Informationen zum Autor JERRY M. MENDEL is Professor in the Ming Hsieh Department of Electrical Engineering at the University of Southern California, Life Fellow of the IEEE, and a Distinguished Member of the IEEE Control Systems Society. HANI HAGRAS is Professor and Director of the Computational Intelligence Centre in the School of Computer Science and Electronic Engineering at the University of Essex, UK, and is a Fellow of the IEEE. WOEI-WAN TAN is Associate Professor in the Department of Electrical Engineering at the National University of Singapore. WILLIAM W. MELEK is Associate Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo. HAO YING is Professor in the Department of Electrical and Computer Engineering at Wayne State University and a Fellow of the IEEE. Klappentext Written by world-class leaders in type-2 fuzzy logic control, this book offers a self-contained reference for both researchers and students. The coverage provides both background and an extensive literature survey on fuzzy logic and related type-2 fuzzy control. It also includes research questions, experiment and simulation results, and downloadable computer programs on an associated website. This key resource will prove useful to students and engineers wanting to learn type-2 fuzzy control theory and its applications. Zusammenfassung Written by world-class leaders in type-2 fuzzy logic control, this book offers a self-contained reference for both researchers and students. The coverage provides both background and an extensive literature survey on fuzzy logic and related type-2 fuzzy control. It also includes research questions, experiment and simulation results, and downloadable computer programs on an associated website. This key resource will prove useful to students and engineers wanting to learn type-2 fuzzy control theory and its applications. Inhaltsverzeichnis Preface xiiiContributors xvii1 Introduction 11.1 Early History of Fuzzy Control 11.2 What Is a Type-1 Fuzzy Set? 21.3 What Is a Type-1 Fuzzy Logic Controller? 31.4 What Is a Type-2 Fuzzy Set? 71.5 What Is a Type-2 Fuzzy Logic Controller? 91.6 Distinguishing an FLC from Other Nonlinear Controllers 101.7 T2 FLCs versus T1 FLCs 111.8 Real-World Applications of IT2 Mamdani FLCs 141.8.1 Applications to Industrial Control 141.8.2 Airplane Altitude Control 231.8.3 Control of Mobile Robots 241.8.4 Control of Ambient Intelligent Environments 271.9 Book Rationale 291.10 Software and How it Can Be Accessed 301.11 Coverage of the Other Chapters 302 Introduction to Type-2 Fuzzy Sets 322.1 Introduction 322.2 Brief Review of Type-1 Fuzzy Sets 322.2.1 Some Definitions 322.2.2 Set-Theoretic Operations 352.2.3 Alpha Cuts 362.2.4 Compositions of T1 FSs 392.2.5 Rules and Their MFs 402.3 Interval Type-2 Fuzzy Sets 422.3.1 Introduction 422.3.2 Definitions 432.3.3 Set-Theoretic Operations 512.3.4 Centroid of an IT2 FS 542.3.5 Properties of cl(k) and cr(k) 582.3.6 KM Algorithms as Well as Some Others 592.4 General Type-2 Fuzzy Sets 682.4.1 alpha-Plane/zSlice Representation 682.4.2 Set-Theoretic Operations 722.4.3 Centroid of a GT2 FS 732.5 Wrapup 772.6 Moving On 793 Interval Type-2 Fuzzy Logic Controllers 803.1 Introduction 803.2 Type-1 Fuzzy Logic Controllers 803.2.1 Introduction 803.2.2 T1 Mamdani FLCs 813.2.3 T1 TSK FLCs 853.2.4 Design of T1 FLCs 863.3 Interval Type-2 Fuzzy Logic Controllers 863.3.1 Introduction 863.3.2 IT2 Mamdani FLCs 873.3.3 IT2 TSK FLCs 1033.3.4 Design of T2 FLCs 1053.4 Wu-Mendel Uncertainty Bounds 1053.5 Control Analyses of IT2 FLCs 1113.6 Determining the FOU Parameters of IT2 FLCs 1143.6.1 Blurring T1 MFs 1143.6.2 Optimizing FOU Parameters 1143.7 Moving On 122Appendix 3A. Proof of Theorem 3.4 1233A.1 Inner-Bound Set [ul...

Autorentext

JERRY M. MENDEL is Professor in the Ming Hsieh Department of Electrical Engineering at the University of Southern California, Life Fellow of the IEEE, and a Distinguished Member of the IEEE Control Systems Society.

HANI HAGRAS is Professor and Director of the Computational Intelligence Centre in the School of Computer Science and Electronic Engineering at the University of Essex, UK, and is a Fellow of the IEEE.

WOEI-WAN TAN is Associate Professor in the Department of Electrical Engineering at the National University of Singapore.

