|
" Dynamic feature, space modelling, filtering and self-tuning control of stochastic systems : "
Pieter W Otter
| Document Type
|
:
|
BL
|
| Record Number
|
:
|
714047
|
| Doc. No
|
:
|
b536196
|
| Main Entry
|
:
|
Pieter W Otter
|
| Title & Author
|
:
|
Dynamic feature, space modelling, filtering and self-tuning control of stochastic systems : : a systems approach with economic and social applications.\ Pieter W Otter
|
| Publication Statement
|
:
|
Berlin: Springer, 1985
|
| Series Statement
|
:
|
Lecture notes in economics and mathematical systems, 246.
|
| Page. NO
|
:
|
XIV, 177 Seiten : Diagramme.
|
| ISBN
|
:
|
0387156542
|
|
|
:
|
: 3540156542
|
|
|
:
|
: 9780387156545
|
|
|
:
|
: 9783540156543
|
| Contents
|
:
|
I: Introduction.- II: Elements of System Theory.- 2.1 Definitions of Dynamic Input-Output and State Space Models.- 2.2 Observability, Reconstructability and Controllability.- 2.3 Realization Theory.- 2.4 Canonical Forms.- 2.5 Stability.- A: Modelling, Filtering and Identification.- III: Feature Space Modelling.- 3.1 Introduction.- 3.2 A Linear Stochastic Dynamic Model with Feature Space.- 3.3 Models with Factor Space.- 3.4 Models with Canonical Space.- 3.5 Singular Value Decomposition and Canonical Correlation.- 3.6 Models with State Space: Balanced Realizations and Model Reduction.- 3.7 State Space Representation of Multivariate Time-Series.- 3.8 Regression Models with Parameter Space.- IV: Discrete Kalman Filtering.- 4.1 Derivation of the Filter.- 4.2 The Kaiman Filter applied to the Classical Linear Regression Model with Constant Parameters.- 4.3 The Kaiman Filter considered to be a Bayesian Estimation Procedure and some (Asymptotic) Properties.- 4.4 Stability of the Discrete Kaiman Filter and its Steady State.- 4.5 Prediction Errors (Innovations).- 4.6 Divergence of the Filter.- V: Parameter Identifiability, Prediction Error Estimation And Model Check.- 5.1 Parameter Identifiability.- 5.2 Stochastic Reconstructability and Parameter Identifiability.- 5.3 Prediction Error Estimation.- 5.4 A Non-Linear Minimization Procedure.- 5.5 Prediction Error Estimation of the (LSF) and (LRF) model.- 5.6 Prediction Error Estimation and Joereskog's LISREL-Procedure.- 5.7 Likelihood Ratio and Model Check.- 5.8 Structure Selection.- VI: Economic Applications.- 6.1 Regression.- 6.2 A Case Study.- 6.3 Univariate Time-Series Modelling.- 6.4 Multivariate Time-Series Modelling.- 6.5 Structural Modelling..- 6.6 Models with `Unobservables'.- B: Control.- VII: Self-Tuning Control.- 7.1 Introduction.- 7.2 Linear Quadratic Gaussian (LQG) Control.- 7.3 Minimum Variance (MV) Control.- 7.4 Duality of Estimation (Filtering) and Control.- 7.5 Estimation in Closed Loop.- 7.6 Self-Tuning Control.- 7.7 Self-Tuning Control of a Macro-Economic System.- Appendix: Solution of the Linear Matrix A X B + C = X and the Are.- References.
|
| Subject
|
:
|
Regelungssystem.
|
| Subject
|
:
|
Stochastischer Prozess.
|
| Subject
|
:
|
Zeitreihenanalyse.
|
| Added Entry
|
:
|
Pieter W Otter
|
| |