Create a time series model and use the model for prediction, forecasting, and state estimation. The measured data is from an induction furnace whose slot size erodes over time. The slot size
Use a data-based modeling approach for fault detection. This example requires Statistics and Machine Learning Toolbox™.
Use an extended Kalman filter for fault detection. The example uses an extended Kalman filter for online estimation of the friction of a simple DC motor. Significant changes in the estimated
Detect abrupt changes in the behavior of a system using online estimation and automatic data segmentation techniques.
Perform multivariate time series forecasting of data measured from predator and prey populations in a prey crowding scenario. The predator-prey population-change dynamics are modeled
Estimate the states of a nonlinear system using an Unscented Kalman Filter in Simulink™. The example also illustrates how to develop an event-based Kalman Filter to update system