Search results for "Extended Kalman Filter"
showing 10 items of 44 documents
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…
Asynchronous sensor fusion of GPS, IMU and CAN-based odometry for heavy-duty vehicles
2021
[EN] In heavy-duty vehicles, multiple signals are available to estimate the vehicle's kinematics, such as Inertial Measurement Unit (IMU), Global Positioning System (GPS) and linear and angular speed readings from wheel tachometers on the internal Controller Area Network (CAN). These signals have different noise variance, bandwidth and sampling rate (being the latter, possibly, irregular). In this paper we present a non-linear sensor fusion algorithm allowing asynchronous sampling and non-causal smoothing. It is applied to achieve accuracy improvements when incorporating odometry measurements from CAN bus to standard GPS+IMU kinematic estimation, as well as the robustness against missing da…
An Extended Kalman Filter-Based Technique for On-Line Identification of Unmanned Aerial System Parameters
2015
ABSTRACT: The present article deals with the identification, at the same time, of aircraft stability and control parameters taking into account dynamic damping derivatives. Such derivatives, due to the rate of change of the angle of attack, are usually neglected. So the damping characteristics of aircraft dynamics are attributed only on pitch rate derivatives. To cope with the dynamic effects of these derivatives, authors developed devoted procedures to estimate them. In the present paper, a complete model of aerodynamic coefficients has been tuned-up to identify simultaneously the whole set of derivatives. Besides, in spite of the employed reduced order model and/or decoupled dynamics, a s…
State Estimation of a Nonlinear Unmanned Aerial Vehicle Model using an Extended Kalman Filter
2008
An Extended Kalman Filter is designed in order to estimate both state variables and wind velocity vector at the same time for a non conventional unmanned aircraft. The proposed observer uses few measurements, obtained by means of either conventional simple air data sensors or a low cost GPS. To cope with the low rate of the GPS with respect to the other sensors, the EKF algorithm has been modified to allow for a dual rate measurement model. State propagation is obtained by means of an accurate six degrees of freedom nonlinear model of the aircraft dynamics. To obtain joint estimation of state and disturbance, wind velocity components are included in the set of the state variables. Both stoc…
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…
Supercapacitor diagnosis using an Extended Kalman Filtering approach
2016
This paper deals with the model-based analysis of a Supercapacitor for diagnostic purposes. A two legs nonlinear physical model is assumed for the Supercapacitor and the corresponding second-order nonlinear state-space mathematical model is obtained. Then, an Extended Kalman Filter is tuned so that the estimated outputs reproduce the voltages at the equivalent capacitance terminals; they give information on the state of health of the supercapacitor but are not directly measurable. In particular, an optimization problem is firstly formulated, involving the experimental input-output data and those given by the Extended Kalman Filter.
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…
Wind Shear On-Line Identification for Unmanned Aerial Systems
2014
An algorithm to perform the on line identification of the wind shear components suitable for the UAS characteristics has been implemented. The mathematical model of aircraft and wind shear in the augmented state space has been built without any restrictive assumption on the dynamic of wind shear. Due to the severe accelerations on the aircraft induced by the strong velocity variation typical of wind shear, the wind shear effects have been modeled as external forces and moments applied on the aircraft. The identification problem addressed in this work has been solved by using the Filter error method approach. An Extended Kalman Filter has been developed to propagate state. It has been tuned …
Adaptive high-gain extended kalman filter and applications
2010
The work concerns the ``observability problem” --- the reconstruction of a dynamic process's full state from a partially measured state--- for nonlinear dynamic systems. The Extended Kalman Filter (EKF) is a widely-used observer for such nonlinear systems. However it suffers from a lack of theoretical justifications and displays poor performance when the estimated state is far from the real state, e.g. due to large perturbations, a poor initial state estimate, etc… We propose a solution to these problems, the Adaptive High-Gain (EKF). Observability theory reveals the existence of special representations characterizing nonlinear systems having the observability property. Such representations…
Sensorless control of induction motors using an extended Kalman filter and linear quadratic tracking
2017
Induction motors are the most commonly used prime-movers in industrial applications. Many induction motors supplied by frequency converters are coupled with a physical angular rotor position/velocity sensor which makes the drive complex and require maintenance. This paper presents a sensorless control structure to avoid using a physical angular rotor position/velocity sensor. The proposed method estimates and control the angular rotor velocity using optimal control theory. The optimal controller used in this paper is based on linear quadratic tracking and the states of the machine are estimated using an extended Kalman filter. Both the controller and the estimator utilize the same internal …