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State and Parameter Estimation of the Mathematical Carcinoma Model under Chemotherapeutic Treatment

Máté Siket, György Eigner, Dániel András Drexler, Imre Rudas, Levente Kovács
2020 Applied Sciences  
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


2006 International Journal of Bifurcation and Chaos in Applied Sciences and Engineering  
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

Karim Salahshoor, Amin Sabet Kamalabady
2008 2008 IEEE Conference on Cybernetics and Intelligent Systems  
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

Hamzah Ahmad, Nur Aqilah Othman, Mohd Syakirin Ramli
2018 TELKOMNIKA (Telecommunication Computing Electronics and Control)  
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

Claudio Urrea, Rayko Agramonte, Giovanni Diraco
2021 Journal of Sensors  
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

Carlos Enrique Mejia Salazar, Julián Esteban Rendón Roldán
2018 Enfoqute  
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

John Harlim, Adam Mahdi, Andrew J. Majda
2014 Journal of Computational Physics  
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/ fatcat:5iasfnkz7vgc5bprw4m6hrxrya

On closure parameter estimation in chaotic systems

J. Hakkarainen, A. Ilin, A. Solonen, M. Laine, H. Haario, J. Tamminen, E. Oja, H. Järvinen
2012 Nonlinear Processes in Geophysics  
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

Juan Pedro Llerena Caña, Jesús García Herrero, José Manuel Molina López
2021 Sensors  
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

Sangwei Lu, Wenxiang Zhou, Jinquan Huang, Feng Lu, Zhongguang Chen
2021 Aerospace (Basel)  
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

Fuwu Yan, Hubei Key Laboratory of Advanced Technology for Automotive Components (Wuhan University of Technology), Wuhan 430070, China
2018 International Journal of Electrochemical Science  
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

H. Banks, Shuhua Hu, Zackary Kenz, Hien Tran
2010 Mathematical Biosciences and Engineering  
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

Basilis Gidas, Fernando Carvalho Gomes, Christopher Robertson
2002 Quarterly of Applied Mathematics  
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

M Knauff, C Dafis, D Niebur
2010 Proceedings of the 2010 American Control Conference  
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

Antonio Padilha Lanari Bo, Philippe Poignet, Christian Geny
2009 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems  
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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