온라인 파라미터 추정

명령줄과 Simulink^®에서 재귀적 알고리즘을 사용하여 모델 파라미터 추정

실시간 데이터와 재귀적 알고리즘을 사용하여 AR, ARMA, ARX, ARMAX, OE 또는 BJ 모델 계수의 파라미터를 추정할 수 있습니다. 재귀적 최소제곱(RLS) 알고리즘을 사용하여 모델을 추정할 수도 있습니다. 알고리즘에 대한 자세한 내용은 Recursive Algorithms for Online Parameter Estimation 항목을 참조하십시오.

System Identification Toolbox™ 라이브러리의 추정기 하위 라이브러리에 있는 Simulink 블록을 사용하여 온라인 파라미터 추정을 수행할 수 있습니다. 그런 다음 Simulink Coder™와 Simulink PLC Coder™를 사용하여 이들 블록에 대한 C/C++ 코드 및 Structured Text를 생성하고, 이 코드를 임베디드 타깃에 배포할 수 있습니다. 명령줄에서 온라인 추정을 수행하고 MATLAB^® Compiler™ 또는 MATLAB Coder를 사용하여 코드를 배포할 수도 있습니다.

함수

`recursiveAR`	Create System object for online parameter estimation of AR model
`recursiveARMA`	Create System object for online parameter estimation of ARMA model
`recursiveARX`	Create System object for online parameter estimation of ARX model
`recursiveARMAX`	Create System object for online parameter estimation of ARMAX model
`recursiveBJ`	Create System object for online parameter estimation of Box-Jenkins polynomial model
`recursiveOE`	Create System object for online parameter estimation of Output-Error polynomial model
`recursiveLS`	Create System object for online parameter estimation using recursive least squares algorithm
`step`	Update model parameters and output online using recursive estimation algorithm
`clone`	Copy online parameter estimation System object
`reset`	Reset online parameter estimation System object
`release`	Unlock online parameter estimation System object
`isLocked`	Locked status of online parameter estimation System object
`rpem`	Estimate general input-output models using recursive prediction-error minimization method
`rplr`	Estimate general input-output models using recursive pseudolinear regression method
`segment`	Segment data and estimate models for each segment

블록

Recursive Least Squares Estimator	Estimate model coefficients using recursive least squares (RLS) algorithm
Recursive Polynomial Model Estimator	Estimate input-output and time-series polynomial model coefficients
Model Type Converter	Convert polynomial model coefficients to state-space model matrices

도움말 항목

온라인 추정 기본 사항

What Is Online Estimation?
Estimate states and parameters of a system in real-time.
How Online Parameter Estimation Differs from Offline Estimation
Difference in data, algorithms, and estimation implementations.
Recursive Algorithms for Online Parameter Estimation
Forgetting factor, Kalman filter, gradient and unnormalized gradient, and finite-history algorithms for online parameter estimation.

Simulink에서의 온라인 파라미터 추정

Preprocess Online Parameter Estimation Data in Simulink
Remove drift, offset, missing samples, seasonalities, equilibrium behavior, and outliers in your data.
Online Recursive Least Squares Estimation
This example shows how to implement an online recursive least squares estimator.
Online ARMAX Polynomial Model Estimation
This example shows how to implement an online polynomial model estimator.
Validate Online Parameter Estimation Results in Simulink
Examine estimation errors, parameter covariance, and difference between simulated and measured outputs.

명령줄에서의 온라인 파라미터 추정

Perform Online Parameter Estimation at the Command Line
Online parameter estimation using System Objects.
Online ARX Parameter Estimation for Tracking Time-Varying System Dynamics
Perform online parameter estimation for a time-varying ARX model at the MATLAB command line.
Line Fitting with Online Recursive Least Squares Estimation
This example shows how to perform online parameter estimation for line-fitting using recursive estimation algorithms at the MATLAB® command line.
Validate Online Parameter Estimation at the Command Line
Examine estimation errors, parameter covariance, and difference between simulated and measured outputs.
Data Segmentation
Use of data segmentation to model systems exhibiting abrupt changes.

코드 생성

Generate Online Parameter Estimation Code in Simulink
Generate C/C++ code and Structured Text using Simulink Coder and Simulink PLC Coder products.
Generate Code for Online Parameter Estimation in MATLAB
Generate C/C++ code using MATLAB Coder software; limitations for System objects.

문제 해결

Troubleshoot Online Parameter Estimation

Check your model, estimation data, estimation settings, and initial parameter values.