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25-07 : Théorie de la commande: commandes des processus
25-01 Logique combinatoire et séquentielle 25-02 Théorie et traitement du signal 25-03 Filtrage analogique et numérique 25-04 Théorie des systèmes:systèmes asservis 25-05 Application du traitement numérique du signal 25-06 Identification et simulation des processus 25-08 Robotique.Application et simulationOuvrages de la bibliothèque en indexation 25-07
Affiner la recherche Interroger des sources externesActive control in mechanical engineering / Louis Jézéquel
Titre : Active control in mechanical engineering Type de document : texte imprimé Auteurs : Louis Jézéquel, Auteur Editeur : Paris : Hermès Année de publication : 1995 Collection : International Symposium MV2 Importance : 448 p. Présentation : ill. Format : 24 cm. ISBN/ISSN/EAN : 978-2-86601-450-6 Langues : Français (fre) Catégories : AUTOMATISME Index. décimale : 25-07 Théorie de la commande: commandes des processus Résumé : L'introduction du contrôle actif en dynamique des structures a donné lieu à un nombre considérable de développements dans des domaines industriels très divers. Une des premières applications a été l'augmentation des vitesses critiques de flottement des avions. Depuis, grâce à de nouvelles technologies, la mise en oeuvre de la théorie du contrôle sur des systèmes mécaniques s'est beaucoup développée. Par exemple, ces dernières années ont vu la mise au point de dispositifs d'isolation active des machines, de suspension avancée de véhicules et de systèmes de contrôle actif de bruit. Dans le domaine du génie civil de nombreuses stratégies ont été proposées pour réduire l'influence du vent ou des séismes sur les bâtiments. Récemment de nouvelles solutions de contrôle actif des vibrations basées sur l'utilisation de matériaux intelligents ont été proposées, et il apparaît important de vérifier leur efficacité par rapport à des solutions passives classiques. Note de contenu : Contents
1. Intelligent suspension systems
2. Active Noise Control
3. Smart Materials
4. Active Control of Flexible Structure
5. Active Control of Machinery Vibration
6. Control of Complex SystemsActive control in mechanical engineering [texte imprimé] / Louis Jézéquel, Auteur . - Paris : Hermès, 1995 . - 448 p. : ill. ; 24 cm.. - (International Symposium MV2) .
ISBN : 978-2-86601-450-6
Langues : Français (fre)
Catégories : AUTOMATISME Index. décimale : 25-07 Théorie de la commande: commandes des processus Résumé : L'introduction du contrôle actif en dynamique des structures a donné lieu à un nombre considérable de développements dans des domaines industriels très divers. Une des premières applications a été l'augmentation des vitesses critiques de flottement des avions. Depuis, grâce à de nouvelles technologies, la mise en oeuvre de la théorie du contrôle sur des systèmes mécaniques s'est beaucoup développée. Par exemple, ces dernières années ont vu la mise au point de dispositifs d'isolation active des machines, de suspension avancée de véhicules et de systèmes de contrôle actif de bruit. Dans le domaine du génie civil de nombreuses stratégies ont été proposées pour réduire l'influence du vent ou des séismes sur les bâtiments. Récemment de nouvelles solutions de contrôle actif des vibrations basées sur l'utilisation de matériaux intelligents ont été proposées, et il apparaît important de vérifier leur efficacité par rapport à des solutions passives classiques. Note de contenu : Contents
1. Intelligent suspension systems
2. Active Noise Control
3. Smart Materials
4. Active Control of Flexible Structure
5. Active Control of Machinery Vibration
6. Control of Complex SystemsExemplaires
Code-barres Cote Support Localisation Section Disponibilité N.Inventaire 1024 25-07-37 Livre Bibliothèque de Génie Electrique- USTO Documentaires Exclu du prêt 1024 1025 25-07-37 Livre Bibliothèque de Génie Electrique- USTO Documentaires Exclu du prêt 1025 1026 25-07-37 Livre Bibliothèque de Génie Electrique- USTO Documentaires Exclu du prêt 1026
Titre : Active fault tolerant control systems : stochastic analysis and synthesis Type de document : texte imprimé Auteurs : Mufeed Mahmoud, Auteur ; Jin Jiang, Auteur ; Youmin Zhang, Auteur Editeur : Berlin; Heidelberg; New York : Springer-Verlag Année de publication : 2003 Collection : Lecture Notes in Control and Information Sciences Importance : 210 p. Présentation : couv. ill. en coul., ill. Format : 24 cm. ISBN/ISSN/EAN : 9783540003185 Langues : Anglais (eng) Catégories : AUTOMATISME Index. décimale : 25-07 Théorie de la commande: commandes des processus Résumé : Modern technological systems rely on sophisticated control functions to meet increased performance requirements. For such systems, Fault Tolerant Control Systems (FTCS) need to be developed. Active FTCS are dependent on a Fault Detection and Identification (FDI) process to monitor system performance and to detect and isolate faults in the systems. The main objective of this book is to study and to validate some important issues in real-time Active FTCS by means of theoretical analysis and simulation. Several models are presented to achieve this objective, taking into consideration practical aspects of the system to be controlled, performance deterioration in FDI algorithms, and limitations in reconfigurable control laws. Note de contenu : Contents
