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Nonlinear control technology of vehicle chassis-by-wire system / / Wanzhong Zhao, Chunyan Wang
| Nonlinear control technology of vehicle chassis-by-wire system / / Wanzhong Zhao, Chunyan Wang |
| Autore | Zhao Wanzhong |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (248 pages) : illustrations (chiefly color) |
| Disciplina | 629.26 |
| Collana | Recent Advancements in Connected Autonomous Vehicle Technologies |
| Soggetto topico |
Automobiles - Chassis
Automobiles - Design and construction Automobiles - Lateral stability Nonlinear control theory |
| ISBN |
981-16-7321-7
981-16-7322-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction Nonlinear stability control of steer-by-wire system Consistency optimization control of electro-hydraulic composite brake-by-wire system Decoupling control of nonlinear inverse system for chassis-by-wire system Nonlinear rollover prevention integrated control of chassis-by-wire system |
| Record Nr. | UNINA-9910743372403321 |
Zhao Wanzhong
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| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Nonlinear filters : theory and applications / / Peyman Setoodeh, Saeid Habibi, Simon Haykin
| Nonlinear filters : theory and applications / / Peyman Setoodeh, Saeid Habibi, Simon Haykin |
| Autore | Setoodeh Peyman <1974-> |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2022] |
| Descrizione fisica | 1 online resource (307 pages) |
| Disciplina | 629.8/36 |
| Soggetto topico |
Nonlinear control theory
Digital filters (Mathematics) Signal processing - Digital techniques |
| ISBN |
1-119-07818-0
1-119-07815-6 1-119-07816-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright -- Contents -- List of Figures -- List of Table -- Preface -- Acknowledgments -- Acronyms -- Chapter 1 Introduction -- 1.1 State of a Dynamic System -- 1.2 State Estimation -- 1.3 Construals of Computing -- 1.4 Statistical Modeling -- 1.5 Vision for the Book -- Chapter 2 Observability -- 2.1 Introduction -- 2.2 State‐Space Model -- 2.3 The Concept of Observability -- 2.4 Observability of Linear Time‐Invariant Systems -- 2.4.1 Continuous‐Time LTI Systems -- 2.4.2 Discrete‐Time LTI Systems -- 2.4.3 Discretization of LTI Systems -- 2.5 Observability of Linear Time‐Varying Systems -- 2.5.1 Continuous‐Time LTV Systems -- 2.5.2 Discrete‐Time LTV Systems -- 2.5.3 Discretization of LTV Systems -- 2.6 Observability of Nonlinear Systems -- 2.6.1 Continuous‐Time Nonlinear Systems -- 2.6.2 Discrete‐Time Nonlinear Systems -- 2.6.3 Discretization of Nonlinear Systems -- 2.7 Observability of Stochastic Systems -- 2.8 Degree of Observability -- 2.9 Invertibility -- 2.10 Concluding Remarks -- Chapter 3 Observers -- 3.1 Introduction -- 3.2 Luenberger Observer -- 3.3 Extended Luenberger‐Type Observer -- 3.4 Sliding‐Mode Observer -- 3.5 Unknown‐Input Observer -- 3.6 Concluding Remarks -- Chapter 4 Bayesian Paradigm and Optimal Nonlinear Filtering -- 4.1 Introduction -- 4.2 Bayes' Rule -- 4.3 Optimal Nonlinear Filtering -- 4.4 Fisher Information -- 4.5 Posterior Cramér-Rao Lower Bound -- 4.6 Concluding Remarks -- Chapter 5 Kalman Filter -- 5.1 Introduction -- 5.2 Kalman Filter -- 5.3 Kalman Smoother -- 5.4 Information Filter -- 5.5 Extended Kalman Filter -- 5.6 Extended Information Filter -- 5.7 Divided‐Difference Filter -- 5.8 Unscented Kalman Filter -- 5.9 Cubature Kalman Filter -- 5.10 Generalized PID Filter -- 5.11 Gaussian‐Sum Filter -- 5.12 Applications -- 5.12.1 Information Fusion -- 5.12.2 Augmented Reality.
