LEADER 01102nam0 2200265 450 001 000005736 005 20060130112329.0 010 $a88-88877-59-2 100 $a20050222d2003----km-y0itay50------ba 101 0 $aita 102 $aIT 200 1 $aInformativa aziendale e innovazione tecnologica. Profili di valutazione, controllo e comunicazione esterna della performance innovativa$fRiccardo Tiscini 205 $aCollana di Studi economico-aziendali 210 $aMilano$cGiuffrè$aRoma$cLuiss University Press$d2003 215 $aXI, 445 p.$d24 cm 225 2 $aCollana di Studi economico-aziendali$iNuova serie$fLuiss Libera Università Internazionale degli Studi sociali Guido Carli$v0026 410 0$12001$aCollana di Studi economico-aziendali. Nuova serie 610 1 $aAziende$aInnovazione tecnologica$aGestione 676 $a658.514 700 1$aTiscini,$bRiccardo$0382712 801 0$aIT$bUNIPARTHENOPE$c20050222$gRICA$2UNIMARC 912 $a000005736 951 $a658-I/41$b37565$cNAVA1$d20050222 996 $aInformativa aziendale e innovazione tecnologica$9260260 997 $aUNIPARTHENOPE LEADER 03338nam 22006855 450 001 9910544848203321 005 20250218004156.0 010 $a9783030907730 010 $a3030907732 024 7 $a10.1007/978-3-030-90773-0 035 $a(MiAaPQ)EBC6882522 035 $a(Au-PeEL)EBL6882522 035 $a(CKB)21069305100041 035 $a(PPN)260828149 035 $a(DE-He213)978-3-030-90773-0 035 $a(EXLCZ)9921069305100041 100 $a20220205d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAnalysis and Synthesis of Nonlinear Control Systems $eA Convex Optimisation Approach /$fby Miguel Bernal, Antonio Sala, Zsófia Lendek, Thierry Marie Guerra 205 $a1st ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (349 pages) 225 1 $aStudies in Systems, Decision and Control,$x2198-4190 ;$v408 300 $aIncludes index. 311 08$aPrint version: Bernal, Miguel Analysis and Synthesis of Nonlinear Control Systems Cham : Springer International Publishing AG,c2022 9783030907723 327 $aIntroduction -- Problems to be Solved and Scope of the Book -- Modeling via Convex Structures -- Stability Analysis -- State Feedback -- Performance, Robustness, Observation, and Output Feedback -- Conclusions and Perspectives. 330 $aThis book presents a modern perspective on the modelling, analysis, and synthesis ideas behind convex-optimisation-based control of nonlinear systems: it embeds them in models with convex structures. Analysis and Synthesis of Nonlinear Control Systems begins with an introduction to the topic and a discussion of the problems to be solved. It then explores modelling via convex structures, including quasi-linear parameter-varying, Takagi?Sugeno models, and linear fractional transformation structures. The authors cover stability analysis, addressing Lyapunov functions and the stability of polynomial models, as well as the performance and robustness of the models. With detailed examples, simulations, and programming code, this book will be useful to instructors, researchers, and graduate students interested in nonlinear control systems. 410 0$aStudies in Systems, Decision and Control,$x2198-4190 ;$v408 606 $aAutomatic control 606 $aMathematical optimization 606 $aSystem theory 606 $aControl theory 606 $aRobust statistics 606 $aControl and Systems Theory 606 $aOptimization 606 $aSystems Theory, Control 606 $aSystem Robustness 615 0$aAutomatic control. 615 0$aMathematical optimization. 615 0$aSystem theory. 615 0$aControl theory. 615 0$aRobust statistics. 615 14$aControl and Systems Theory. 615 24$aOptimization. 615 24$aSystems Theory, Control. 615 24$aSystem Robustness. 676 $a629.8312 676 $a629.836 700 $aBernal$b Miguel$01117288 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910544848203321 996 $aAnalysis and synthesis of nonlinear control systems$92918109 997 $aUNINA LEADER 05446nam 22007214a 450 001 9911019519203321 005 20200520144314.0 010 $a9786610344468 010 $a9781280344466 010 $a1280344466 010 $a9780470252338 010 $a0470252332 010 $a9780471473275 010 $a0471473278 010 $a9780471473268 010 $a047147326X 035 $a(CKB)1000000000019007 035 $a(EBL)468660 035 $a(OCoLC)609847405 035 $a(SSID)ssj0000313052 035 $a(PQKBManifestationID)11254623 035 $a(PQKBTitleCode)TC0000313052 035 $a(PQKBWorkID)10358142 035 $a(PQKB)10930238 035 $a(MiAaPQ)EBC468660 035 $a(PPN)243027818 035 $a(Perlego)2788545 035 $a(EXLCZ)991000000000019007 100 $a20030513d2004 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aWeibull models /$fD.N. Prabhakar Murthy, Min Xie, Renyan Jiang 210 $aHoboken, N.J. $cJ. Wiley$dc2004 215 $a1 online resource (409 p.) 225 1 $aWiley series in probability and statistics 300 $aDescription based upon print version of record. 