Search results for " Kalman Filter"
showing 10 items of 55 documents
The Kalman Filter and Its Applications in GNSS and INS
2011
This chapter contains sections titled: Introduction Review of Kalman Filtering and Extended Kalman Filtering for Navigation EKF-Based PVT Computation in a Stand-Alone GNSS Receiver Inertial Navigation Fundamentals IMU Alignment General Architecture for the Loose Integration General Architecture for the Tight Integration General Architecture for the Ultra-Tight Integration Conclusions References Appendix A
FastSLAM 2.0: Least-Squares Approach
2006
In this paper, we present a set of robust and efficient algorithms with O(N) cost for the following situations: object detection with a laser ranger; mobile robot pose estimation and a FastSLAM improved implementation. Objected detection is mainly based on a novel multiple line fitting method, related with walls at the environment. This method assumes that walls at the environment constitute a regular constrained angles. A line-based pose estimation method is also proposed, based on Least-Squares (LS). This method performs the matching of detected lines and estimated map lines and it can provide the global pose estimation under assumption of known Data-Association. FastSLAM 1.0 has been imp…
AUTOMATIC TAKE-OFF OR LANDING PATH FOLLOWING IN TURBULENT AIR FOR UAS - AN EKF BASED PROCEDURE
2015
By using the Extended Kalman Filter (EKF) an accurate take-off or landing flight path following in turbulent air is performed. The tuned up procedure employs simultaneously two different EKF: the first one estimates gust disturbances, the second one affords to determine the necessary controls displacements for rejecting those ones. In particular, the first filter, by using instrumental measurements gathered in turbulent air, estimates wind components. The second one obtains command laws able to follow the desired flight path. To perform this task aerodynamic coefficients have been modified by adding entirely new derivatives or synthetic increments to basic ones whose might the kind of chang…
Optimal Flight Path Determination in Turbulent Air: A Modified EKF Approach
2017
By using the Extended Kalman Filter an accurate path following in turbulent air is performed. The procedure employs simultaneously two different EKFs: the first one estimates disturbances, the second one affords to determine the necessary controls displacements for rejecting those ones. To tune the EKFs an optimization algorithm has been designed to automatically determine Process Noise Covariance and Measurement Noise Covariance matrices. The first filter, by using instrumental measurements gathered in turbulent air, estimates wind components. The second one obtains command laws able to follow the desired flight path. To perform this task aerodynamic coefficients have been modified. Such a…
An EKF Based Method for Path Following in Turbulent Air
2017
An innovative use of the Extended Kalman Filter (EKF) is proposed to perform both accurate path following and adequate disturbance rejection in turbulent air. The tuned up procedure employs simultaneously two different EKF: the first one estimates gust disturbances, the second one estimates modified aircraft parameters. The first filter, by using measurements gathered in turbulent air, estimates both aircraft states and wind components. The second one, by using the estimated disturbances, obtains command laws that are able to reject disturbances. The predictor of the second EKF uses the estimated wind components to solve motion equations in turbulent air. Besides a set of unknown stability …
Automatic EKF tuning for UAS path following in turbulent air
2018
By using two simultaneously working Extended Kalman Filters, a procedure is implemented in order to perform in a fully autonomous way the path following in turbulent air. To guarantee the robustness of the proposed algorithm, an automatic tuning procedure is proposed to determine optimal values of Process and Measurement Noise statistics. Such a procedure is based on both the characteristics of the disturbances and the desired flight path; in particular, a specific performance index is applied to tune filters. In this way control laws are adapted to the flight condition and these lead to an optimal path-following. This research represents an upload of previous papers. It allows eliminating …
Extended complex Kalman filter for sensorless control of an induction motor
2014
Abstract This paper deals with the design of an extended complex Kalman filter (ECKF) for estimating the state of an induction motor (IM) model, and for sensorless control of systems employing this type of motor as an actuator. A complex-valued model is adopted that simultaneously allows a simpler observability analysis of the system and a more effective state estimation. The observability analysis of this model is first performed by assuming that a third order ECKF has to be designed, by neglecting the mechanical equation of the IM model, which is a valid hypothesis when the motor is operated at constant rotor speed. It is shown that this analysis is more effective and easier than the one …
Advanced techniques for solving groundwater and surface water problems in the context of inverse methods and climate change.
2021
[ES] El tema de la investigación se centra en técnicas avanzadas para manejar problemas de aguas subterráneas y superficiales relacionados con métodos inversos y cambio climático. Los filtros de Kalman, con especial atención en Ensemble Smoother with Multiple Data Assimilation (ES-MDA), se analizan y mejoran para la solución de diferentes tipos de problemas inversos. En particular, la principal novedad es la aplicación de estos métodos para la identificación de series temporales. La primera parte de la tesis, luego de la descripción del método, presenta el desarrollo de un software escrito en Python para la aplicación de la metodología propuesta. El software cuenta con un flujo de trabajo f…
Fuzzy EKF Control for Wheeled Nonholonomic Vehicles
2006
In this paper a new Fuzzy extended Kalman robust control system for position and orientation tracking of nonholonomic vehicles with two wheels actuated by two independent DC motors is presented. The problem of robustness and localization are solved simultaneously. About the robustness, some perturbations coming from the outside environment and depending on the contact between the wheels and the ground, involve violations of the nonholonomic constraints. The fuzzy controller of this work is able to obtain a dynamic term of robustness with respect to the perturbations above. However, by using encoders only, the measures of actual position and orientation of the vehicle are with Gaussian noise…
Convergence analysis of cubature Kalman filter
2014
This paper investigates the stability analysis of cubature Kalman filter (CKF) for nonlinear systems with linear measurement. The certain conditions to ensure that the estimation error of CKF remains bounded are proved. Then, the effect of process noise covariance is investigated and an adaptive process noise covariance is proposed to deal with large estimation error. Accordingly, a modified CKF (MCKF) is developed to enhance the stability and accuracy of state estimation. The performance of the MCKF is compared to the CKF by two case studies. Simulation results demonstrate that the large estimation error may lead to instability of CKF while the MCKF is successfully able to estimate the sta…