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Online State Estimation

Estimate model parameters using linear and nonlinear Kalman filters at the command line and in Simulink®

You can estimate the states of your system using real-time data and linear, extended, or unscented Kalman filter algorithms. You can perform online state estimation using the Simulink blocks in the Estimators sublibrary of the System Identification Toolbox™ library. You can then generate C/C++ code for these blocks using Simulink Coder™, and deploy this code to an embedded target. You can also perform online state estimation at the command line, and deploy your code using MATLAB® Compiler™ or MATLAB Coder.

Functions

extendedKalmanFilterCreate extended Kalman filter object for online state estimation
unscentedKalmanFilterCreate unscented Kalman filter object for online state estimation
particleFilterParticle filter object for online state estimation
correctCorrect state and state estimation error covariance using extended or unscented Kalman filter, or particle filter and measurements
predictPredict state and state estimation error covariance at next time step using extended or unscented Kalman filter, or particle filter
initializeInitialize the state of the particle filter
cloneCopy online state estimation object

Blocks

Kalman FilterEstimate states of discrete-time or continuous-time linear system
Extended Kalman FilterEstimate states of discrete-time nonlinear system using extended Kalman filter
Unscented Kalman FilterEstimate states of discrete-time nonlinear system using unscented Kalman filter

Topics

Online Estimation Basics

What Is Online Estimation?

Estimate states and parameters of a system in real-time.

Extended and Unscented Kalman Filter Algorithms for Online State Estimation

Description of the underlying algorithms for state estimation of nonlinear systems.

Online State Estimation in Simulink

State Estimation Using Time-Varying Kalman Filter

Estimate states of linear systems using time-varying Kalman filters in Simulink.

Estimate States of Nonlinear System with Multiple, Multirate Sensors

Use an Extended Kalman Filter block to estimate the states of a system with multiple sensors that are operating at different sampling rates.

Validate Online State Estimation in Simulink

Validate online state estimation that is performed using Extended Kalman Filter and Unscented Kalman Filter blocks.

Online State Estimation at the Command Line

Nonlinear State Estimation Using Unscented Kalman Filter and Particle Filter

Use the unscented Kalman filter algorithm for nonlinear state estimation for the van der Pol oscillator.

Fault Detection Using an Extended Kalman Filter

You can use an extended Kalman filter for fault detection.

Validate Online State Estimation at the Command Line

Validate online state estimation that is performed using extended and unscented Kalman filter algorithms.

Generate Code for Online State Estimation in MATLAB

Deploy extended or unscented Kalman filters, or particle filters using MATLAB Coder software.

Troubleshooting

Troubleshoot Online State Estimation

Troubleshoot online state estimation performed using extended and unscented Kalman filter algorithms.

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