311 08$a9780471360926 311 08$a0471360929 320 $aIncludes bibliographical references and index. 327 $aWeibull Models; Contents; Preface; PART A OVERVIEW; Chapter 1 Overview; 1.1 Introduction; 1.2 Illustrative Problems; 1.3 Empirical Modeling Methodology; 1.4 Weibull Models; 1.5 Weibull Model Selection; 1.6 Applications of Weibull Models; 1.7 Outline of the Book; 1.8 Notes; Exercises; Chapter 2 Taxonomy for Weibull Models; 2.1 Introduction; 2.2 Taxonomy for Weibull Models; 2.3 Type I Models: Transformation of Weibull Variable; 2.4 Type II Models: Modification/Generalization of Weibull Distribution; 2.5 Type III Models: Models Involving Two or More Distributions 327 $a2.6 Type IV Models: Weibull Models with Varying Parameters2.7 Type V Models: Discrete Weibull Models; 2.8 Type VI Models: Multivariate Weibull Models; 2.9 Type VII Models: Stochastic Point Process Models; Exercises; PART B BASIC WEIBULL MODEL; Chapter 3 Model Analysis; 3.1 Introduction; 3.2 Basic Concepts; 3.3 Standard Weibull Model; 3.4 Three-Parameter Weibull Model; 3.5 Notes; Exercises; Chapter 4 Parameter Estimation; 4.1 Introduction; 4.2 Data Types; 4.3 Estimation: An Overview; 4.4 Estimation Methods and Estimators; 4.5 Two-Parameter Weibull Model: Graphical Methods 327 $a4.6 Standard Weibull Model: Statistical Methods4.7 Three-Parameter Weibull Model; Exercises; Chapter 5 Model Selection and Validation; 5.1 Introduction; 5.2 Graphical Methods; 5.3 Goodness-of-Fit Tests; 5.4 Model Discrimination; 5.5 Model Validation; 5.6 Two-Parameter Weibull Model; 5.7 Three-Parameter Weibull Model; Exercises; PART C TYPES I AND II MODELS; Chapter 6 Type I Weibull Models; 6.1 Introduction; 6.2 Model I(a)-3: Reflected Weibull Distribution; 6.3 Model I(a)-4: Double Weibull Distribution; 6.4 Model I(b)-1: Power Law Transformation; 6.5 Model I(b)-2: Log Weibull Transformation 327 $a6.6 Model I(b)-3: Inverse Weibull DistributionExercises; Chapter 7 Type II Weibull Models; 7.1 Introduction; 7.2 Model II(a)-1: Pseudo-Weibull Distribution; 7.3 Model II(a)-2: Stacy-Mihram Model; 7.4 Model II(b)-1: Extended Weibull Distribution; 7.5 Model II(b)-2: Exponentiated Weibull Distribution; 7.6 Model II(b)-3: Modified Weibull Distribution; 7.7 Models II(b)4-6: Generalized Weibull Family; 7.8 Model II(b)-7: Three-Parameter Generalized Gamma; 7.9 Model II(b)-8: Extended Generalized Gamma; 7.10 Models II(b)9-10: Four- and Five-Parameter Weibulls 327 $a7.11 Model II(b)-11: Truncated Weibull Distribution7.12 Model II(b)-12: Slymen-Lachenbruch Distributions; 7.13 Model II(b)-13: Weibull Extension; Exercises; PART D TYPE III MODELS; Chapter 8 Type III(a) Weibull Models; 8.1 Introduction; 8.2 Model III(a)-1: Weibull Mixture Model; 8.3 Model III(a)-2: Inverse Weibull Mixture Model; 8.4 Model III(a)-3: Hybrid Weibull Mixture Models; 8.5 Notes; Exercises; Chapter 9 Type III(b) Weibull Models; 9.1 Introduction; 9.2 Model III(b)-1: Weibull Competing Risk Model; 9.3 Model III(b)-2: Inverse Weibull Competing Risk Model 327 $a9.4 Model III(b)-3: Hybrid Weibull Competing Risk Model 330 $aA comprehensive perspective on Weibull models The literature on Weibull models is vast, disjointed, and scattered across many different journals. Weibull Models is a comprehensive guide that integrates all the different facets of Weibull models in a single volume. This book will be of great help to practitioners in reliability and other disciplines in the context of modeling data sets using Weibull models. For researchers interested in these modeling techniques, exercises at the end of each chapter define potential topics for future research. Organized into seven distinct parts, Weibull 410 0$aWiley series in probability and statistics. 606 $aWeibull distribution 615 0$aWeibull distribution. 676 $a519.2/4 700 $aMurthy$b D. N. P$0742239 701 $aXie$b M$g(Min)$01643415 701 $aJiang$b Renyan$f1956-$0501365 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911019519203321 996 $aWeibull models$94419205 997 $aUNINA