1 INTRODUCTION
2 Active Fault Tolerant Control in Prospective.
3 Stochastic Stability.
4 Ftcs with Markovian Parameters (FTCSMP).
5 Stochastic Stability of FTCSMP.
6 Performance and Staility of FTCSMP Under Imperfect FDI.
7 FTCSMP with Actuator Saturation and Parameter Uncertainties.
8 Synthesis of Fault Tolerant Control Laws.
9 Epilogue.Active fault tolerant control systems : stochastic analysis and synthesis [texte imprimé] / Mufeed Mahmoud, Auteur ; Jin Jiang, Auteur ; Youmin Zhang, Auteur . - Berlin; Heidelberg; New York : Springer-Verlag, 2003 . - 210 p. : couv. ill. en coul., ill. ; 24 cm.. - (Lecture Notes in Control and Information Sciences) .
ISSN : 9783540003185
Langues : Anglais (eng)
Catégories : AUTOMATISME Index. décimale : 25-07 Théorie de la commande: commandes des processus Résumé : Modern technological systems rely on sophisticated control functions to meet increased performance requirements. For such systems, Fault Tolerant Control Systems (FTCS) need to be developed. Active FTCS are dependent on a Fault Detection and Identification (FDI) process to monitor system performance and to detect and isolate faults in the systems. The main objective of this book is to study and to validate some important issues in real-time Active FTCS by means of theoretical analysis and simulation. Several models are presented to achieve this objective, taking into consideration practical aspects of the system to be controlled, performance deterioration in FDI algorithms, and limitations in reconfigurable control laws. Note de contenu : Contents
1 INTRODUCTION
2 Active Fault Tolerant Control in Prospective.
3 Stochastic Stability.
4 Ftcs with Markovian Parameters (FTCSMP).
5 Stochastic Stability of FTCSMP.
6 Performance and Staility of FTCSMP Under Imperfect FDI.
7 FTCSMP with Actuator Saturation and Parameter Uncertainties.
8 Synthesis of Fault Tolerant Control Laws.
9 Epilogue.Exemplaires
Code-barres Cote Support Localisation Section Disponibilité N.Inventaire 414 25-07-12 Livre Bibliothèque de Génie Electrique- USTO Documentaires Exclu du prêt 414
Titre : Adaptive control : algorithms, analysis and applications Type de document : texte imprimé Auteurs : Ioan D. Landau, Auteur ; Rogelio Lozano, Auteur ; Mohammed M'Saad, Auteur Mention d'édition : 2 ème ed. Editeur : New York, Dordrecht, Heidelberg : Springer Année de publication : 2011 Importance : 587 p. Présentation : couv. ill. en coul., ill. Format : 24,5 cm. ISBN/ISSN/EAN : 978-0-85729-663-4 Langues : Anglais (eng) Catégories : AUTOMATISME Index. décimale : 25-07 Théorie de la commande: commandes des processus Résumé : Adaptive Control (second edition) shows how a desired level of system performance can be maintained automatically and in real time, even when process or disturbance parameters are unknown and variable. It is a coherent exposition of the many aspects of this field, setting out the problems to be addressed and moving on to solutions, their practical significance and their application. Discrete-time aspects of adaptive control are emphasized to reflect the importance of digital computers in the application of the ideas presented. The second edition is thoroughly revised to throw light on recent developments in theory and applications with new chapters on: multimodel adaptive control with switching, direct and indirect adaptive regulation and adaptive feedforward disturbance compensation. Many algorithms are newly presented in MATLAB® m-file format to facilitate their employment in real systems. Classroom-tested slides for instructors to use in teaching this material are also now provided. All of this supplementary electronic material can be downloaded from fill in URL. The core material is also up-dated and re-edited to keep its perspective in line with modern ideas and more closely to associate algorithms with their applications giving the reader a solid grounding in: synthesis and analysis of parameter adaptation algorithms, recursive plant model identification in open and closed loop, robust digital control for adaptive control; • robust parameter adaptation algorithms, practical considerations and applications, including flexible transmission systems, active vibration control and broadband disturbance rejection and a supplementary introduction on hot dip galvanizing and a phosphate drying furnace. Control researchers and applied mathematicians will find Adaptive Control of significant and enduring interest and its use of example and application will appeal to practitioners working with unknown- and variable-parameter plant. Note de contenu : Contents
