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MARC Lista (tabellare)
Adaptive approximation based control [[electronic resource] ] : unifying neural, fuzzy and traditional adaptive approximation approaches / / Jay A. Farrell, Marios M. Polycarpou
Adaptive approximation based control [[electronic resource] ] : unifying neural, fuzzy and traditional adaptive approximation approaches / / Jay A. Farrell, Marios M. Polycarpou
Autore Farrell Jay
Pubbl/distr/stampa Hoboken, N.J., : Wiley-Interscience, c2006
Descrizione fisica 1 online resource (440 p.)
Disciplina 629.8
Altri autori (Persone) PolycarpouMarios
Collana Wiley series in adaptive and learning systems for signal processing, communication and control
Soggetto topico Adaptive control systems
Feedback control systems
Soggetto genere / forma Electronic books.
ISBN 1-280-44804-0
9786610448043
0-470-32501-1
0-471-78181-9
0-471-78180-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto ADAPTIVE APPROXIMATlON BASED CONTROL; CONTENTS; Preface; 1 Introduction; 1.1 Systems and Control Terminology; 1.2 Nonlinear Systems; 1.3 Feedback Control Approaches; 1.3.1 Linear Design; 1.3.2 Adaptive Linear Design; 1.3.3 Nonlinear Design; 1.3.4 Adaptive Approximation Based Design; 1.3.5 Example Summary; 1.4 Components of Approximation Based Control; 1.4.1 Control Architecture; 1.4.2 Function Approximator; 1.4.3 Stable Training Algorithm; 1.5 Discussion and Philosophical Comments; 1.6 Exercises and Design Problems; 2 Approximation Theory; 2.1 Motivating Example; 2.2 Interpolation
2.3 Function Approximation2.3.1 Offline (Batch) Function Approximation; 2.3.2 Adaptive Function Approximation; 2.4 Approximator Properties; 2.4.1 Parameter (Non) Linearity; 2.4.2 Classical Approximation Results; 2.4.3 Network Approximators; 2.4.4 Nodal Processors; 2.4.5 Universal Approximator; 2.4.6 Best Approximator Property; 2.4.7 Generalization; 2.4.8 Extent of Influence Function Support; 2.4.9 Approximator Transparency; 2.4.10 Haar Conditions; 2.4.11 Multivariable Approximation by Tensor Products; 2.5 Summary; 2.6 Exercises and Design Problems; 3 Approximation Structures; 3.1 Model Types
3.1.1 Physically Based Models3.1.2 Structure (Model) Free Approximation; 3.1.3 Function Approximation Structures; 3.2 Polynomials; 3.2.1 Description; 3.2.2 Properties; 3.3 Splines; 3.3.1 Description; 3.3.2 Properties; 3.4 Radial Basis Functions; 3.4.1 Description; 3.4.2 Properties; 3.5 Cerebellar Model Articulation Controller; 3.5.1 Description; 3.5.2 Properties; 3.6 Multilayer Perceptron; 3.6.1 Description; 3.6.2 Properties; 3.7 Fuzzy Approximation; 3.7.1 Description; 3.7.2 Takagi-Sugeno Fuzzy Systems; 3.7.3 Properties; 3.8 Wavelets; 3.8.1 Multiresolution Analysis (MRA); 3.8.2 MRA Properties
3.9 Further Reading3.10 Exercises and Design Problems; 4 Parameter Estimation Methods; 4.1 Formulation for Adaptive Approximation; 4.1.1 Illustrative Example; 4.1.2 Motivating Simulation Examples; 4.1.3 Problem Statement; 4.1.4 Discussion of Issues in Parametric Estimation; 4.2 Derivation of Parametric Models; 4.2.1 Problem Formulation for Full-State Measurement; 4.2.2 Filtering Techniques; 4.2.3 SPR Filtering; 4.2.4 Linearly Parameterized Approximators; 4.2.5 Parametric Models in State Space Form; 4.2.6 Parametric Models of Discrete-Time Systems
