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State and Parameter Estimation of the Mathematical Carcinoma Model under Chemotherapeutic Treatment
2020
Applied Sciences
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In this study, a moving horizon estimation (MHE)-based observer is developed and compared to an optimized EKF. The observers utilize a third-order tumor growth model. ...
One of the most widely applied estimators for nonlinear problems is the extended Kalman filter (EKF). ...
Abbreviations The following abbreviations are used in this manuscript:
EKF Extended Kalman filter MHE moving horizon estimation RMSE root-mean-square error ...
doi:10.3390/app10249046
fatcat:bl6ucztetfcxbmlgm75jokic6u
PARAMETER ESTIMATION USING KALMAN FILTERS WITH CONSTRAINTS
2006
International Journal of Bifurcation and Chaos in Applied Sciences and Engineering
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We suggest incorporating dynamical information such as locations of unstable fixed points into parameter estimation algorithms in order to improve the method of reconstructing dynamics from time series ...
data. ...
We will explain how the EKF can be used to estimate all unknown parameters of a pseudo-linear model but for ease of exposition will restrict the problem to determining the weight parameters in the examples ...
doi:10.1142/s0218127406015325
fatcat:nov5b3w5frgq3azus3onusudfe
On-line identification of multivariable processes using EKF learning-based adaptive neural networks
2008
2008 IEEE Conference on Cybernetics and Intelligent Systems
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The extended kalman filter (EKF) is proposed as learning algorithm to adapt the parameters of multi-input, multi-output (MIMO) RBF neural network in both GAP-RBF and MRAN approaches. ...
The performances of the algorithms are evaluated on a highly nonlinear and timevarying CSTR benchmark problem for comparison purposes. ...
EKF LEARNING ALGORITHM The EKF is considered as one of the most effective methods for both nonlinear state and parameter estimation. The EKF gives an approximation of the optimal estimate. ...
doi:10.1109/iccis.2008.4670811
fatcat:37kce2eymrb4fpvx7l2vk66fzy
A Solution to Partial Observability in Extended Kalman Filter Mobile Robot Navigation
2018
TELKOMNIKA (Telecommunication Computing Electronics and Control)
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Partial ob servab ility in EKF b ased mob ile rob ot navigation is investigated in this paper to find a solution that can prevent erroneous estimation. ...
Fuzzy Logic technique is proposed to ensure that the estimation achieved desired performance even though some of the landmarks were excluded for references. ...
Special thanks to Namerikawa Laboratory in Keio University for their participation and advises. ...
doi:10.12928/telkomnika.v16i2.9025
fatcat:hrdizpph5zgd3bnxlgheivt5km
Kalman Filter: Historical Overview and Review of Its Use in Robotics 60 Years after Its Creation
2021
Journal of Sensors
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In addition, the characteristics of each modification on this filter are analyzed and compared. ...
This work reviews some of the modifications conducted on to this algorithm over the last years. Problems such as the consistency, convergence, and accuracy of the filter are also dealt with. ...
This type of filtering is based on the determination of the dynamic system's statistical parameters according to the system's behavior during data processing [14, 15] . ...
doi:10.1155/2021/9674015
fatcat:jpbjftwvjbcfzcr4i3j32epdru
Fractional order modeling of a nonlinear electromechanical system
2018
Enfoqute
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This paper presents a novel modeling technique for a VTOL electromechanical nonlinear dynamical system, based on fractional order derivatives. ...
parameters for the differential operators of the model, an extended Kalman filter was implemented. ...
The authors would like to thank professor Mónica Ayde Vallejo Velásquez, director of Electronics and Control Laboratory at Universidad Nacional de Colombia for allowing us to take measurements of the VTOL ...
doi:10.29019/enfoqueute.v9n4.398
fatcat:cpefs72ke5gjbjbr3zwefcfvaq
An ensemble Kalman filter for statistical estimation of physics constrained nonlinear regression models
2014
Journal of Computational Physics
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A central issue in contemporary science is the development of nonlinear data driven statistical-dynamical models for time series of noisy partial observations from nature or a complex model. ...
Here a new finite ensemble Kalman filtering algorithm is developed for estimating the state, the linear and nonlinear model coefficients, the model and the observation noise covariances from available ...
Numerical results with EKF based parameter estimation scheme We consider here parameter estimation with Belanger's method [18, 22] blended with EKF (see Appendix for the detail algorithm) for estimating ...
doi:10.1016/j.jcp.2013.10.025
fatcat:5iasfnkz7vgc5bprw4m6hrxrya
On closure parameter estimation in chaotic systems
2012
Nonlinear Processes in Geophysics
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Traditionally, parameters of dynamical systems are estimated by directly comparing the model simulations to observed data using, for instance, a least squares approach. ...