1: Introduction to Adaptive Control
1.1 Adaptive Control-Why?
1.2 Adaptive Control Versus Conventional Feedback Control
1.3 Basic Adaptive Control Schemes
1.4 Examples of Applications
1.5 A Brief Historical Note
1.6 Further Reading
1.7 Concluding Remarks
2: Discrete-Time System Models for Control
2.1 Deterministic Environment
2.2 Stochastic Environment
2.3 Concluding Remarks
2.4 Problems
3: Parameter Adaptation Algorithms-Deterministic Environment
3.1 The Problem
3.2 Parameter Adaptation Algorithms (PAA)-Examples
3.3 Stability of Parameter Adaptation Algorithms
3.4 Parametric Convergence
3.5 Concluding Remarks
3.6 Problems
4: Parameter Adaptation Algorithms-Stochastic Environment
4.1 Effect of Stochastic Disturbances
4.2 The Averaging Method for the Analysis of Adaptation Algorithms in a Stochastic Environment
4.3 The Martingale Approach for the Analysis of PAA in a Stochastic Environment
4.4 The Frequency Domain Approach
4.5 Concluding Remarks
4.6 Problem
5: Recursive Plant Model Identification in Open Loop
5.1 Recursive Identification in the Context of System Identification
5.2 Structure of Recursive Parameter Estimation Algorithms
5.3 Recursive Identification Methods Based on the Whitening of the the prediction error type I
5.4 Validation of the Models Identified with Type I Methods
5.5 Identification Methods Based on the Decorrelation of the Observation vector and the prediction error type II
5.6 Validation of the Models Identified with Type II Methods
5.7 Selection of the Pseudo Random Binary Sequence
5.8 Model Order Selection
5.9 An Example: Identification of a Flexible Transmission
5.10 Concluding Remarks
5.11 Problems
6: Adaptive Prediction
6.1 The Problem
6.2 Adaptive Prediction-Deterministic Case
6.3 Adaptive Prediction-Stochastic Case
6.4 Concluding Remarks
6.5 Problems
7: Digital Control Strategies
7.1 Introduction
7.2 Canonical Form for Digital Controllers
7.3 Pole Placement
7.4 Tracking and Regulation with Independent Objectives
7.5 Tracking and Regulation with Weighted Input
7.6 Minimum Variance Tracking and Regulation
7.7 Generalized Predictive Control
7.8 Linear Quadratic Control
7.9 Concluding Remarks
7.10 Problems
8: Robust Digital Control Design
8.1 The Robustness Problem
8.2 The Sensitivity Functions
8.3 Robust Stability
8.4 Definition of "Templates" for the Sensitivity Functions
8.5 Properties of the Sensitivity Functions
8.6 Shaping the Sensitivity Functions
8.7 Other Design Methods
8.8 A Design Example: Robust Digital Control of a Flexible Transmission
8.9 Concluding Remarks
8.10 Problems
9: Recursive Plant Model Identification in Closed Loop
9.1 The Problem
9.2 Closed-Loop Output Error Algorithms (CLOE)
9.3 Filtered Open-Loop Recursive Identification Algorithms (FOL)
9.4 Frequency Distribution of the Asymptotic Bias in Closed-Loop Identification
9.5 Validation of Models Identified in Closed-Loop
9.6 Iterative Identification in Closed-Loop and Controller Redesign
9.7 Comparative Evaluation of the Various Algorithms
9.8 Iterative Identification in Closed Loop and Controller Redesign Applied to the Flexible Transmis
9.9 Concluding Remarks
9.10 Problems
10: Robust Parameter Estimation
10.1 The Problem
10.2 Input/Output Data Filtering