4.2.7 Parametric Models of Input-Output Systems4.3 Design of Online Learning Schemes; 4.3.1 Error Filtering Online Learning (EFOL) Scheme; 4.3.2 Regressor Filtering Online Learning (RFOL) Scheme; 4.4 Continuous-Time Parameter Estimation; 4.4.1 Lyapunov-Based Algorithms; 4.4.2 Optimization Methods; 4.4.3 Summary; 4.5 Online Learning: Analysis; 4.5.1 Analysis of LIP EFOL Scheme with Lyapunov Synthesis Method; 4.5.2 Analysis of LIP RFOL Scheme with the Gradient Algorithm; 4.5.3 Analysis of LIP RFOL Scheme with RLS Algorithm; 4.5.4 Persistency of Excitation and Parameter Convergence
4.6 Robust Learning Algorithms
Record Nr. UNINA-9910143397203321
Farrell Jay  
Hoboken, N.J., : Wiley-Interscience, c2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Adaptive approximation based control [[electronic resource] ] : unifying neural, fuzzy and traditional adaptive approximation approaches / / Jay A. Farrell, Marios M. Polycarpou
Adaptive approximation based control [[electronic resource] ] : unifying neural, fuzzy and traditional adaptive approximation approaches / / Jay A. Farrell, Marios M. Polycarpou
Autore Farrell Jay
Pubbl/distr/stampa Hoboken, N.J., : Wiley-Interscience, c2006
Descrizione fisica 1 online resource (440 p.)
Disciplina 629.8
Altri autori (Persone) PolycarpouMarios
Collana Wiley series in adaptive and learning systems for signal processing, communication and control
Soggetto topico Adaptive control systems
Feedback control systems
ISBN 1-280-44804-0
9786610448043
0-470-32501-1
0-471-78181-9
0-471-78180-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto ADAPTIVE APPROXIMATlON BASED CONTROL; CONTENTS; Preface; 1 Introduction; 1.1 Systems and Control Terminology; 1.2 Nonlinear Systems; 1.3 Feedback Control Approaches; 1.3.1 Linear Design; 1.3.2 Adaptive Linear Design; 1.3.3 Nonlinear Design; 1.3.4 Adaptive Approximation Based Design; 1.3.5 Example Summary; 1.4 Components of Approximation Based Control; 1.4.1 Control Architecture; 1.4.2 Function Approximator; 1.4.3 Stable Training Algorithm; 1.5 Discussion and Philosophical Comments; 1.6 Exercises and Design Problems; 2 Approximation Theory; 2.1 Motivating Example; 2.2 Interpolation
2.3 Function Approximation2.3.1 Offline (Batch) Function Approximation; 2.3.2 Adaptive Function Approximation; 2.4 Approximator Properties; 2.4.1 Parameter (Non) Linearity; 2.4.2 Classical Approximation Results; 2.4.3 Network Approximators; 2.4.4 Nodal Processors; 2.4.5 Universal Approximator; 2.4.6 Best Approximator Property; 2.4.7 Generalization; 2.4.8 Extent of Influence Function Support; 2.4.9 Approximator Transparency; 2.4.10 Haar Conditions; 2.4.11 Multivariable Approximation by Tensor Products; 2.5 Summary; 2.6 Exercises and Design Problems; 3 Approximation Structures; 3.1 Model Types
3.1.1 Physically Based Models3.1.2 Structure (Model) Free Approximation; 3.1.3 Function Approximation Structures; 3.2 Polynomials; 3.2.1 Description; 3.2.2 Properties; 3.3 Splines; 3.3.1 Description; 3.3.2 Properties; 3.4 Radial Basis Functions; 3.4.1 Description; 3.4.2 Properties; 3.5 Cerebellar Model Articulation Controller; 3.5.1 Description; 3.5.2 Properties; 3.6 Multilayer Perceptron; 3.6.1 Description; 3.6.2 Properties; 3.7 Fuzzy Approximation; 3.7.1 Description; 3.7.2 Takagi-Sugeno Fuzzy Systems; 3.7.3 Properties; 3.8 Wavelets; 3.8.1 Multiresolution Analysis (MRA); 3.8.2 MRA Properties
