Stochastic Modelling and Control:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Dordrecht
Springer Netherlands
1985
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| Schriftenreihe: | Monographs on Statistics and Applied Probability
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| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | This book aims to provide a unified treatment of input/output modelling and of control for discrete-time dynamical systems subject to random disturbances. The results presented are of wide applica bility in control engineering, operations research, econometric modelling and many other areas. There are two distinct approaches to mathematical modelling of physical systems: a direct analysis of the physical mechanisms that comprise the process, or a 'black box' approach based on analysis of input/output data. The second approach is adopted here, although of course the properties ofthe models we study, which within the limits of linearity are very general, are also relevant to the behaviour of systems represented by such models, however they are arrived at. The type of system we are interested in is a discrete-time or sampled-data system where the relation between input and output is (at least approximately) linear and where additive random dis turbances are also present, so that the behaviour of the system must be investigated by statistical methods. After a preliminary chapter summarizing elements of probability and linear system theory, we introduce in Chapter 2 some general linear stochastic models, both in input/output and state-space form. Chapter 3 concerns filtering theory: estimation of the state of a dynamical system from noisy observations. As well as being an important topic in its own right, filtering theory provides the link, via the so-called innovations representation, between input/output models (as identified by data analysis) and state-space models, as required for much contemporary control theory |
| Beschreibung: | 1 Online-Ressource (XII, 394 p) |
| ISBN: | 9789400948280 |
| DOI: | 10.1007/978-94-009-4828-0 |
Internformat
MARC
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| 500 | |a This book aims to provide a unified treatment of input/output modelling and of control for discrete-time dynamical systems subject to random disturbances. The results presented are of wide applica bility in control engineering, operations research, econometric modelling and many other areas. There are two distinct approaches to mathematical modelling of physical systems: a direct analysis of the physical mechanisms that comprise the process, or a 'black box' approach based on analysis of input/output data. The second approach is adopted here, although of course the properties ofthe models we study, which within the limits of linearity are very general, are also relevant to the behaviour of systems represented by such models, however they are arrived at. The type of system we are interested in is a discrete-time or sampled-data system where the relation between input and output is (at least approximately) linear and where additive random dis turbances are also present, so that the behaviour of the system must be investigated by statistical methods. After a preliminary chapter summarizing elements of probability and linear system theory, we introduce in Chapter 2 some general linear stochastic models, both in input/output and state-space form. Chapter 3 concerns filtering theory: estimation of the state of a dynamical system from noisy observations. As well as being an important topic in its own right, filtering theory provides the link, via the so-called innovations representation, between input/output models (as identified by data analysis) and state-space models, as required for much contemporary control theory | ||
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Datensatz im Suchindex
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|---|---|
| any_adam_object | |
| author | Davis, Mark H. A. 1945-2020 |
| author_GND | (DE-588)120781611 (DE-588)110538781 |
| author_facet | Davis, Mark H. A. 1945-2020 |
| author_role | aut |
| author_sort | Davis, Mark H. A. 1945-2020 |
| author_variant | m h a d mha mhad |
| building | Verbundindex |
| bvnumber | BV042423731 |
| classification_tum | MAT 000 |
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| dewey-full | 50 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 050 - General serial publications |
| dewey-raw | 50 |
| dewey-search | 50 |
| dewey-sort | 250 |
| dewey-tens | 050 - General serial publications |
| discipline | Allgemeine Naturwissenschaft Mathematik |
| doi_str_mv | 10.1007/978-94-009-4828-0 |
| format | Electronic eBook |
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| indexdate | 2024-07-10T01:21:14Z |
| institution | BVB |
| isbn | 9789400948280 |
| language | English |
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| series2 | Monographs on Statistics and Applied Probability |
| spelling | Davis, Mark H. A. 1945-2020 Verfasser (DE-588)120781611 aut Stochastic Modelling and Control by M. H. A. Davis, R. B. Vinter Dordrecht Springer Netherlands 1985 1 Online-Ressource (XII, 394 p) txt rdacontent c rdamedia cr rdacarrier Monographs on Statistics and Applied Probability This book aims to provide a unified treatment of input/output modelling and of control for discrete-time dynamical systems subject to random disturbances. The results presented are of wide applica bility in control engineering, operations research, econometric modelling and many other areas. There are two distinct approaches to mathematical modelling of physical systems: a direct analysis of the physical mechanisms that comprise the process, or a 'black box' approach based on analysis of input/output data. The second approach is adopted here, although of course the properties ofthe models we study, which within the limits of linearity are very general, are also relevant to the behaviour of systems represented by such models, however they are arrived at. The type of system we are interested in is a discrete-time or sampled-data system where the relation between input and output is (at least approximately) linear and where additive random dis turbances are also present, so that the behaviour of the system must be investigated by statistical methods. After a preliminary chapter summarizing elements of probability and linear system theory, we introduce in Chapter 2 some general linear stochastic models, both in input/output and state-space form. Chapter 3 concerns filtering theory: estimation of the state of a dynamical system from noisy observations. As well as being an important topic in its own right, filtering theory provides the link, via the so-called innovations representation, between input/output models (as identified by data analysis) and state-space models, as required for much contemporary control theory Science (General) Science, general Naturwissenschaft Lineares stochastisches System (DE-588)4167737-7 gnd rswk-swf Stochastische Kontrolltheorie (DE-588)4263657-7 gnd rswk-swf Stochastisches Modell (DE-588)4057633-4 gnd rswk-swf Stochastisches Modell (DE-588)4057633-4 s 1\p DE-604 Stochastische Kontrolltheorie (DE-588)4263657-7 s 2\p DE-604 Lineares stochastisches System (DE-588)4167737-7 s 3\p DE-604 Vinter, Richard B. 1948- Sonstige (DE-588)110538781 oth Erscheint auch als 978-94-010-8640-0 Druck-Ausgabe https://doi.org/10.1007/978-94-009-4828-0 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Davis, Mark H. A. 1945-2020 Stochastic Modelling and Control Science (General) Science, general Naturwissenschaft Lineares stochastisches System (DE-588)4167737-7 gnd Stochastische Kontrolltheorie (DE-588)4263657-7 gnd Stochastisches Modell (DE-588)4057633-4 gnd |
| subject_GND | (DE-588)4167737-7 (DE-588)4263657-7 (DE-588)4057633-4 |
| title | Stochastic Modelling and Control |
| title_auth | Stochastic Modelling and Control |
| title_exact_search | Stochastic Modelling and Control |
| title_full | Stochastic Modelling and Control by M. H. A. Davis, R. B. Vinter |
| title_fullStr | Stochastic Modelling and Control by M. H. A. Davis, R. B. Vinter |
| title_full_unstemmed | Stochastic Modelling and Control by M. H. A. Davis, R. B. Vinter |
| title_short | Stochastic Modelling and Control |
| title_sort | stochastic modelling and control |
| topic | Science (General) Science, general Naturwissenschaft Lineares stochastisches System (DE-588)4167737-7 gnd Stochastische Kontrolltheorie (DE-588)4263657-7 gnd Stochastisches Modell (DE-588)4057633-4 gnd |
| topic_facet | Science (General) Science, general Naturwissenschaft Lineares stochastisches System Stochastische Kontrolltheorie Stochastisches Modell |
| url | https://doi.org/10.1007/978-94-009-4828-0 |
| work_keys_str_mv | AT davismarkha stochasticmodellingandcontrol AT vinterrichardb stochasticmodellingandcontrol |