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Moradei$d[1970?] 215 $a221 p.$cill.$d29 cm 225 1 $aBiblioteca tecnica 454 0$12001$aEmploi rationnel des transistors$930504 610 0 $aTransistori 676 $a621.381 700 1$aOehmichen,$bJean Pierre$0505003 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990008820890403321 952 $a13 F 77 20$b16084$fFINBC 959 $aFINBC 996 $aEmploi rationnel des transistors$930504 997 $aUNINA LEADER 05565nam 2200697 a 450 001 9910828876303321 005 20240313135945.0 010 $a1-118-57898-8 010 $a1-118-57899-6 010 $a1-299-18669-6 010 $a1-118-57900-3 035 $a(CKB)2670000000327569 035 $a(EBL)1120445 035 $a(OCoLC)827207821 035 $a(SSID)ssj0000855371 035 $a(PQKBManifestationID)11470367 035 $a(PQKBTitleCode)TC0000855371 035 $a(PQKBWorkID)10912973 035 $a(PQKB)10040226 035 $a(MiAaPQ)EBC1120445 035 $a(Au-PeEL)EBL1120445 035 $a(CaPaEBR)ebr10657663 035 $a(CaONFJC)MIL449919 035 $a(PPN)270829768 035 $a(EXLCZ)992670000000327569 100 $a20120913d2013 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 00$aVehicle dynamics estimation using Kalman filtering $eexperimental validation /$fMoustapha Doumiati ... [et al.] ; series editor, Bernard Dubuisson 205 $a1st ed. 210 $aLondon $cISTE ;$aHoboken, N.J. $cJohn Wiley and Sons Inc$d2013 215 $a1 online resource (263 p.) 225 0 $aAutomation - control and industrial engineering series 300 $aDescription based upon print version of record. 311 $a1-84821-366-2 320 $aIncludes bibliographical references and index. 327 $aTitle Page; Contents; Preface; Introduction; I.1. Needs of ADAS systems; I.2. Limitation of available ADAS systems; I.3. This book versus existing studies; I.4. Laboratory vehicle; I.5. Outline; Chapter 1. Modeling of Tire and Vehicle Dynamics; 1.1. Introduction; 1.2. Tire dynamics; 1.2.1. Tire forces and moments; 1.2.1.1. Vertical/normal forces; 1.2.1.2. Longitudinal forces and longitudinal slip ratio; 1.2.1.3. Lateral forces and sideslip angle; 1.2.1.4. Aligning moment; 1.2.1.5. Coupling effects between longitudinal and lateral tire forces; 1.2.2. Tire-road friction coefficient 327 $a1.2.2.1. Normalized longitudinal traction force 1.2.2.2. Normalized lateral traction force; 1.2.3. Quasi-static tire model; 1.2.3.1. Pacejka's magic tire model; 1.2.3.2. Dugoff's tire model; 1.2.3.3. Linear model; 1.2.4. Transient tire model; 1.3. Wheel rotational dynamics; 1.3.1. Static tire radius; 1.3.2. Effective tire radius; 1.4. Vehicle body dynamics; 1.4.1. Vehicle's vertical dynamics; 1.4.1.1. Suspension functions; 1.4.1.2. Quarter-car vehicle model; 1.4.2. Vehicle planar dynamics; 1.4.2.1. Four-wheel vehicle model; 1.4.2.2. Wheel-ground vertical forces calculation 327 $a1.4.2.3. Bicycle model 1.4.3. Roll dynamics and lateral load transfer evaluation; 1.5. Summary; Chapter 2. Estimation Methods Based on Kalman Filtering; 2.1. Introduction; 2.2. State-space representation and system observability; 2.2.1. Linear system; 2.2.2. Nonlinear system; 2.3. Estimation method: why stochastic models?; 2.3.1. Closed-loop observer; 2.3.2. Choice of the observer type; 2.4. The linear Kalman filter; 2.5. Extension to the nonlinear case; 2.6. The unscented Kalman filter; 2.6.1. Unscented transformation; 2.6.2. UKF algorithm 327 $a2.7. Illustration of a linear Kalman filter application: road profile estimation 2.7.1. Motivation; 2.7.2. Observer design; 2.7.3. Experimental results: observer evaluation; 2.7.3.1. Comparison with LPA signal; 2.7.3.2. Comparison with GMP signal; 2.8. Summary; Chapter 3. Estimation of the Vertical Tire Forces; 3.1. Introduction; 3.1.1. Related works; 3.2. Algorithm description; 3.3. Techniques for lateral load transfer calculation in an open-loop scheme; 3.3.1. Lateral acceleration calculation; 3.3.2. Roll angle calculation; 3.3.3. Limitation of the open-loop model 327 $a3.4. Observer design for vertical forces estimation 3.5. Vertical forces estimation; 3.5.1. Observer OFzE design; 3.5.2. Observer OFzL formulation; 3.6. Analysis concerning the two-part estimation strategy; 3.7. Models observability analysis; 3.8. Determining the vehicle's mass; 3.8.1. Experimental validation of the vehicle's weight identification method; 3.9. Detection of rollover avoidance: LTR evaluation; 3.10. Experimental validation; 3.10.1. Regulation of observers; 3.10.2. Evaluation of observers; 3.10.3. Road experimental results; 3.10.3.1. Starting-slalom-braking test 327 $a3.10.3.2. Circle-braking test 330 $aVehicle dynamics and stability have been of considerable interest for a number of years. The obvious dilemma is that people naturally desire to drive faster and faster yet expect their vehicles to be "infinitely" stable and safe during all normal and emergency maneuvers. For the most part, people pay little attention to the limited handling potential of their vehicles until some unusual behavior is observed that often results in accidents and even fatalities.This book presents several model-based estimation methods which involve information from current potential-integrable sensors. 410 0$aAutomation-control and industrial engineering series 606 $aMotor vehicles$xDynamics 606 $aKalman filtering 615 0$aMotor vehicles$xDynamics. 615 0$aKalman filtering. 676 $a629.8312 701 $aDoumiati$b Moustapha$01639342 701 $aDubuisson$b Bernard$0741319 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910828876303321 996 $aVehicle dynamics estimation using Kalman filtering$93982254 997 $aUNINA LEADER 03048nam 2200781z- 450 001 9910404092303321 005 20210212 010 $a3-03928-573-4 035 $a(CKB)4100000011302215 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/59238 035 $a(oapen)doab59238 035 $a(EXLCZ)994100000011302215 100 $a20202102d2020 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aSentiment Analysis for Social Media 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2020 215 $a1 online resource (152 p.) 311 08$a3-03928-572-6 330 $aSentiment analysis is a branch of natural language processing concerned with the study of the intensity of the emotions expressed in a piece of text. The automated analysis of the multitude of messages delivered through social media is one of the hottest research fields, both in academy and in industry, due to its extremely high potential applicability in many different domains. 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