3.9 Further Reading3.10 Exercises and Design Problems; 4 Parameter Estimation Methods; 4.1 Formulation for Adaptive Approximation; 4.1.1 Illustrative Example; 4.1.2 Motivating Simulation Examples; 4.1.3 Problem Statement; 4.1.4 Discussion of Issues in Parametric Estimation; 4.2 Derivation of Parametric Models; 4.2.1 Problem Formulation for Full-State Measurement; 4.2.2 Filtering Techniques; 4.2.3 SPR Filtering; 4.2.4 Linearly Parameterized Approximators; 4.2.5 Parametric Models in State Space Form; 4.2.6 Parametric Models of Discrete-Time Systems
4.2.7 Parametric Models of Input-Output Systems4.3 Design of Online Learning Schemes; 4.3.1 Error Filtering Online Learning (EFOL) Scheme; 4.3.2 Regressor Filtering Online Learning (RFOL) Scheme; 4.4 Continuous-Time Parameter Estimation; 4.4.1 Lyapunov-Based Algorithms; 4.4.2 Optimization Methods; 4.4.3 Summary; 4.5 Online Learning: Analysis; 4.5.1 Analysis of LIP EFOL Scheme with Lyapunov Synthesis Method; 4.5.2 Analysis of LIP RFOL Scheme with the Gradient Algorithm; 4.5.3 Analysis of LIP RFOL Scheme with RLS Algorithm; 4.5.4 Persistency of Excitation and Parameter Convergence
4.6 Robust Learning Algorithms
Record Nr. UNINA-9910830081303321
Farrell Jay  
Hoboken, N.J., : Wiley-Interscience, c2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Adaptive approximation based control [[electronic resource] ] : unifying neural, fuzzy and traditional adaptive approximation approaches / / Jay A. Farrell, Marios M. Polycarpou
Adaptive approximation based control [[electronic resource] ] : unifying neural, fuzzy and traditional adaptive approximation approaches / / Jay A. Farrell, Marios M. Polycarpou
Autore Farrell Jay
Pubbl/distr/stampa Hoboken, N.J., : Wiley-Interscience, c2006
Descrizione fisica 1 online resource (440 p.)
Disciplina 629.8
Altri autori (Persone) PolycarpouMarios
Collana Wiley series in adaptive and learning systems for signal processing, communication and control
Soggetto topico Adaptive control systems
Feedback control systems
ISBN 1-280-44804-0
9786610448043
0-470-32501-1
0-471-78181-9
0-471-78180-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto ADAPTIVE APPROXIMATlON BASED CONTROL; CONTENTS; Preface; 1 Introduction; 1.1 Systems and Control Terminology; 1.2 Nonlinear Systems; 1.3 Feedback Control Approaches; 1.3.1 Linear Design; 1.3.2 Adaptive Linear Design; 1.3.3 Nonlinear Design; 1.3.4 Adaptive Approximation Based Design; 1.3.5 Example Summary; 1.4 Components of Approximation Based Control; 1.4.1 Control Architecture; 1.4.2 Function Approximator; 1.4.3 Stable Training Algorithm; 1.5 Discussion and Philosophical Comments; 1.6 Exercises and Design Problems; 2 Approximation Theory; 2.1 Motivating Example; 2.2 Interpolation
2.3 Function Approximation2.3.1 Offline (Batch) Function Approximation; 2.3.2 Adaptive Function Approximation; 2.4 Approximator Properties; 2.4.1 Parameter (Non) Linearity; 2.4.2 Classical Approximation Results; 2.4.3 Network Approximators; 2.4.4 Nodal Processors; 2.4.5 Universal Approximator; 2.4.6 Best Approximator Property; 2.4.7 Generalization; 2.4.8 Extent of Influence Function Support; 2.4.9 Approximator Transparency; 2.4.10 Haar Conditions; 2.4.11 Multivariable Approximation by Tensor Products; 2.5 Summary; 2.6 Exercises and Design Problems; 3 Approximation Structures; 3.1 Model Types
