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[null,"1.","Record Nr.",null,"UNINA9910828876303321"]
[null,null,"Titolo",null,"Vehicle dynamics estimation using Kalman filtering : experimental validation / / Moustapha Doumiati ... [et al.] ; series editor, Bernard Dubuisson"]
[null,null,"Pubbl/distr/stampa",null,"London, : ISTE"]
[{"$nulls":4},"Hoboken, N.J., : John Wiley and Sons Inc, 2013"]
[null,null,"ISBN",null,"1-118-57898-8"]
[{"$nulls":4},"1-118-57899-6"]
[{"$nulls":4},"1-299-18669-6"]
[{"$nulls":4},"1-118-57900-3"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (263 p.)"]
[null,null,"Collana",null,"Automation - control and industrial engineering series"]
[null,null,"Disciplina",null,"629.8312"]
[null,null,"Soggetti",null,"Motor vehicles - Dynamics"]
[{"$nulls":4},"Kalman filtering"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Title Page; Contents; Preface; Introduction; I.1. Needs of ADAS systems; I.2. Limitation of available ADAS systems; I.3. This book versus existing studies; I.4. Laboratory vehicle; I.5. Outline; Chapter 1. Modeling of Tire and Vehicle Dynamics; 1.1. Introduction; 1.2. Tire dynamics; 1.2.1. Tire forces and moments; 1.2.1.1. Vertical/normal forces; 1.2.1.2. Longitudinal forces and longitudinal slip ratio; 1.2.1.3. Lateral forces and sideslip angle; 1.2.1.4. Aligning moment; 1.2.1.5. Coupling effects between longitudinal and lateral tire forces; 1.2.2. Tire-road friction coefficient"]
[{"$nulls":4},"1.2.2.1. 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"]
[{"$nulls":4},"1.4.2.3. Bicycle model 1.4.3. Roll dynamics and lateral load transfer evaluation; 1.5. Summary; Chapter 2. Estimation Methods Based on "]
[{"$nulls":4},"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"]
[{"$nulls":4},"2.7. Illustration of a linear Kalman filter application: road profile estimation 2.7.1. Motivation; 2.7.2. Observer design; 2.7.3. Experimental results: observer evaluation; 2.7.3.1. Comparison with LPA signal; 2.7.3.2. Comparison with GMP signal; 2.8. Summary; Chapter 3. Estimation of the Vertical Tire Forces; 3.1. Introduction; 3.1.1. Related works; 3.2. Algorithm description; 3.3. Techniques for lateral load transfer calculation in an open-loop scheme; 3.3.1. Lateral acceleration calculation; 3.3.2. Roll angle calculation; 3.3.3. Limitation of the open-loop model"]
[{"$nulls":4},"3.4. 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"]
[{"$nulls":4},"3.10.3.2. Circle-braking test"]
[null,null,null,"Sommario/riassunto","Vehicle 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."]
[null,"2.","Record Nr.",null,"UNINA9910404092303321"]
[null,null,"Autore",null,"Moreno Antonio"]
[null,null,"Titolo",null,"Sentiment Analysis for Social Media"]
[null,null,"Pubbl/distr/stampa",null,"MDPI - Multidisciplinary Digital Publishing Institute, 2020"]
[null,null,"ISBN",null,"3-03928-573-4"]
[null,null,"Descrizione fisica",null,"1 online resource (152 p.)"]
[null,null,"Soggetti",null,"History of engineering and technology"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","Sentiment 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. This Special Issue describes both technological contributions to the field, mostly based on deep learning techniques, and specific applications in areas like health insurance, gender classification, recommender systems, and cyber aggression detection."]