| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNINA9910818728503321 |
|
|
Autore |
Dong Hongli <1977-> |
|
|
Titolo |
Filtering, control, and fault detection with randomly occurring incomplete information / / Hongli Dong, Zidong Wang, Huijun Gao |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Chichester, West Sussex, U.K., : Wiley, c2013 |
|
|
|
|
|
|
|
ISBN |
|
1-118-65097-2 |
1-118-65098-0 |
1-118-65096-4 |
|
|
|
|
|
|
|
|
Edizione |
[1st ed.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (283 p.) |
|
|
|
|
|
|
Altri autori (Persone) |
|
WangZidong <1966-> |
GaoHuijun |
|
|
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Automatic control |
Electric filters, Digital |
Fault tolerance (Engineering) |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Note generali |
|
Description based upon print version of record. |
|
|
|
|
|
|
Nota di bibliografia |
|
Includes bibliographical references and index. |
|
|
|
|
|
|
Nota di contenuto |
|
FILTERING, CONTROL AND FAULT DETECTION WITH RANDOMLY OCCURRING INCOMPLETE INFORMATION; Contents; Preface; Acknowledgments; List of Abbreviations; List of Notations; 1 Introduction; 1.1 Background, Motivations, and Research Problems; 1.1.1 Randomly Occurring Incomplete Information; 1.1.2 The Analysis and Synthesis of Nonlinear Stochastic Systems; 1.1.3 Distributed Filtering over Sensor Networks; 1.2 Outline; 2 Variance-Constrained Finite-Horizon Filtering and Control with Saturations; 2.1 Problem Formulation for Finite-Horizon Filter Design; 2.2 Analysis of H and Covariance Performances |
2.2.1 H Performance2.2.2 Variance Analysis; 2.3 Robust Finite-Horizon Filter Design; 2.4 Robust H Finite-Horizon Control with Sensor and Actuator Saturations; 2.4.1 Problem Formulation; 2.4.2 Main Results; 2.5 Illustrative Examples; 2.5.1 Example 1; 2.5.2 Example 2; 2.6 Summary; 3 Filtering and Control with Stochastic Delays and Missing Measurements; 3.1 Problem Formulation for Robust Filter Design; 3.2 Robust H Filtering Performance Analysis; 3.3 Robust H Filter Design; 3.4 Robust H Fuzzy Control; 3.4.1 Problem Formulation; 3.4.2 |
|
|
|
|
|
|
|
|
|
|
|
Performance Analysis; 3.4.3 Controller Design |
3.5 Illustrative Examples3.5.1 Example 1; 3.5.2 Example 2; 3.5.3 Example 3; 3.6 Summary; 4 Filtering and Control for Systems with Repeated Scalar Nonlinearities; 4.1 Problem Formulation for Filter Design; 4.1.1 The Physical Plant; 4.1.2 The Communication Link; 4.1.3 The Filter; 4.1.4 The Filtering Error Dynamics; 4.2 Filtering Performance Analysis; 4.3 Filter Design; 4.4 Observer-Based H Control with Multiple Packet Losses; 4.4.1 Problem Formulation; 4.4.2 Main Results; 4.5 Illustrative Examples; 4.5.1 Example 1; 4.5.2 Example 2; 4.5.3 Example 3; 4.5.4 Example 4; 4.6 Summary |
5 Filtering and Fault Detection for Markov Systems with Varying Nonlinearities5.1 Problem Formulation for Robust H° Filter Design; 5.2 Performance Analysis of Robust H° Filter; 5.3 Design of Robust H° Filters; 5.4 Fault Detection with Sensor Saturations and Randomly Varying Nonlinearities; 5.4.1 Problem Formulation; 5.4.2 Main Results; 5.5 Illustrative Examples; 5.5.1 Example 1; 5.5.2 Example 2; 5.5.3 Example 3; 5.5.4 Example 4; 5.6 Summary; 6 Quantized Fault Detection with Mixed Time-Delays and Packet Dropouts; 6.1 Problem Formulation for Fault Detection Filter Design; 6.2 Main Results |
6.3 Fuzzy-Model-Based Robust Fault Detection6.3.1 Problem Formulation; 6.3.2 Main Results; 6.4 Illustrative Examples; 6.4.1 Example 1; 6.4.2 Example 2; 6.5 Summary; 7 Distributed Filtering over Sensor Networks with Saturations; 7.1 Problem Formulation; 7.2 Main Results; 7.3 An Illustrative Example; 7.4 Summary; 8 Distributed Filtering with Quantization Errors: The Finite-Horizon Case; 8.1 Problem Formulation; 8.2 Main Results; 8.3 An Illustrative Example; 8.4 Summary; 9 Distributed Filtering for Markov Jump Nonlinear Time-Delay Systems; 9.1 Problem Formulation |
9.1.1 Deficient Statistics of Markovian Modes Transitions |
|
|
|
|
|
|
Sommario/riassunto |
|
In the context of systems and control, incomplete information refers to a dynamical system in which knowledge about the system states is limited due to the difficulties in modelling complexity in a quantitative way. The well-known types of incomplete information include parameter uncertainties and norm-bounded nonlinearities. Recently, in response to the development of network technologies, the phenomenon of randomly occurring incomplete information has become more and more prevalent. Filtering, Control and Fault Detection with Randomly Occurring Incomplete Information reflects |
|
|
|
|
|
|
|
| |