAIN) 8-10 September 2003 Predcton of Drvng Behavor through Probablstc Inference Toru Kumaga*, Yasuo Sakaguch**, Masayuk Okuwa*** and Motoyuk Akamatsu* *Natonal Insttute of

More information