Identification of Continuous-time Models from Sampled Data

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Garnier, Hugues (Επιμελητής έκδοσης), Wang, Liuping (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: London : Springer London, 2008.
• Σειρά: Advances in Industrial Control,
• Θέματα: Engineering.; Logic design.; Computer simulation.; Probabilities.; Vibration.; Dynamical systems.; Dynamics.; Control engineering.; Control.; Logic Design.; Probability Theory and Stochastic Processes.; Simulation and Modeling.; Vibration, Dynamical Systems, Control.; Signal, Image and Speech Processing.

System identification is an established field in the area of system analysis and control. It aims to determine particular models for dynamical systems based on observed inputs and outputs. Although dynamical systems in the physical world are naturally described in the continuous-time domain, most sy...

Πίνακας περιεχομένων:

• Direct Identification of Continuous-time Models from Sampled Data: Issues, Basic Solutions and Relevance
• Estimation of Continuous-time Stochastic System Parameters
• Robust Identification of Continuous-time Systems from Sampled Data
• Refined Instrumental Variable Identification of Continuous-time Hybrid Box-Jenkins Models
• Instrumental Variable Methods for Closed-loop Continuous-time Model Identification
• Model Order Identification for Continuous-time Models
• Estimation of the Parameters of Continuous-time Systems Using Data Compression
• Frequency-domain Approach to Continuous-time System Identification: Some Practical Aspects
• The CONTSID Toolbox: A Software Support for Data-based Continuous-time Modelling
• Subspace-based Continuous-time Identification
• Process Parameter and Delay Estimation from Non-uniformly Sampled Data
• Iterative Methods for Identification of Multiple-input Continuous-time Systems with Unknown Time Delays
• Closed-loop Parametric Identification for Continuous-time Linear Systems via New Algebraic Techniques
• Continuous-time Model Identification Using Spectrum Analysis with Passivity-preserving Model Reduction.