5.12.3 Urban Traffic Network -- 5.12.4 Cybersecurity of Power Systems -- 5.12.5 Incidence of Influenza -- 5.12.6 COVID‐19 Pandemic -- 5.13 Concluding Remarks -- Chapter 6 Particle Filter -- 6.1 Introduction -- 6.2 Monte Carlo Method -- 6.3 Importance Sampling -- 6.4 Sequential Importance Sampling -- 6.5 Resampling -- 6.6 Sample Impoverishment -- 6.7 Choosing the Proposal Distribution -- 6.8 Generic Particle Filter -- 6.9 Applications -- 6.9.1 Simultaneous Localization and Mapping -- 6.10 Concluding Remarks -- Chapter 7 Smooth Variable‐Structure Filter -- 7.1 Introduction -- 7.2 The Switching Gain -- 7.3 Stability Analysis -- 7.4 Smoothing Subspace -- 7.5 Filter Corrective Term for Linear Systems -- 7.6 Filter Corrective Term for Nonlinear Systems -- 7.7 Bias Compensation -- 7.8 The Secondary Performance Indicator -- 7.9 Second‐Order Smooth Variable Structure Filter -- 7.10 Optimal Smoothing Boundary Design -- 7.11 Combination of SVSF with Other Filters -- 7.12 Applications -- 7.12.1 Multiple Target Tracking -- 7.12.2 Battery State‐of‐Charge Estimation -- 7.12.3 Robotics -- 7.13 Concluding Remarks -- Chapter 8 Deep Learning -- 8.1 Introduction -- 8.2 Gradient Descent -- 8.3 Stochastic Gradient Descent -- 8.4 Natural Gradient Descent -- 8.5 Neural Networks -- 8.6 Backpropagation -- 8.7 Backpropagation Through Time -- 8.8 Regularization -- 8.9 Initialization -- 8.10 Convolutional Neural Network -- 8.11 Long Short‐Term Memory -- 8.12 Hebbian Learning -- 8.13 Gibbs Sampling -- 8.14 Boltzmann Machine -- 8.15 Autoencoder -- 8.16 Generative Adversarial Network -- 8.17 Transformer -- 8.18 Concluding Remarks -- Chapter 9 Deep Learning‐Based Filters -- 9.1 Introduction -- 9.2 Variational Inference -- 9.3 Amortized Variational Inference -- 9.4 Deep Kalman Filter -- 9.5 Backpropagation Kalman Filter -- 9.6 Differentiable Particle Filter. 9.7 Deep Rao-Blackwellized Particle Filter -- 9.8 Deep Variational Bayes Filter -- 9.9 Kalman Variational Autoencoder -- 9.10 Deep Variational Information Bottleneck -- 9.11 Wasserstein Distributionally Robust Kalman Filter -- 9.12 Hierarchical Invertible Neural Transport -- 9.13 Applications -- 9.13.1 Prediction of Drug Effect -- 9.13.2 Autonomous Driving -- 9.14 Concluding Remarks -- Chapter 10 Expectation Maximization -- 10.1 Introduction -- 10.2 Expectation Maximization Algorithm -- 10.3 Particle Expectation Maximization -- 10.4 Expectation Maximization for Gaussian Mixture Models -- 10.5 Neural Expectation Maximization -- 10.6 Relational Neural Expectation Maximization -- 10.7 Variational Filtering Expectation Maximization -- 10.8 Amortized Variational Filtering Expectation Maximization -- 10.9 Applications -- 10.9.1 Stochastic Volatility -- 10.9.2 Physical Reasoning -- 10.9.3 Speech, Music, and Video Modeling -- 10.10 Concluding Remarks -- Chapter 11 Reinforcement Learning‐Based Filter -- 11.1 Introduction -- 11.2 Reinforcement Learning -- 11.3 Variational Inference as Reinforcement Learning -- 11.4 Application -- 11.4.1 Battery State‐of‐Charge Estimation -- 11.5 Concluding Remarks -- Chapter 12 Nonparametric Bayesian Models -- 12.1 Introduction -- 12.2 Parametric vs Nonparametric Models -- 12.3 Measure‐Theoretic Probability -- 12.4 Exchangeability -- 12.5 Kolmogorov Extension Theorem -- 12.6 Extension of Bayesian Models -- 12.7 Conjugacy -- 12.8 Construction of Nonparametric Bayesian Models -- 12.9 Posterior Computability -- 12.10 Algorithmic Sufficiency -- 12.11 Applications -- 12.11.1 Multiple Object Tracking -- 12.11.2 Data‐Driven Probabilistic Optimal Power Flow -- 12.11.3 Analyzing Single‐Molecule Tracks -- 12.12 Concluding Remarks -- References -- Index -- EULA. |
| Record Nr. | UNINA-9910555153203321 |
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Setoodeh Peyman <1974->
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| Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Nonlinear filters : theory and applications / / Peyman Setoodeh, Saeid Habibi, Simon Haykin
