Search results for "Extended Kalman Filter"
showing 10 items of 44 documents
ARIANNA: a smartphone-based navigation system with human in the loop
2014
In this paper we present a low cost navigation system, called ARIANNA, primarily designed for visually impaired people. ARIANNA (pAth Recognition for Indoor Assisted NavigatioN with Augmented perception) permits to find some points of interests in an indoor environment by following a path painted or sticked on the floor. The path is detected by the camera of the smartphone which also generates a vibration signal providing a feedback to the user for correcting his/her direction. Some special landmarks can be deployed along the path for coding additional information detectable by the camera. In order to study the practical feasibility of the ARIANNA system for human users that want to follow …
Stability and Noises Evaluation of Fuzzy Kalman UAV Navigation System.
2009
In this paper a new Fuzzy/Kalman navigation system for Unmanned Aerial Vehicles (UAV) is presented. A closed loop velocity Fuzzy navigation system is proposed for stabilizing the UAV in a reference trajectory generated dynamically and for obtaining a forward velocity command. The Kalman's filter (KF) is included in the feedback line of the fuzzy control system to filter the internal noise of the sensors and to evaluate the external noise due to possible perturbations of the nominal motion. The efficiency of the navigation system has been shown through experimental tests in a Matlab environment.
Observation and identification tools for non-linear systems: application to a fluid catalytic cracker
2005
In this paper we recall general methodologies we developed for observation and identification in non-linear systems theory, and we show how they can be applied to real practical problems. In a previous paper, we introduced a filter which is intermediate between the extended Kalman filter in its standard version and its high-gain version, and we applied it to certain observation problems. But we were missing some important cases. Here, we show how to treat these cases. We also apply the same technique in the context of our identifiability theory. As non-academic illustrations, we treat a problem of observation and a problem of identification, for a fluid catalytic cracker (FCC). This FCC uni…
Descriptor-type Robust Kalman Filter and Neural Adaptive Speed Estimation Scheme for Sensorless Control of Induction Motor Drive Systems
2012
Abstract This paper deals with robust estimation of speed and rotor flux for sensorless control of motion control systems which use induction motors as actuators. Due to the observability lack of five and six order Extended Kalman Filters, speed is here estimated by means of a Total Least Square algorithm with Neural Adaptive mechanism. This allows the use of a fourth-order Kalman Filter for estimating rotor flux and to filter stator currents. To cope with motor-load parameter variations, a descriptor-type robust Kalman Filter is designed taking explicitly into account these variations. The descriptor-type structure allows direct translation of parameter variations into variations of the co…
Robustness Analysis of an Extended Kalman Filter for Sensorless Control of Induction Motors
2010
This paper deals with robustness analysis of Extended Kalman Filters (EKFs) for sensorless motion control of induction motors. Analysis is carried out by means of simulation experiments considering a conventional EKF, in which system and measurement noise covariance matrices are constant, and an adaptive EKF in which the system noise covariance matrix is updated on-line using a PID-type algorithm driven by the stator current estimation errors.
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 …