WILLIAM W. MELEK is Associate Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo.

HAO YING is Professor in the Department of Electrical and Computer Engineering at Wayne State University and a Fellow of the IEEE.

Klappentext

Written by world-class leaders in type-2 fuzzy logic control, this book offers a self-contained reference for both researchers and students. The coverage provides both background and an extensive literature survey on fuzzy logic and related type-2 fuzzy control. It also includes research questions, experiment and simulation results, and downloadable computer programs on an associated website. This key resource will prove useful to students and engineers wanting to learn type-2 fuzzy control theory and its applications.

Inhalt

Preface xiii Contributors xvii 1 Introduction 1 1.1 Early History of Fuzzy Control 1 1.2 What Is a Type-1 Fuzzy Set? 2 1.3 What Is a Type-1 Fuzzy Logic Controller? 3 1.4 What Is a Type-2 Fuzzy Set? 7 1.5 What Is a Type-2 Fuzzy Logic Controller? 9 1.6 Distinguishing an FLC from Other Nonlinear Controllers 10 1.7 T2 FLCs versus T1 FLCs 11 1.8 Real-World Applications of IT2 Mamdani FLCs 14 1.8.1 Applications to Industrial Control 14 1.8.2 Airplane Altitude Control 23 1.8.3 Control of Mobile Robots 24 1.8.4 Control of Ambient Intelligent Environments 27 1.9 Book Rationale 29 1.10 Software and How it Can Be Accessed 30 1.11 Coverage of the Other Chapters 30 2 Introduction to Type-2 Fuzzy Sets 32 2.1 Introduction 32 2.2 Brief Review of Type-1 Fuzzy Sets 32 2.2.1 Some Definitions 32 2.2.2 Set-Theoretic Operations 35 2.2.3 Alpha Cuts 36 2.2.4 Compositions of T1 FSs 39 2.2.5 Rules and Their MFs 40 2.3 Interval Type-2 Fuzzy Sets 42 2.3.1 Introduction 42 2.3.2 Definitions 43 2.3.3 Set-Theoretic Operations 51 2.3.4 Centroid of an IT2 FS 54 2.3.5 Properties of cl(k) and cr(k) 58 2.3.6 KM Algorithms as Well as Some Others 59 2.4 General Type-2 Fuzzy Sets 68 2.4.1 alpha-Plane/zSlice Representation 68 2.4.2 Set-Theoretic Operations 72 2.4.3 Centroid of a GT2 FS 73 2.5 Wrapup 77 2.6 Moving On 79 3 Interval Type-2 Fuzzy Logic Controllers 80 3.1 Introduction 80 3.2 Type-1 Fuzzy Logic Controllers 80 3.2.1 Introduction 80 3.2.2 T1 Mamdani FLCs 81 3.2.3 T1 TSK FLCs 85 3.2.4 Design of T1 FLCs 86 3.3 Interval Type-2 Fuzzy Logic Controllers 86 3.3.1 Introduction 86 3.3.2 IT2 Mamdani FLCs 87 3.3.3 IT2 TSK FLCs 103 3.3.4 Design of T2 FLCs 105 3.4 Wu-Mendel Uncertainty Bounds 105 3.5 Control Analyses of IT2 FLCs 111 3.6 Determining the FOU Parameters of IT2 FLCs 114 3.6.1 Blurring T1 MFs 114 3.6.2 Optimizing FOU Parameters 114 3.7 Moving On 122 Appendix 3A. Proof of Theorem 3.4 123 3A.1 Inner-Bound Set [ul(x), ur(x)] 123 3A.2 Outer-Bound Set [ul(x), ur(x)] 124 4 Analytical Structure of Various Interval Type-2 Fuzzy PI and PD Controllers 131 4.1 Introduction 131 4.2 PID, PI, and PD Controllers and Their Relationships 134 4.2.1 Two Forms of PID Controller--Position Form and Incremental Form 134 4.2.2 PI and PD Controllers and Their Relationship 135 4.3 Components of the Interval T2 Fuzzy PI and PD Controllers 136 4.4 Mamdani Fuzzy PI and PD Controllers--Configuration 1 140 4.4.1 Fuzzy PI Controller Configuration 140 4.4.2 Method for Deriving the Analytical Structure 144 4.5 Mamdani Fuzzy PI and PD Controllers--Configuration 2 154 4.6 Mamdani Fuzzy PI and PD Controllers--Configuration 3 162 4.6.1 Fuzzy PI Controller Configuration 162 4.6.2 Method for Deriving the Analytical Structure 165 4.7 Mamdani Fuzzy PI and PD Controllers--Configuration 4 169 4.7.1 Fuzzy PI Control…