10.3 Effect of Disturbances
10.4 PAA with Dead Zone
10.5 PAA with Projection
10.6 Data Normalization
10.7 A Robust Parameter Estimation Scheme
10.8 Concluding Remarks
10.9 Problems
11: Direct Adaptive Control
11.1 Introduction
11.2 Adaptive Tracking and Regulation with Independent Objectives
11.3 Adaptive Tracking and Regulation with Weighted Input
11.4 Adaptive Minimum Variance Tracking and Regulation
11.5 Robust Direct Adaptive Control
11.6 An Example
11.7 Concluding Remarks
11.8 Problems
12: Indirect Adaptive Control
12.1 Introduction
12.2 Adaptive Pole Placement
12.3 Robust Indirect Adaptive Control
12.4 Adaptive Generalized Predictive Control
12.5 Adaptive Linear Quadratic Control
12.6 Adaptive Tracking and Robust Regulation
12.7 Indirect Adaptive Control Applied to the Flexible Transmission
12.8 Concluding Remarks
12.9 Problems
13: Multimodel Adaptive Control with Switching
13.1 Introduction
13.2 Princip13.3les of Multimodel Adaptive Control with Switching
13.3 Stability Issues
13.4 Application to the Flexible Transmission System
13.5 Concluding Remarks
13.6 Problems
14: Adaptive Regulation-Rejection of Unknown Disturbances
14.1 Introduction
14.2 Plant Representation and Controller Design
14.3 Robustness Considerations
14.4 Direct Adaptive Regulation
14.5 Stability Analysis
14.6 Indirect Adaptive Regulation
14.7 Adaptive Rejection of Multiple Narrow Band Disturbances on an Active Vibration Control System
14.8 Concluding Remarks
14.9 Problems
15: Adaptive Feedforward Compensation of Disturbances
15.1 Introduction
15.2 Basic Equations and Notations
15.3 Development of the Algorithms
15.4 Analysis of the Algorithms
15.5 Adaptive Attenuation of Broad Band Disturbances on an Active Vibration Control System
15.6 Concluding Remarks
15.7 Problems
16: Practical Aspects
16.1 Introduction
16.2 The Digital Control System
16.2.1 Selection of the Sampling Frequency
16.2.2 Anti-Aliasing Filters
16.2.3 Digital Controller
16.2.4 Effects of the Digital to Analog Converter
16.2.5 Handling Actuator Saturations (Anti-Windup)
16.2.6 Manual to Automatic Bumpless Transfer
16.2.7 Effect of the Computational Delay
16.2.8 Choice of the Desired Performance
16.3 The Parameter Adaptation Algorithm
16.3.1 Scheduling Variable alpha1(t)
16.3.2 Implementation of the Adaptation Gain Updating-The U-D Factorization
16.4 Adaptive Control Algorithms
16.4.1 Control Strategies
16.4.2 Adaptive Control Algorithms
16.5 Initialization of Adaptive Control Schemes
16.6 Monitoring of Adaptive Control Systems
16.7 Concluding Remarks
Appendix A: Stochastic Processes
Appendix B: Stability
Appendix C: Passive (Hyperstable) Systems
C.1 Passive (Hyperstable) Systems
C.2 Passivity-Some Definitions
C.3 Discrete Linear Time-Invariant Passive Systems
C.4 Discrete Linear Time-Varying Passive Systems
C.5 Stability of Feedback Interconnected Systems
C.6 Hyperstability and Small Gain
Appendix D: Martingales
References
IndexAdaptive control : algorithms, analysis and applications [texte imprimé] / Ioan D. Landau, Auteur ; Rogelio Lozano, Auteur ; Mohammed M'Saad, Auteur . - 2 ème ed. . - New York, Dordrecht, Heidelberg : Springer, 2011 . - 587 p. : couv. ill. en coul., ill. ; 24,5 cm.