| Nonlinear filters : theory and applications / / Peyman Setoodeh, Saeid Habibi, Simon Haykin |
| Autore | Setoodeh Peyman <1974-> |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2022] |
| Descrizione fisica | 1 online resource (307 pages) |
| Disciplina | 629.8/36 |
| Soggetto topico |
Nonlinear control theory
Digital filters (Mathematics) Signal processing - Digital techniques |
| ISBN |
1-119-07818-0
1-119-07815-6 1-119-07816-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright -- Contents -- List of Figures -- List of Table -- Preface -- Acknowledgments -- Acronyms -- Chapter 1 Introduction -- 1.1 State of a Dynamic System -- 1.2 State Estimation -- 1.3 Construals of Computing -- 1.4 Statistical Modeling -- 1.5 Vision for the Book -- Chapter 2 Observability -- 2.1 Introduction -- 2.2 State‐Space Model -- 2.3 The Concept of Observability -- 2.4 Observability of Linear Time‐Invariant Systems -- 2.4.1 Continuous‐Time LTI Systems -- 2.4.2 Discrete‐Time LTI Systems -- 2.4.3 Discretization of LTI Systems -- 2.5 Observability of Linear Time‐Varying Systems -- 2.5.1 Continuous‐Time LTV Systems -- 2.5.2 Discrete‐Time LTV Systems -- 2.5.3 Discretization of LTV Systems -- 2.6 Observability of Nonlinear Systems -- 2.6.1 Continuous‐Time Nonlinear Systems -- 2.6.2 Discrete‐Time Nonlinear Systems -- 2.6.3 Discretization of Nonlinear Systems -- 2.7 Observability of Stochastic Systems -- 2.8 Degree of Observability -- 2.9 Invertibility -- 2.10 Concluding Remarks -- Chapter 3 Observers -- 3.1 Introduction -- 3.2 Luenberger Observer -- 3.3 Extended Luenberger‐Type Observer -- 3.4 Sliding‐Mode Observer -- 3.5 Unknown‐Input Observer -- 3.6 Concluding Remarks -- Chapter 4 Bayesian Paradigm and Optimal Nonlinear Filtering -- 4.1 Introduction -- 4.2 Bayes' Rule -- 4.3 Optimal Nonlinear Filtering -- 4.4 Fisher Information -- 4.5 Posterior Cramér-Rao Lower Bound -- 4.6 Concluding Remarks -- Chapter 5 Kalman Filter -- 5.1 Introduction -- 5.2 Kalman Filter -- 5.3 Kalman Smoother -- 5.4 Information Filter -- 5.5 Extended Kalman Filter -- 5.6 Extended Information Filter -- 5.7 Divided‐Difference Filter -- 5.8 Unscented Kalman Filter -- 5.9 Cubature Kalman Filter -- 5.10 Generalized PID Filter -- 5.11 Gaussian‐Sum Filter -- 5.12 Applications -- 5.12.1 Information Fusion -- 5.12.2 Augmented Reality.
5.12.3 Urban Traffic Network -- 5.12.4 Cybersecurity of Power Systems -- 5.12.5 Incidence of Influenza -- 5.12.6 COVID‐19 Pandemic -- 5.13 Concluding Remarks -- Chapter 6 Particle Filter -- 6.1 Introduction -- 6.2 Monte Carlo Method -- 6.3 Importance Sampling -- 6.4 Sequential Importance Sampling -- 6.5 Resampling -- 6.6 Sample Impoverishment -- 6.7 Choosing the Proposal Distribution -- 6.8 Generic Particle Filter -- 6.9 Applications -- 6.9.1 Simultaneous Localization and Mapping -- 6.10 Concluding Remarks -- Chapter 7 Smooth Variable‐Structure Filter -- 7.1 Introduction -- 7.2 The Switching Gain -- 7.3 Stability Analysis -- 7.4 Smoothing Subspace -- 7.5 Filter Corrective Term for Linear Systems -- 7.6 Filter Corrective Term for Nonlinear Systems -- 7.7 Bias Compensation -- 7.8 The Secondary Performance Indicator -- 7.9 Second‐Order Smooth Variable Structure Filter -- 7.10 Optimal Smoothing Boundary Design -- 7.11 Combination of SVSF with Other Filters -- 7.12 Applications -- 7.12.1 Multiple Target Tracking -- 7.12.2 Battery State‐of‐Charge Estimation -- 7.12.3 Robotics -- 7.13 Concluding Remarks -- Chapter 8 Deep Learning -- 8.1 Introduction -- 8.2 Gradient Descent -- 8.3 Stochastic Gradient Descent -- 8.4 Natural Gradient Descent -- 8.5 Neural Networks -- 8.6 Backpropagation -- 8.7 Backpropagation Through Time -- 8.8 Regularization -- 8.9 Initialization -- 8.10 Convolutional Neural Network -- 8.11 Long Short‐Term Memory -- 8.12 Hebbian Learning -- 8.13 Gibbs Sampling -- 8.14 Boltzmann Machine -- 8.15 Autoencoder -- 8.16 Generative Adversarial Network -- 8.17 Transformer -- 8.18 Concluding Remarks -- Chapter 9 Deep Learning‐Based Filters -- 9.1 Introduction -- 9.2 Variational Inference -- 9.3 Amortized Variational Inference -- 9.4 Deep Kalman Filter -- 9.5 Backpropagation Kalman Filter -- 9.6 Differentiable Particle Filter. 