3.1.1 Physically Based Models3.1.2 Structure (Model) Free Approximation; 3.1.3 Function Approximation Structures; 3.2 Polynomials; 3.2.1 Description; 3.2.2 Properties; 3.3 Splines; 3.3.1 Description; 3.3.2 Properties; 3.4 Radial Basis Functions; 3.4.1 Description; 3.4.2 Properties; 3.5 Cerebellar Model Articulation Controller; 3.5.1 Description; 3.5.2 Properties; 3.6 Multilayer Perceptron; 3.6.1 Description; 3.6.2 Properties; 3.7 Fuzzy Approximation; 3.7.1 Description; 3.7.2 Takagi-Sugeno Fuzzy Systems; 3.7.3 Properties; 3.8 Wavelets; 3.8.1 Multiresolution Analysis (MRA); 3.8.2 MRA Properties
3.9 Further Reading3.10 Exercises and Design Problems; 4 Parameter Estimation Methods; 4.1 Formulation for Adaptive Approximation; 4.1.1 Illustrative Example; 4.1.2 Motivating Simulation Examples; 4.1.3 Problem Statement; 4.1.4 Discussion of Issues in Parametric Estimation; 4.2 Derivation of Parametric Models; 4.2.1 Problem Formulation for Full-State Measurement; 4.2.2 Filtering Techniques; 4.2.3 SPR Filtering; 4.2.4 Linearly Parameterized Approximators; 4.2.5 Parametric Models in State Space Form; 4.2.6 Parametric Models of Discrete-Time Systems
4.2.7 Parametric Models of Input-Output Systems4.3 Design of Online Learning Schemes; 4.3.1 Error Filtering Online Learning (EFOL) Scheme; 4.3.2 Regressor Filtering Online Learning (RFOL) Scheme; 4.4 Continuous-Time Parameter Estimation; 4.4.1 Lyapunov-Based Algorithms; 4.4.2 Optimization Methods; 4.4.3 Summary; 4.5 Online Learning: Analysis; 4.5.1 Analysis of LIP EFOL Scheme with Lyapunov Synthesis Method; 4.5.2 Analysis of LIP RFOL Scheme with the Gradient Algorithm; 4.5.3 Analysis of LIP RFOL Scheme with RLS Algorithm; 4.5.4 Persistency of Excitation and Parameter Convergence
4.6 Robust Learning Algorithms
Record Nr. UNINA-9910841512703321
Farrell Jay  
Hoboken, N.J., : Wiley-Interscience, c2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Adaptive approximation based control : unifying neural, fuzzy and traditional adaptive approximation approaches / Jay A. Farrell, Marios M. Polycarpou
Adaptive approximation based control : unifying neural, fuzzy and traditional adaptive approximation approaches / Jay A. Farrell, Marios M. Polycarpou
Autore Farrell, Jay A.
Pubbl/distr/stampa Hoboken, : Wiley, c2006
Descrizione fisica XVI, 420 p. ; 24 cm.
Disciplina 629.8
629.836
Altri autori (Persone) Polycarpou, Marios M.
Collana Wiley series in adaptive and learning systems for signal processing, communication and control
Soggetto topico Sistemi di controllo
ISBN 0471727881
9780471727880
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISANNIO-MIL0705909
Farrell, Jay A.  
Hoboken, : Wiley, c2006
Materiale a stampa
Lo trovi qui: Univ. del Sannio
Opac: Controlla la disponibilità qui
The global positioning systems and inertial navigation / Jay Farrell, Matthew Barth
The global positioning systems and inertial navigation / Jay Farrell, Matthew Barth
Autore Farrell, Jay
Pubbl/distr/stampa New York : McGraw Hill, 1998
Disciplina 526.6
623.8
Altri autori (Persone) Barth, Matthew
Soggetto non controllato Sistemi di posizionamento globale
Navigazione inerziale
ISBN 0-07-022045-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Titolo uniforme
Record Nr. UNIPARTHENOPE-000026523
Farrell, Jay  
New York : McGraw Hill, 1998
Materiale a stampa
Lo trovi qui: Univ. Parthenope
Opac: Controlla la disponibilità qui