ISBN : 978-0-85729-663-4
Langues : Anglais (eng)
Catégories : AUTOMATISME Index. décimale : 25-07 Théorie de la commande: commandes des processus Résumé : Adaptive Control (second edition) shows how a desired level of system performance can be maintained automatically and in real time, even when process or disturbance parameters are unknown and variable. It is a coherent exposition of the many aspects of this field, setting out the problems to be addressed and moving on to solutions, their practical significance and their application. Discrete-time aspects of adaptive control are emphasized to reflect the importance of digital computers in the application of the ideas presented. The second edition is thoroughly revised to throw light on recent developments in theory and applications with new chapters on: multimodel adaptive control with switching, direct and indirect adaptive regulation and adaptive feedforward disturbance compensation. Many algorithms are newly presented in MATLAB® m-file format to facilitate their employment in real systems. Classroom-tested slides for instructors to use in teaching this material are also now provided. All of this supplementary electronic material can be downloaded from fill in URL. The core material is also up-dated and re-edited to keep its perspective in line with modern ideas and more closely to associate algorithms with their applications giving the reader a solid grounding in: synthesis and analysis of parameter adaptation algorithms, recursive plant model identification in open and closed loop, robust digital control for adaptive control; • robust parameter adaptation algorithms, practical considerations and applications, including flexible transmission systems, active vibration control and broadband disturbance rejection and a supplementary introduction on hot dip galvanizing and a phosphate drying furnace. Control researchers and applied mathematicians will find Adaptive Control of significant and enduring interest and its use of example and application will appeal to practitioners working with unknown- and variable-parameter plant. Note de contenu : Contents
1: Introduction to Adaptive Control
1.1 Adaptive Control-Why?
1.2 Adaptive Control Versus Conventional Feedback Control
1.3 Basic Adaptive Control Schemes
1.4 Examples of Applications
1.5 A Brief Historical Note
1.6 Further Reading
1.7 Concluding Remarks
2: Discrete-Time System Models for Control
2.1 Deterministic Environment
2.2 Stochastic Environment
2.3 Concluding Remarks
2.4 Problems
3: Parameter Adaptation Algorithms-Deterministic Environment
3.1 The Problem
3.2 Parameter Adaptation Algorithms (PAA)-Examples
3.3 Stability of Parameter Adaptation Algorithms
3.4 Parametric Convergence
3.5 Concluding Remarks
3.6 Problems
4: Parameter Adaptation Algorithms-Stochastic Environment
4.1 Effect of Stochastic Disturbances
4.2 The Averaging Method for the Analysis of Adaptation Algorithms in a Stochastic Environment
4.3 The Martingale Approach for the Analysis of PAA in a Stochastic Environment
4.4 The Frequency Domain Approach
4.5 Concluding Remarks
4.6 Problem
5: Recursive Plant Model Identification in Open Loop
5.1 Recursive Identification in the Context of System Identification
5.2 Structure of Recursive Parameter Estimation Algorithms
5.3 Recursive Identification Methods Based on the Whitening of the the prediction error type I
5.4 Validation of the Models Identified with Type I Methods
5.5 Identification Methods Based on the Decorrelation of the Observation vector and the prediction error type II
5.6 Validation of the Models Identified with Type II Methods
5.7 Selection of the Pseudo Random Binary Sequence
5.8 Model Order Selection
5.9 An Example: Identification of a Flexible Transmission
5.10 Concluding Remarks
5.11 Problems
6: Adaptive Prediction
6.1 The Problem
6.2 Adaptive Prediction-Deterministic Case
6.3 Adaptive Prediction-Stochastic Case
6.4 Concluding Remarks
6.5 Problems
7: Digital Control Strategies
7.1 Introduction
7.2 Canonical Form for Digital Controllers
7.3 Pole Placement
7.4 Tracking and Regulation with Independent Objectives
7.5 Tracking and Regulation with Weighted Input
7.6 Minimum Variance Tracking and Regulation
7.7 Generalized Predictive Control
7.8 Linear Quadratic Control
7.9 Concluding Remarks
7.10 Problems
8: Robust Digital Control Design
8.1 The Robustness Problem
8.2 The Sensitivity Functions
8.3 Robust Stability
8.4 Definition of "Templates" for the Sensitivity Functions
8.5 Properties of the Sensitivity Functions
8.6 Shaping the Sensitivity Functions
8.7 Other Design Methods
8.8 A Design Example: Robust Digital Control of a Flexible Transmission
8.9 Concluding Remarks