9.7 Deep Rao-Blackwellized Particle Filter -- 9.8 Deep Variational Bayes Filter -- 9.9 Kalman Variational Autoencoder -- 9.10 Deep Variational Information Bottleneck -- 9.11 Wasserstein Distributionally Robust Kalman Filter -- 9.12 Hierarchical Invertible Neural Transport -- 9.13 Applications -- 9.13.1 Prediction of Drug Effect -- 9.13.2 Autonomous Driving -- 9.14 Concluding Remarks -- Chapter 10 Expectation Maximization -- 10.1 Introduction -- 10.2 Expectation Maximization Algorithm -- 10.3 Particle Expectation Maximization -- 10.4 Expectation Maximization for Gaussian Mixture Models -- 10.5 Neural Expectation Maximization -- 10.6 Relational Neural Expectation Maximization -- 10.7 Variational Filtering Expectation Maximization -- 10.8 Amortized Variational Filtering Expectation Maximization -- 10.9 Applications -- 10.9.1 Stochastic Volatility -- 10.9.2 Physical Reasoning -- 10.9.3 Speech, Music, and Video Modeling -- 10.10 Concluding Remarks -- Chapter 11 Reinforcement Learning‐Based Filter -- 11.1 Introduction -- 11.2 Reinforcement Learning -- 11.3 Variational Inference as Reinforcement Learning -- 11.4 Application -- 11.4.1 Battery State‐of‐Charge Estimation -- 11.5 Concluding Remarks -- Chapter 12 Nonparametric Bayesian Models -- 12.1 Introduction -- 12.2 Parametric vs Nonparametric Models -- 12.3 Measure‐Theoretic Probability -- 12.4 Exchangeability -- 12.5 Kolmogorov Extension Theorem -- 12.6 Extension of Bayesian Models -- 12.7 Conjugacy -- 12.8 Construction of Nonparametric Bayesian Models -- 12.9 Posterior Computability -- 12.10 Algorithmic Sufficiency -- 12.11 Applications -- 12.11.1 Multiple Object Tracking -- 12.11.2 Data‐Driven Probabilistic Optimal Power Flow -- 12.11.3 Analyzing Single‐Molecule Tracks -- 12.12 Concluding Remarks -- References -- Index -- EULA. |
| Record Nr. | UNINA-9910831039103321 |
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Setoodeh Peyman <1974->
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| Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Nonlinear systems : analysis, stability, and control / Shankar Sastry
| Nonlinear systems : analysis, stability, and control / Shankar Sastry |
| Autore | Sastry, Shankar |
| Pubbl/distr/stampa | New York : Springer, c1999 |
| Descrizione fisica | xxv, 667 p. : ill. ; 25 cm |
| Disciplina | 629.836 |
| Collana | Interdisciplinary applied mathematics ; v. 10 |
| Soggetto topico |
Automatic control
Nonlinear control theory Adaptive control systems |
| ISBN | 0387985131 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISALENTO-991001106859707536 |
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Sastry, Shankar
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| New York : Springer, c1999 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
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Nonlinear systems : modeling, estimation, and stability / / edited by Walter Legnani, Terry E. Moschandreou
| Nonlinear systems : modeling, estimation, and stability / / edited by Walter Legnani, Terry E. Moschandreou |
| Pubbl/distr/stampa | London, England : , : IntechOpen, , [2020] |
| Descrizione fisica | 1 online resource (286 pages) : illustrations |
| Disciplina | 629.836 |
| Soggetto topico |
Nonlinear control theory
Nonlinear systems |
| ISBN | 1-78985-472-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Nonlinear Systems |
| Record Nr. | UNINA-9910409753403321 |
| London, England : , : IntechOpen, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Nonlinear Systems : Design, Analysis, Estimation and Control / / Christos Volos, Tim Burg, Dongbin Lee, editors
| Nonlinear Systems : Design, Analysis, Estimation and Control / / Christos Volos, Tim Burg, Dongbin Lee, editors |
| Pubbl/distr/stampa | Rijeka, Croatia : , : IntechOpen, , [2016] |
| Descrizione fisica | 1 online resource (364 pages) : illustrations |
