This paper presents the detailed mathematical and Simulink® model of a two-phase stepper BLDC motor in the machine variables, proving the rotor's position role in supplying the motor. Then an extended Kalman filter (EKF) is designed to estimate the motor state variables: stator currents, and the rotor position and velocity, on the basis of noisy measurements of stator currents, since it has a n...

|An algorithm is presented for tracking a landing aircraft using fusion of two diierent passive sensors, a laser range nder (LRF) and a forward-looking infrared (FLIR) camera. The main feature of this algorithm is its ability to identify and compensate for an exhaust plume disturbance. The algorithm is based on the extended Kalman lter (EKF) and the ltering conndence function (FCF) which introd...

The motion of a car is described using a stochastic model in which the driving processes are the steering angle and the tangential acceleration. The model incorporates exactly the kinematic constraint that the wheels do not slip sideways. Two lters based on this model have been implemented, namely the standard EKF, and a new lter (the CUF) in which the expectation and the covariance of the syst...

Based on the idea of fault detection and isolation (FDI) for the distributed parameters system, a practical approach of sub-sea pipelines leak detection and location is discussed. The discrete fluid transient equation is linearized and coupled with the extended Kalman filter (EKF) to estimate system state where the only observed data were inlet and outlet flow rate and pressure. The leak estima...

Orbit determination in application to the estimation of impact probability has the goal of determining the evolution of the state probability density function (pdf) and determining a measure of the probability of collision. Nonlinear gravitational interaction and non-conservative forces can make the pdf far from Gaussian. This work implements three nonlinear sequential estimators: the Extended ...

In this paper we investigate the use of an alternative to the extended Kalman filter (EKF), the unscented Kalman filter (UKF). First we give a broad overview of different UKF algorithms, then present an extension to the ensemble of UKF algorithms, and finally address the issue of how to add constraints using the UKF approach. The performance of the constrained approach is compared with EKF and ...

An adaptive High-Gain observer (AHG) as well as an Extended (EKF) and Unscented Kalman filter (UKF) are implemented for joint state and parameter estimation of a novel multi-axial electromagnetically actuated punch. These observers are compared in terms of convergence and response time to erroneous parameter and state initialization, as well as parameter modifications during operation. The AHG ...

This paper analyzes the consistency of the classical extended Kalman filter (EKF) solution to the simultaneous localization and map building (SLAM) problem. Our results show that in large environments the map quickly becomes inconsistent due to linearization errors. We propose a new EKF-based SLAM algorithm, robocentric mapping, that greatly reduces linearization errors, improving map consisten...

To ensure safe operation of unmanned aerial vehicles (UAVs), component hazards need to be dealt with robustly through effective fault diagnosis. The extended Kalman filter (EKF) has proven popular in this realm, though it is known to suffer from linearisation errors that can degrade performance. This paper presents results from initial simulation trials that address sensor fault detection and i...

The filters tuning is a crucial issue due the need to quantify the accuracy of the model in terms of the process noise covariance matrix for process characterized by structural uncertainties which are time-varying. Thus, approaches to time-varying covariances were studied and included to a traditional EKF and an optimization-based state estimators constrained EKF (CEKF) formulations. The result...