8.10 Problems
9: Recursive Plant Model Identification in Closed Loop
9.1 The Problem
9.2 Closed-Loop Output Error Algorithms (CLOE)
9.3 Filtered Open-Loop Recursive Identification Algorithms (FOL)
9.4 Frequency Distribution of the Asymptotic Bias in Closed-Loop Identification
9.5 Validation of Models Identified in Closed-Loop
9.6 Iterative Identification in Closed-Loop and Controller Redesign
9.7 Comparative Evaluation of the Various Algorithms
9.8 Iterative Identification in Closed Loop and Controller Redesign Applied to the Flexible Transmis
9.9 Concluding Remarks
9.10 Problems
10: Robust Parameter Estimation
10.1 The Problem
10.2 Input/Output Data Filtering
10.3 Effect of Disturbances
10.4 PAA with Dead Zone
10.5 PAA with Projection
10.6 Data Normalization
10.7 A Robust Parameter Estimation Scheme
10.8 Concluding Remarks
10.9 Problems
11: Direct Adaptive Control
11.1 Introduction
11.2 Adaptive Tracking and Regulation with Independent Objectives
11.3 Adaptive Tracking and Regulation with Weighted Input
11.4 Adaptive Minimum Variance Tracking and Regulation
11.5 Robust Direct Adaptive Control
11.6 An Example
11.7 Concluding Remarks
11.8 Problems
12: Indirect Adaptive Control
12.1 Introduction
12.2 Adaptive Pole Placement
12.3 Robust Indirect Adaptive Control
12.4 Adaptive Generalized Predictive Control
12.5 Adaptive Linear Quadratic Control
12.6 Adaptive Tracking and Robust Regulation
12.7 Indirect Adaptive Control Applied to the Flexible Transmission
12.8 Concluding Remarks
12.9 Problems
13: Multimodel Adaptive Control with Switching
13.1 Introduction
13.2 Princip13.3les of Multimodel Adaptive Control with Switching
13.3 Stability Issues
13.4 Application to the Flexible Transmission System
13.5 Concluding Remarks
13.6 Problems
14: Adaptive Regulation-Rejection of Unknown Disturbances
14.1 Introduction
14.2 Plant Representation and Controller Design
14.3 Robustness Considerations
14.4 Direct Adaptive Regulation
14.5 Stability Analysis
14.6 Indirect Adaptive Regulation
14.7 Adaptive Rejection of Multiple Narrow Band Disturbances on an Active Vibration Control System
14.8 Concluding Remarks
14.9 Problems
15: Adaptive Feedforward Compensation of Disturbances
15.1 Introduction
15.2 Basic Equations and Notations
15.3 Development of the Algorithms
15.4 Analysis of the Algorithms
15.5 Adaptive Attenuation of Broad Band Disturbances on an Active Vibration Control System
15.6 Concluding Remarks
15.7 Problems
16: Practical Aspects
16.1 Introduction
16.2 The Digital Control System
16.2.1 Selection of the Sampling Frequency
16.2.2 Anti-Aliasing Filters
16.2.3 Digital Controller
16.2.4 Effects of the Digital to Analog Converter
16.2.5 Handling Actuator Saturations (Anti-Windup)
16.2.6 Manual to Automatic Bumpless Transfer
16.2.7 Effect of the Computational Delay
16.2.8 Choice of the Desired Performance
16.3 The Parameter Adaptation Algorithm
16.3.1 Scheduling Variable alpha1(t)
16.3.2 Implementation of the Adaptation Gain Updating-The U-D Factorization
16.4 Adaptive Control Algorithms
16.4.1 Control Strategies
16.4.2 Adaptive Control Algorithms
16.5 Initialization of Adaptive Control Schemes
16.6 Monitoring of Adaptive Control Systems
16.7 Concluding Remarks
Appendix A: Stochastic Processes
Appendix B: Stability
Appendix C: Passive (Hyperstable) Systems
C.1 Passive (Hyperstable) Systems
C.2 Passivity-Some Definitions
C.3 Discrete Linear Time-Invariant Passive Systems
C.4 Discrete Linear Time-Varying Passive Systems
C.5 Stability of Feedback Interconnected Systems
C.6 Hyperstability and Small Gain
Appendix D: Martingales
References
IndexExemplaires
Code-barres Cote Support Localisation Section Disponibilité N.Inventaire 2893 25-07-88 Livre Bibliothèque de Génie Electrique- USTO Documentaires Exclu du prêt 2893 2894 25-07-88 Livre Bibliothèque de Génie Electrique- USTO Documentaires Exclu du prêt 2894
Titre : Adaptive feedforward controllers for active noise control Type de document : texte imprimé Auteurs : Biao Liu, Auteur Editeur : Germany : Shaker Verlag Année de publication : 2001 Collection : Berichte Aus Der Elektrotechnik Importance : 112 p. Présentation : couv. ill.,ill. Format : 24 cm. ISBN/ISSN/EAN : 978-3-8265-8766-5 Langues : Anglais (eng) Catégories : AUTOMATISME Index. décimale : 25-07 Théorie de la commande: commandes des processus Résumé : Active noise control (ANC) of headsets is revisited in this paper. An in-depth electroacoustic analysis of the combined loudspeaker-cavity headset system is conducted on the basis of electro-mechano-acoustical analogous circuits. Model matching of the primary path and the secondary path leads to a feedforward control architecture. The ideal