| Disciplina | 629.836 |
| Soggetto topico | Nonlinear control theory |
| ISBN |
953-51-4173-2
953-51-2715-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti |
Nonlinear systems
Nonlinear Systems - Design, Analysis, Estimation and Control |
| Record Nr. | UNINA-9910169212203321 |
| Rijeka, Croatia : , : IntechOpen, , [2016] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Nonlinear systems stability analysis [[electronic resource] ] : Lyapunov-based approach / / Seyed Kamaleddin Yadavar Nikravesh
| Nonlinear systems stability analysis [[electronic resource] ] : Lyapunov-based approach / / Seyed Kamaleddin Yadavar Nikravesh |
| Autore | Nikravesh Seyed Kamaleddin Yadavar |
| Pubbl/distr/stampa | Boca Raton, : CRC Press, 2013 |
| Descrizione fisica | 1 online resource (313 p.) |
| Disciplina | 515.392 |
| Soggetto topico |
Lyapunov stability
Nonlinear control theory |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-4665-6929-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Contents; Preface; Acknowledgments; Chapter 1 - Basic Concepts; Chapter 2 - Stability Analysis of Autonomous Systems; Chapter 3 - Stability Analysis of Nonautonomous Systems; Chapter 4 - Stability Analysis of Time-Delayed Systems; Chapter 5 - An Introduction to Stability Analysis of Linguistic Fuzzy Dynamic Systems; References; Appendix A1: Application of VLF in Nonlinear Power System Stabilization; Appendix A2: Proof of Theorem 3.8; Appendix A3: Stability Analysis of Nonlinear Systems via Δ-Homogeneous Approximation
Appendix A4: Stabilization of Model Predictive Control of Nonlinear Time-Delayed SystemsAppendix A5: Some New Notions for Symmetric Behavior of Matrices and Related Theorems; Back Cover |
| Record Nr. | UNINA-9910462600903321 |
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Nikravesh Seyed Kamaleddin Yadavar
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| Boca Raton, : CRC Press, 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Nonlinear systems stability analysis [[electronic resource] ] : Lyapunov-based approach / / Seyed Kamaleddin Yadavar Nikravesh
| Nonlinear systems stability analysis [[electronic resource] ] : Lyapunov-based approach / / Seyed Kamaleddin Yadavar Nikravesh |
| Autore | Nikravesh Seyed Kamaleddin Yadavar |
| Pubbl/distr/stampa | Boca Raton, : CRC Press, 2013 |
| Descrizione fisica | 1 online resource (313 p.) |
| Disciplina | 515.392 |
| Soggetto topico |
Lyapunov stability
Nonlinear control theory |
| ISBN |
1-315-21599-3
1-138-07277-X 1-351-83188-7 1-4665-6929-8 |
| Classificazione | SCI013060TEC007000TEC032000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Contents; Preface; Acknowledgments; Chapter 1 - Basic Concepts; Chapter 2 - Stability Analysis of Autonomous Systems; Chapter 3 - Stability Analysis of Nonautonomous Systems; Chapter 4 - Stability Analysis of Time-Delayed Systems; Chapter 5 - An Introduction to Stability Analysis of Linguistic Fuzzy Dynamic Systems; References; Appendix A1: Application of VLF in Nonlinear Power System Stabilization; Appendix A2: Proof of Theorem 3.8; Appendix A3: Stability Analysis of Nonlinear Systems via Δ-Homogeneous Approximation
Appendix A4: Stabilization of Model Predictive Control of Nonlinear Time-Delayed SystemsAppendix A5: Some New Notions for Symmetric Behavior of Matrices and Related Theorems; Back Cover |
| Record Nr. | UNINA-9910786036603321 |
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Nikravesh Seyed Kamaleddin Yadavar
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| Boca Raton, : CRC Press, 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Nonlinear systems stability analysis : Lyapunov-based approach / / Seyed Kamaleddin Yadavar Nikravesh
| Nonlinear systems stability analysis : Lyapunov-based approach / / Seyed Kamaleddin Yadavar Nikravesh |
| Autore | Nikravesh Seyed Kamaleddin Yadavar |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Boca Raton, : CRC Press, 2013 |
| Descrizione fisica | 1 online resource (313 p.) |