In this paper, we study numerical methods available for estimating closure parameters in chaotic models. ...
Martin Leutbecher from ECMWF is gratefully acknowledged for his support and help in designing the numerical experiments carried out with the stochastic Lorenz-95 system. ...
doi:10.5194/npg-19-127-2012
fatcat:l7rsw6vuenbkrhocbb2tqldrnu
Forecasting Nonlinear Systems with LSTM: Analysis and Comparison with EKF
2021
Sensors
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Certain difficulties in path forecasting and filtering problems are based in the initial hypothesis of estimation and filtering techniques. ...
This paper addresses the forecast–filter problem from deep learning paradigms with a neural network architecture inspired by natural language processing techniques and data structure. ...
For each one, we describe the synthetic data generation model, the classic estimator model and the neuronal structure used. ...
doi:10.3390/s21051805
pmid:33807681
fatcat:nlke3wmwznhszk3deq3ilxynpy
A Novel Performance Adaptation and Diagnostic Method for Aero-Engines Based on the Aerothermodynamic Inverse Model
2021
Aerospace (Basel)
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A method based on the aerothermodynamic inverse model (AIM) is proposed to improve the adaptation accuracy and fault diagnostic dynamic estimation response speed in this paper. ...
In addition, the proposed method is implemented in combination with compensation of the nonlinear filter for real-time estimation of health parameters under the hypothesis of estimated dimensionality reduction ...
If |z − y| exceeds a very small pre-set value, the EKF will work synchronously to estimate the compensation ∆x of health parameters online from (z − y). ...
doi:10.3390/aerospace9010016
fatcat:uvef4kzptvcenfj3z22pukawsy
Comparative Study of two Kalman Algorithms for Estimating the State of Charge of Lithium-Ion Cells at Ambient Temperature
2018
International Journal of Electrochemical Science
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Kalman filters (KFs) are effective tools for estimating online state of charge (SOC), and a great variety of studies about different kinds of KFs have been published. ...
The model parameters were identified by hybrid pulse power characterization tests at 0, 15, 30, 45, and 55 ℃. ...
A physics-based electrochemical model can capture the temporally evolved and spatially distributed behavior of the essential states of a battery [41] . ...
doi:10.20964/2018.12.65
fatcat:6b6747mghrf3znaksk3qyyhfce
A comparison of nonlinear filtering approaches in the context of an HIV model
2010
Mathematical Biosciences and Engineering
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The filters are implemented to estimate model states as well as model parameters from simulated noisy data, and are compared in terms of estimation accuracy and computational time. ...
parameter estimation when used with log state variables of a model of the immunologic response to the human immunodeficiency virus (HIV) in individuals. ...
The estimated values versus the true values for each model compartment obtained by applying the filters to a typical data set. ...
doi:10.3934/mbe.2010.7.213
pmid:20462287
fatcat:nx25ve66fjgotig33ufcrvt2f4
Model-based tracking of moving objects in cluttered environments
2002
Quarterly of Applied Mathematics
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The procedure involves three basic models: (i) an object representation, (ii) a dynamic model, and (iii) a data or observation model. ...
key for successful tracking; put differently, the deficiencies of linear dynamics models cannot be easily compensated with more sophisticated data models. ...
In principle, one could parametrize the mass matrix elements with a sustainable set of identifiable parameters as in (3.4) and then estimated these parameters from data (more precisely, from the data ...
doi:10.1090/qam/1939009
fatcat:yze4luxutfct7dzl3rippzalaa
A new battery model for use with an extended Kalman filter state of charge estimator
2010
Proceedings of the 2010 American Control Conference
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The model is compared to a linear circuit model consisting of two parallel RC circuits, often used in EKF based state of charge estimation, demonstrating improvement in accuracy. ...
A new battery model is proposed for use with such an estimator in an attempt to further improve its accuracy. ...
CONCLUSION This paper presents a new battery model for use with an EKF based SOC estimator. ...
doi:10.1109/acc.2010.5531412
fatcat:2wuq57cterfldlvy3fc5z76il4
Filtering voluntary motion for pathological tremor compensation
2009
2009 IEEE/RSJ International Conference on Intelligent Robots and Systems
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Estimation is performed by means of an extended Kalman filter (EKF), which also estimates tremor parameters. ...
Comparison of the proposed method with techniques described in the literature are conducted with two experimental data sets from tremor patients performing the same task, drawing a spiral. ...
Fig. 5 . 5 Tremor in coordinate X estimated by all three evaluated methods.
TABLE I I Parameters used for our EKF-based algorithm. ...
doi:10.1109/iros.2009.5353972
dblp:conf/iros/BoPG09
fatcat:vqbgt2fovnhl5n3rhesaxtpyiq
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