controller sheds some light on the key parameters that affect the noise reduction performance. Filtered-X least-mean-squares algorithm is employed to implement the feedforward controller on a digital signal processor. Since the relative delay of the primary path and the secondary path is crucial to the noise reduction performance, multirate signal processing with polyphase implementation is utilized to minimize the effective analog-digital conversion delay in the secondary path. Ad hoc decimation and interpolation filters are designed in order not to introduce excessive phase delays at the cutoff. Real-time experiments are undertaken to validate the implemented ANC system. Listening tests are also conducted to compare the fixed controller and the adaptive controller in terms of noise reduction and signal tracking performance for three noise types. The results have demonstrated that the fixed feedforward controller achieved satisfactory noise reduction performance and signal tracking quality. Note de contenu : Table des matiéres:
1 Introduction
2 ANC as a control problem and the ANC plant
3 Adaptive system identification
4 Simplified feedback representations of adaptive algorithms
5 From signal processing to control: the underlying design problem of the direct adaptive inverse controller
6 Robustness of the adaptive inverse controller
7 Direct adaptive inverse control for ANC in ductAdaptive feedforward controllers for active noise control [texte imprimé] / Biao Liu, Auteur . - Germany : Shaker Verlag, 2001 . - 112 p. : couv. ill.,ill. ; 24 cm.. - (Berichte Aus Der Elektrotechnik) .
ISBN : 978-3-8265-8766-5
Langues : Anglais (eng)
Catégories : AUTOMATISME Index. décimale : 25-07 Théorie de la commande: commandes des processus Résumé : Active noise control (ANC) of headsets is revisited in this paper. An in-depth electroacoustic analysis of the combined loudspeaker-cavity headset system is conducted on the basis of electro-mechano-acoustical analogous circuits. Model matching of the primary path and the secondary path leads to a feedforward control architecture. The ideal controller sheds some light on the key parameters that affect the noise reduction performance. Filtered-X least-mean-squares algorithm is employed to implement the feedforward controller on a digital signal processor. Since the relative delay of the primary path and the secondary path is crucial to the noise reduction performance, multirate signal processing with polyphase implementation is utilized to minimize the effective analog-digital conversion delay in the secondary path. Ad hoc decimation and interpolation filters are designed in order not to introduce excessive phase delays at the cutoff. Real-time experiments are undertaken to validate the implemented ANC system. Listening tests are also conducted to compare the fixed controller and the adaptive controller in terms of noise reduction and signal tracking performance for three noise types. The results have demonstrated that the fixed feedforward controller achieved satisfactory noise reduction performance and signal tracking quality. Note de contenu : Table des matiéres:
1 Introduction
2 ANC as a control problem and the ANC plant
3 Adaptive system identification
4 Simplified feedback representations of adaptive algorithms
5 From signal processing to control: the underlying design problem of the direct adaptive inverse controller
6 Robustness of the adaptive inverse controller
7 Direct adaptive inverse control for ANC in ductExemplaires
Code-barres Cote Support Localisation Section Disponibilité N.Inventaire 972 25-07-23 Livre Bibliothèque de Génie Electrique- USTO Documentaires Exclu du prêt 972
Titre : Adaptive prediction and predictive control Type de document : texte imprimé Auteurs : Partha Pratim Kanjilal, Auteur Editeur : London : The Institution of Electrical Engineers Année de publication : 1995 Collection : IEE Control Engineering Series 52 Importance : 518 p. Présentation : couv. ill. en coul., ill. Format : 24,4 cm. ISBN/ISSN/EAN : 978-0-86341-193-9 Langues : Anglais (eng) Catégories : AUTOMATISME Index. décimale : 25-07 Théorie de la commande: commandes des processus Résumé : Control often follows predictions: predictive control has been highly successful in producing robust and practical solutions in many real-life, real-time applications. Adaptive prediction covers a variety of ways of adding 'intelligence' to predictive control techniques. Many different groups, with widely varying disciplinary backgrounds and approaches, are tackling the same problem from different angles; these groups are sometimes unaware of alternative approaches from other disciplines.
