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Input-Output Polynomial Models

ARX, ARMAX, BJ and OE models


System Identification Identify models of dynamic systems from measured data


arx Estimate parameters of ARX or AR model using least squares
armax Estimate parameters of ARMAX model using time-domain data
bj Estimate Box-Jenkins polynomial model using time domain data
iv4 ARX model estimation using four-stage instrumental variable method
ivx ARX model estimation using instrumental variable method with arbitrary instruments
oe Estimate Output-Error polynomial model using time or frequency domain data
polyest Estimate polynomial model using time- or frequency-domain data
idpoly Polynomial model with identifiable parameters
pem Prediction error estimate for linear and nonlinear model
arxstruc Compute loss functions for single-output ARX models
ivstruc Compute loss functions for sets of ARX model structures using instrumental variable method
selstruc Select model order for single-output ARX models
struc Generate model-order combinations for single-output ARX model estimation
arxRegul Determine regularization constants for ARX model estimation
delayest Estimate time delay (dead time) from data
init Set or randomize initial parameter values
polydata Access polynomial coefficients and uncertainties of identified model
getpvec Model parameters and associated uncertainty data
setpvec Modify value of model parameters
getpar Obtain attributes such as values and bounds of linear model parameters
setpar Set attributes such as values and bounds of linear model parameters
setPolyFormat Specify format for B and F polynomials of multi-input polynomial model
armaxOptions Option set for armax
arxOptions Option set for arx
arxRegulOptions Option set for arxRegul
bjOptions Option set for bj
iv4Options Option set for iv4
oeOptions Option set for oe
polyestOptions Option set for polyest

Examples and How To

Preliminary Step – Estimating Model Orders and Input Delays

To estimate polynomial models, you must provide input delays and model orders.

Estimate Polynomial Models in the App

Import data into the app, specify model orders, delays and estimation options.

Estimate Polynomial Models at the Command Line

Specify model orders, delays, and estimation options.

Polynomial Sizes and Orders of Multi-Output Polynomial Models

Size of A, B, C, D, and F polynomials for multi-output models.

Estimate Models Using armax

This example shows how to estimate a linear, polynomial model with an ARMAX structure for a three-input and single-output (MISO) system using the iterative estimation method armax.


What Are Polynomial Models?

Polynomial model structures including ARX, ARMAX, ourput-error, and Box-Jenkins.

Data Supported by Polynomial Models

Use time-domain and frequency-domain data to estimate discrete-time and continuous-time models.

Specifying Initial States for Iterative Estimation Algorithms

When you use the pem or polyest to estimate ARMAX, Box-Jenkins (BJ), Output-Error (OE), you must specify how the algorithm treats initial conditions.

Polynomial Model Estimation Algorithms

Choose between the ARX and IV algorithms for ARX and AR model estimation.

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