Search results for "Kalman filter"
showing 10 items of 108 documents
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 …
Multispectral high resolution sensor fusion for smoothing and gap-filling in the cloud
2020
Remote sensing optical sensors onboard operational satellites cannot have high spectral, spatial and temporal resolutions simultaneously. In addition, clouds and aerosols can adversely affect the signal contaminating the land surface observations. We present a HIghly Scalable Temporal Adaptive Reflectance Fusion Model (HISTARFM) algorithm to combine multispectral images of different sensors to reduce noise and produce monthly gap free high resolution (30 m) observations over land. Our approach uses images from the Landsat (30 m spatial resolution and 16 day revisit cycle) and the MODIS missions, both from Terra and Aqua platforms (500 m spatial resolution and daily revisit cycle). We implem…
Parameter identification and state estimation of a microalgae dynamical model in sulphur deprived conditions: Global sensitivity analysis, optimizati…
2014
International audience; In this article, a dynamic model describing the growth of the green microalgae Chlamydomonas reinhardtii , under light attenuation and sulphur‐deprived conditions leading to hydrogen production in a photobioreactor is presented. The strong interactions between biological and physical phenomena require complex mathematical expressions with an important number of parameters. This article presents a global identification procedure in three steps using data from batch experiments. First, it includes the application of a sensitivity function analysis, which allows one to determine the parameters having the greatest influence on model outputs. Secondly, the most influentia…
Adaptive-gain extended Kalman filter: Extension to the continuous-discrete case
2009
In the present article we propose a nonlinear observer that merges the behaviors 1) of an extended Kalman filter, mainly designed to smooth off noise , and 2) of high-gain observers devoted to handle large perturbations in the state estimation. We specifically aim at continuous-discrete systems. The strategy consists in letting the high-gain self adapt according to the innovation. We define innovation computed over a time window and justify its usage via an important lemma. We prove the general convergence of the resulting observer.
Adaptive Consensus-Based Distributed Kalman Filter for WSNs with Random Link Failures
2016
Wireless Sensor Networks have emerged as a very powerful tool for the monitoring and control, over large areas, of diverse phenomena. One of the most appealing properties of these networks is their potentiality to perform complex tasks in a total distributed fashion, without requiring a central entity. In this scenario, where nodes are constrained to use only local information and communicate with one-hop neighbors, iterative consensus algorithms are extensively used due to their simplicity. In this work, we propose the design of a consensus-based distributed Kalman filter for state estimation, in a sensor network whose connections are subject to random failures. As a result of this unrelia…
Integrated GNSS/IMU Hub Motion Estimator for Offshore Wind Turbine Blade Installation
2019
Abstract Offshore wind turbines (OWTs) have become increasingly popular for their ability to harvest clean offshore wind energy. Bottom-fixed foundations are the most used foundation type. Because of its large diameter, the foundation is sensitive to wave loads. For typical manually assisted blade-mating operations, the decision to perform the mating operation is based on the relative distance and velocity between the blade root center and the hub, and in accordance with the weather window. Hence, monitoring the hub real-time position and velocity is necessary, whether the blade installation is conducted manually or automatically. In this study, we design a hub motion estimation algorithm f…
Ship-to-Ship State Observer Using Sensor Fusion and the Extended Kalman Filter
2019
In this paper, a solution for estimating the relative position and orientation between two ships in six degrees-of-freedom (6DOF) using sensor fusion and an extended Kalman filter (EKF) approach is presented. Two different sensor types, based on time-of-flight and inertial measurement principles, were combined to create a reliable and redundant estimate of the relative motion between the ships. An accurate and reliable relative motion estimate is expected to be a key enabler for future ship-to-ship operations, such as autonomous load transfer and handling. The proposed sensor fusion algorithm was tested with real sensors (two motion reference units (MRS) and a laser tracker) and an experime…
An adaptive multi-rate system for visual tracking in augmented reality applications
2016
The visual tracking of an object is a well-known problem, and it involves many fields of applications. Often a single sensor, the camera, could not provide enough information in order to track the whole object trajectory due to a low updating rate; therefore a multi-sensor system, based also on inertial measurements, could be necessary to improve the tracking accuracy. This leads to the fundamental question: how can information from different sensors be combined when they work at different rates? In this paper an approach based on recursive parameter estimation focusing on multi-rate situations is suggested. The problem is here formulated as the state-of-the-art problem of the visual tracki…
Automatic Take Off and Landing for UAS Flying in Turbulent Air - An EKF Based Procedure
2020
An innovative use of the Extended Kalman Filter (EKF) is proposed to perform automatic take off and landing by the rejection of disturbances due to turbulence. By using two simultaneously working Extended Kalman Filters, a procedure is implemented: the first filter, by using measurements gathered in turbulent air, estimates wind components; the second one, by using the estimated disturbances, obtains command laws that are able to reject disturbances. The fundamental innovation of such a procedure consists in the fact that the covariance matrices of process (Q) and measurement (R) noise are not treated as filter design parameters. In this way determined optimal values of the aforementioned m…
Using an Adaptive High-Gain Extended Kalman Filter With a Car Efficiency Model
2010
The authors apply the Adaptive High-Gain Extended Kalman Filter (AEKF) to the problem of estimating engine efficiency with data gathered from normal driving. The AEKF is an extension of the traditional Kalman Filter that allows the filter to be reactive to perturbations without sacrificing noise filtering. An observability normal form of the engine efficiency model is developed for the AEKF. The continuous-discrete AEKF is presented along with strategies for dealing with asynchronous data. Empiric test results are presented and contrasted with EKF-derived results.Copyright © 2010 by ASME