This book attempts to give a unified and comprehensive coverage of the principles and methods that these groups have developed. It avoids basing its descriptions on very complex mathematical formulations but still gives a rigorous exposure to the subject, and illustrates the theory with many practical examples. It is chiefly aimed at students, researchers and practitioners, but will also be accessible to the non-specialist.Note de contenu : contents:
Chapter 1: Introduction
Chapter 2: Process models
Chapter 3: Parameter estimation
Chapter 4: Some popular methods of prediction
Chapter 5: Adaptive prediction using transfer-function models
Chapter 6: Kalman filter and state-space approaches
Chapter 7: Orthogonal transformation and modelling of periodic series
Chapter 8: Modellong of nonlinear processes: an introduction
Chapter 9: Modelling of nonlinear processes using GMDH
Chapter 10: Modelling and prediction of nonlinear processes using neural networks
Chapter 11: Modelling and prediction of quasiperiodic series
Chapter 12: Predictive control (Part-I): input-output model based
Chapter 13: Predictive control (Part-II): state-space model based
Chapter 14: Smoothing and filtering
AppendicesAdaptive prediction and predictive control [texte imprimé] / Partha Pratim Kanjilal, Auteur . - London : The Institution of Electrical Engineers, 1995 . - 518 p. : couv. ill. en coul., ill. ; 24,4 cm.. - (IEE Control Engineering Series 52) .
ISBN : 978-0-86341-193-9
Langues : Anglais (eng)
Catégories : AUTOMATISME Index. décimale : 25-07 Théorie de la commande: commandes des processus Résumé : Control often follows predictions: predictive control has been highly successful in producing robust and practical solutions in many real-life, real-time applications. Adaptive prediction covers a variety of ways of adding 'intelligence' to predictive control techniques. Many different groups, with widely varying disciplinary backgrounds and approaches, are tackling the same problem from different angles; these groups are sometimes unaware of alternative approaches from other disciplines.
This book attempts to give a unified and comprehensive coverage of the principles and methods that these groups have developed. It avoids basing its descriptions on very complex mathematical formulations but still gives a rigorous exposure to the subject, and illustrates the theory with many practical examples. It is chiefly aimed at students, researchers and practitioners, but will also be accessible to the non-specialist.Note de contenu : contents:
Chapter 1: Introduction
Chapter 2: Process models
Chapter 3: Parameter estimation
Chapter 4: Some popular methods of prediction
Chapter 5: Adaptive prediction using transfer-function models
Chapter 6: Kalman filter and state-space approaches
Chapter 7: Orthogonal transformation and modelling of periodic series
Chapter 8: Modellong of nonlinear processes: an introduction
Chapter 9: Modelling of nonlinear processes using GMDH
Chapter 10: Modelling and prediction of nonlinear processes using neural networks
Chapter 11: Modelling and prediction of quasiperiodic series
Chapter 12: Predictive control (Part-I): input-output model based
Chapter 13: Predictive control (Part-II): state-space model based
Chapter 14: Smoothing and filtering
AppendicesExemplaires
Code-barres Cote Support Localisation Section Disponibilité N.Inventaire 922 25-07-22 Livre Bibliothèque de Génie Electrique- USTO Documentaires Exclu du prêt 922
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