| Disciplina | 515.392 |
| Soggetto topico |
Lyapunov stability
Nonlinear control theory |
| ISBN |
1-315-21599-3
1-138-07277-X 1-351-83188-7 1-4665-6929-8 |
| Classificazione | SCI013060TEC007000TEC032000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Contents; Preface; Acknowledgments; Chapter 1 - Basic Concepts; Chapter 2 - Stability Analysis of Autonomous Systems; Chapter 3 - Stability Analysis of Nonautonomous Systems; Chapter 4 - Stability Analysis of Time-Delayed Systems; Chapter 5 - An Introduction to Stability Analysis of Linguistic Fuzzy Dynamic Systems; References; Appendix A1: Application of VLF in Nonlinear Power System Stabilization; Appendix A2: Proof of Theorem 3.8; Appendix A3: Stability Analysis of Nonlinear Systems via Δ-Homogeneous Approximation
Appendix A4: Stabilization of Model Predictive Control of Nonlinear Time-Delayed SystemsAppendix A5: Some New Notions for Symmetric Behavior of Matrices and Related Theorems; Back Cover |
| Record Nr. | UNINA-9910818698503321 |
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Nikravesh Seyed Kamaleddin Yadavar
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| Boca Raton, : CRC Press, 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Nonlinear time-delay systems : a geometric approach / / Claudia Califano, Claude H. Moog
| Nonlinear time-delay systems : a geometric approach / / Claudia Califano, Claude H. Moog |
| Autore | Califano Claudia |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (x, 105 pages) |
| Disciplina | 629.83 |
| Collana | SpringerBriefs in Electrical and Computer Engineering. Control, Automation and Robotics |
| Soggetto topico |
Time delay systems
Nonlinear control theory |
| ISBN | 3-030-72026-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- 1 Preliminaries -- 1.1 The Class of Systems -- 1.2 Integrability -- 1.3 Geometric Behavior -- 1.4 Accessibility and Observability Properties -- 1.5 Notation -- 1.6 Recalls on Non-commutative Algebra -- 2 Geometric Tools for Time-Delay Systems -- 2.1 The Initialization of the Time-Delay System Versus the Initialization of the Delay-Free Extended System -- 2.2 Non-independence of the Inputs of the Extended System -- 2.3 The Differential Form Representation -- 2.4 Generalized Lie Derivative and Generalized Lie Bracket -- 2.5 Some Remarks on the Polynomial Lie Bracket -- 2.6 The Action of Changes of Coordinates -- 2.7 The Action of Static State Feedback Laws -- 2.8 Problems -- 3 The Geometric Framework-Results on Integrability -- 3.1 Some Remarks on Left and Right Integrability -- 3.2 Integrability of a Right-Submodule -- 3.2.1 Involutivity of a Right-Submodule Versus its Integrability -- 3.2.2 Smallest 0-Integrable Right-Submodule Containing Δ(δ] -- 3.2.3 p-Integrability -- 3.2.4 Bicausal Change of Coordinates -- 3.3 Integrability of a Left-Submodule -- 3.4 Problems -- 4 Accessibility of Nonlinear Time-Delay Systems -- 4.1 The Accessibility Submodules in the Delay Context -- 4.2 A Canonical Decomposition with Respect to Accessibility -- 4.3 On the Computation of the Accessibility Submodules -- 4.4 On t-Accessibility of Time-Delay Systems -- 4.5 Problems -- 5 Observability -- 5.1 Decomposing with Respect to Observability -- 5.1.1 The Case of Autonomous Systems -- 5.2 On Regular Observability for Time-Delay Systems -- 5.3 Problems -- 6 Applications of Integrability -- 6.1 Characterization of the Chained Form with Delays -- 6.2 Input-Output Feedback Linearization -- 6.2.1 Introductory Examples -- 6.2.2 Static Output Feedback Solutions -- 6.2.3 Hybrid Output Feedback Solutions -- 6.3 Input-State Linearization.
6.3.1 Introductory Example -- 6.3.2 Solution -- 6.4 Normal Form -- 6.5 Problems -- Series Editor Biographies -- References. |
| Record Nr. | UNINA-9910483435903321 |
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Califano Claudia
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| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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