Modelos de función de transferencia
Los modelos de función de transferencia describen la relación entre las entradas y salidas de un sistema utilizando una relación de polinomios. El orden del modelo es igual al orden del denominador polinomial. Las raíces del denominador polinomial se conocen como los polos del modelo. Las raíces del polinomio del numerador se conocen como los ceros del modelo.
Los parámetros de un modelo de función de transferencia son los polos, ceros y retardos de transporte.
En tiempo continuo, un modelo de función de transferencia tiene el siguiente formato:
En este caso, Y(s), U(s) y E(s) representan las transformadas de Laplace de la salida, la entrada y el ruido, respectivamente. num(s) y den(s) representan numerador y denominador polinomiales que definen la relación entre la entrada y la salida.
Para obtener más información, consulte What Are Transfer Function Models?
Apps
| System Identification | Identificar modelos de sistemas dinámicos a partir de datos medidos. |
Funciones
Temas
Conceptos básicos del modelo de función de transferencia
- What Are Transfer Function Models?
Transfer function models describe the relationship between the inputs and outputs of a system using a ratio of polynomials. - Estimate Transfer Function Models in the System Identification App
Use the app to set model configuration and estimation options for estimating a transfer function model. - Estimate Transfer Function Models at the Command Line
General workflow for estimating transfer function models at the command line. - Data Supported by Transfer Function Models
Characteristics of estimation data for transfer function identification.
Realizar la estimación de modelos de función de transferencia
- Estimate Transfer Function Models by Specifying Number of Poles
This example shows how to identify a transfer function containing a specified number of poles for given data. - Estimate Transfer Function Models with Transport Delay to Fit Given Frequency-Response Data
This example shows how to identify a transfer function to fit a given frequency response data (FRD) containing additional phase roll off induced by input delay. - Estimate Transfer Function Models with Prior Knowledge of Model Structure and Constraints
This example shows how to estimate a transfer function model when the structure of the expected model is known and apply constraints to the numerator and denominator coefficients. - Estimate Transfer Functions with Delays
This example shows how to estimate transfer function models with I/O delays. - Estimate Transfer Function Models with Unknown Transport Delays
This example shows how to estimate a transfer function model with unknown transport delays and apply an upper bound on the unknown transport delays.
Resolver problemas del dominio de la frecuencia
- Troubleshoot Frequency-Domain Identification of Transfer Function Models
Improve frequency-domain model estimation by preprocessing data and applying frequency-dependent weighting filters.
Inicialización de modelos y parámetros de estructura
- Transfer Function Structure Specification
Specify the values and constraints for the numerator, denominator and transport delays. - Specifying Initial Conditions for Iterative Estimation of Transfer Functions
Specify how initial conditions are handled during model estimation in the app and at the command line.
Ejemplos destacados
Estimating Transfer Function Models for a Heat Exchanger
Estimate a transfer function from measured signal data.
Estimating Transfer Function Models for a Boost Converter
Estimate a transfer function from frequency response data.
