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Modelos básicos

Modelos frecuentes de sistemas lineales, como funciones de transferencia y modelos de espacio de estados

Los modelos numéricos lineales invariantes con el tiempo (LTI) son bloques de creación básicos que se utilizan para representar sistemas lineales. Los objetos de modelo numéricos LTI permiten almacenar sistemas dinámicos en representaciones de uso frecuente. Por ejemplo, los modelos tf representan las funciones de transferencia en términos de los coeficientes de los polinomios de su numerador y denominador, y los modelos ss representan sistemas LTI en términos de matrices de espacio de estados. También existen tipos de modelos LTI especializados para representar controladores PID en términos de sus coeficientes proporcionales, integrales y derivados.

Cree un modelo más complejo de un sistema de control representando componentes individuales como modelos LTI y conectando los componentes para modelar su arquitectura de control. Para ver un ejemplo, consulte Modelado de sistemas de control con objetos de modelo.

Funciones

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tfTransfer function model
zpkZero-pole-gain model
ssState-space model
frdFrequency-response data model
filtSpecify discrete transfer functions in DSP format
dssCreate descriptor state-space models
pidCreate PID controller in parallel form, convert to parallel-form PID controller
pidstd Create a PID controller in standard form, convert to standard-form PID controller
pid2Create 2-DOF PID controller in parallel form, convert to parallel-form 2-DOF PID controller
pidstd2 Create 2-DOF PID controller in standard form, convert to standard-form 2-DOF PID controller
rssGenerate random continuous test model
drssGenere un modelo de prueba discreto aleatorio

Bloques

LTI SystemUse linear time invariant system model object in Simulink
LPV SystemSimulate Linear Parameter-Varying (LPV) systems

Temas

Introducción

Modelado de sistemas de control con objetos de modelo

Los objetos de modelo pueden representar componentes tales como la planta, actuadores, sensores o controladores. Se conectan los objetos de modelo para generar modelos agregativos que representen la respuesta combinada de varios elementos.

What Are Model Objects?

Model objects represent linear systems as specialized data containers that encapsulate model data and attributes in a structured way.

Using Model Objects

Ways to use model objects include linear analysis, compensator design, and control system tuning.

Modelos de tiempo continuo

Creating Continuous-Time Models

This example shows how to create continuous-time linear models using the tf, zpk, ss, and frd commands.

Transfer Functions

Represent transfer functions in terms of numerator and denominator coefficients or zeros, poles, and gain.

State-Space Models

Represent state-space models in terms of the state-space matrices.

Frequency Response Data (FRD) Models

Represent dynamic systems in terms of the magnitude and phase of their responses at various frequencies.

Proportional-Integral-Derivative (PID) Controllers

Represent PID controllers in terms of controller gains or time constants.

Two-Degree-of-Freedom PID Controllers

2-DOF PID controllers can achieve faster disturbance rejection without significant increase of overshoot in setpoint tracking.

Using the Right Model Representation

This example shows some best practices for working with LTI models.

Modelos de tiempo discreto

Creating Discrete-Time Models

This example shows how to create discrete-time linear models using the tf, zpk, ss, and frd commands.

Discrete-Time Numeric Models

Represent discrete-time numeric models by specifying a sample time when you create the model object.

Discrete-Time Proportional-Integral-Derivative (PID) Controllers

The integrator and filter terms in discrete-time PID controllers can be represented by several different formulas.

Modelos MIMO

MIMO Transfer Functions

Create MIMO transfer functions by concatenating SISO transfer functions or by specifying coefficient sets for each I/O channel.

MIMO State-Space Models

These examples show how to represent MIMO systems as state-space models.

MIMO Frequency Response Data Models

Use frequency-response data from multiple I/O pairs in a system to create a MIMO frequency response model.

Select Input/Output Pairs in MIMO Models

Extract particular I/O channels from a MIMO dynamic system model.

Modelos LTI en Simulink

Import LTI Model Objects into Simulink

Use the LTI System block to import linear system model objects into Simulink®.

Más información sobre objetos de modelo

Types of Model Objects

Model object types include numeric models, for representing systems with fixed coefficients, and generalized models for systems with tunable or uncertain coefficients.

Dynamic System Models

Represent systems that have internal dynamics or memory of past states, such as integrators, delays, transfer functions, and state-space models.

Numeric Models

Numeric LTI Models represent dynamic elements, such as transfer functions or state-space models, with fixed coefficients.

Static Models

Represent static input/output relationships, including tunable or uncertain parameters and arrays.