Hybrid extended Kalman filtering and noise statistics optimization for produce wash state estimation

Systematic Estimation of State Noise Statistics for Extended Kalman Filters

The successful application of model-based control depends on the information about the states of the dynamic system. State-estimation methods, like extended Kalman filters ( ) EKF , are useful for obtaining reliable estimates of the states from a limited number of measurements. They also can handle the model uncertainties and the effect of unmeasured disturbances. The main issue in applying EKF...

Non-stationary Noise Estimation in Adaptive Linear and Extended Kalman Filtering

Abstract. When Optimal Linear Kalman Filtering is employed, the complete knowledge of all system parameters, including the forcing input functions and the noise statistics, is required. In Adaptive schemes, frequently employed in control, communications, and other applications where the statistical characteristics of the signals to be filtered are either totally unknown a priori or, as assumed ...

On Line Electric Power Systems State Estimation Using Kalman Filtering (RESEARCH NOTE)

In this paper principles of extended Kalman filtering theory is developed and applied to simulated on-line electric power systems state estimation in order to trace the operating condition changes through the redundant and noisy measurements. Test results on IEEE 14 - bus test system are included. Three case systems are tried; through the comparing of their results, it is concluded that the pro...

Extended Kalman Filtering by

Kalman filtering for disease-state estimation from microarray data

MOTIVATION In this paper, we propose using the Kalman filter (KF) as a pre-processing step in microarray-based molecular diagnosis. Incorporating the expression covariance between genes is important in such classification problems, since this represents the functional relationships that govern tissue state. Failing to fulfil such requirements may result in biologically implausible class predict...