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This paper investigates the robust weighted fusion estimation problem of multi-sensor systems with mixed uncertainties, including stochastic parameter uncertainties, missing measurements and uncertain noise variances. The stochastic parameter uncertainties are described by multiplicative noise. Especially, the variances of both the multiplicative and additive noises are uncertain. By introducing two...
We study the problem of distributed state estimation over adaptive networks, where agents collaborate to estimate a common state parameter vector. If the sensing target area is too large or we want to improve the convergence speed of a large adaptive network, single-level diffusion algorithms do not have better performance, so we study the multi-level diffusion Kalman filter algorithm where a network...
Fault estimation with performance analysis is investigated in the least squares sense for a class of time-varying systems with event-triggered measurement transmission and biased process noise covariances. In most other work, process noise covariance is assumed as either completely known. In this paper, we relax the assumption of knowing the exact process noise covariance and apply an event-triggered...
Servo drives comprise a high dynamic and smooth motion control which is typically based on a cascaded control structure with position measurement or estimation. By including an additional acceleration feedback, the command and disturbance behavior can be improved significantly. Based on the proven cascaded control structure, this contribution analyzes an extended control concept with additional acceleration...
This paper proposes a method for estimating the process noise covariance matrix, using multiple Kalman filters. The basic idea is to employ the difference between the expected prediction error covariance, calculated in the Kalman filters, and the measured prediction error covariance. The required estimate of the process noise covariance is obtained by solving a least squares problem. One simulated...
The optimal sensor selection for scalar state parameter estimation in wireless sensor networks is studied in the paper. A subset of N candidate sensing locations is selected to measure a state parameter and send the observation to a fusion center via wireless AWGN channel. In addition to selecting the optimal sensing location, the sensor type to be placed in these locations is selected from a pool...
Locomotives are equipped with slip controllers to limit a value of a wheel slip velocity and conducive to reach required locomotive tractive effort. The slip control methods are developed for tenths years, and the methods are based on several principles. Progressive methods determine an adhesion-slip characteristic slope. This method requires knowledge of an adhesion coefficient value or an adhesion...
This paper presents a vehicle positioning method based on joint estimation of time of arrival (TOA) and direction of arrival (DOA) with Vehicle-to-Roadside (V2R) communications. By analyzing the measured channel frequency response (CFR) between vehicles and the roadside unit (RU), the enhanced two-dimensional matrix pencil (2-D MP) algorithm is implemented to design the parameter estimator, which...
In this paper, fault-tolerant active control of the rotational motion of the satellite has been applied. Satellite mathematical models are introduced, and the nontraditional Kalman filter is designed with the presented control algorithms. Re-adjustment control procedure has been established taking into account the identified control distribution matrix. If there are three-axis reaction wheels on the...
Spin-stabilization offers a simple attitude control solution, specifically for micro and nanosatellites, and has a large potential for implementation on numerous missions. This paper proposes an attitude estimation algorithm for spin satellites. The algorithm is loosely based on a filter proposed by Bar-Itzhack and Harman. Using a simple Kalman filter (KF) algorithm and only the magnetometer measurements,...
The Pole Placement Control is a control strategy to reallocate poles of a system forcing a desired behaviour to it. The technique is established on states feedback backed by a gain matrix. States are estimated when they are not directly available. Then, in this work a pole placement control based on Discrete Kalman Filter, in discrete time, for feedback states was applied over a linear welding robot...
It is common to assume that there is only one degradation mechanism in the system in recent works on prognostics focusing on estimation of the remaining useful life (RUL) of an electromechanical system. However, there are cases in which the system may be subjected to more than one failure (degradation) mechanisms due to different stress factors, types of components and their interactions with one...
In this article, an approach for multi-vehicles localization and guiding is described and demonstrated with experiments in real conditions. The general methodology of the presented work is based on a top down approach implemented in each vehicle of the fleet and having a map of the environment to estimate the absolute localization of each vehicle. The principle is to select, at each time, the best...
The paper addresses a problem of ballistic object trajectory estimation on the basis of measurements from a cinetheodolite electro-optical tracking system. The object flight dynamics is modeled using a three degrees of freedom equations of motion. The estimation of object trajectory is performed with the use of an Extended Kalman Filter.
Singular Value Decomposition (SVD) and extended Kalman filter (EKF) are integrated earlier by authors in order to estimate the satellite's angular motion parameters about center of mass. The SVD-aided EKF algorithm is used in this study for estimation of the attitude angles and angular velocities. In the eclipse period, algorithm is switched into the prediction phase for better attitude estimation...
The highly limited number of observation results in the increase of the prediction errors. In such case the linear Kalman filter (KF) will work within the unsteady state, which can lead to unpredictable results. The paper presents an alternative, simplified methods for the tracked object position prediction with the linearization of the trajectory. The obtained results are compared with the KF predictions...
As an energy source of mobile system including robot, Li battery is extensively applied. To increase durability and efficient usage of battery, it is to require the rigorous management to battery controller, BMS,. Of them, the exact estimation of SOC is very important for correct usage. In this paper, introducing the design of BMS simply and, as a estimation method of SOC, dual extended Kalman filter...
Many exist localization algorithms are unbiased estimators. However, the estimation performance presents biased feature in the real location systems. On the other hand, many biased location estimators show advantages that unbiased estimators can not achieve, e.g., robust to the noise, more accurate estimation and low complexity. In this paper, we propose a biased localization estimator and a hybrid...
A comparison of attitude estimation algorithms is performed to allow selection of an appropriate algorithm for a quadrotor collision recovery system. A Multiplicative Extended Kalman Filter (MEKF), an Unscented Kalman Filter (UKF), a complementary filter, an H∞ Filter, and adaptive varieties of the selected filters are chosen for comparison. The adaptive modifications to the estimation algorithms...
Due to the limited bandwidth of underwater communication links, underwater cooperative localization usually adopts a distributed processing architecture. Members of the team estimate positions using their local sensor data, and fuse the information communicated by other members for cooperation. It is common practice to naïvely assume independency during information fusion between cooperative members...
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