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Tytuł:
Comparison of estimation accuracy of EKF, UKF and PF filters
Autorzy:
Konatowski, S.
Kaniewski, P.
Matuszewski, J.
Powiązania:
https://bibliotekanauki.pl/articles/320725.pdf
Data publikacji:
2016
Wydawca:
Polskie Forum Nawigacyjne
Tematy:
non-linear filtering
extended Kalman filter
unscented Kalman filter
particle filter
Opis:
Several types of nonlinear filters (EKF — extended Kalman filter, UKF — unscented Kalman filter, PF — particle filter) are widely used for location estimation and their algorithms are described in this paper. In the article filtering accuracy for non-linear form of measurement equation is presented. The results of complex simulations that com-pare the quality of estimation of analyzed non-linear filters for complex non-linearities of state vector are presented. The moves of maneuvering object are described in two-dimensional Cartesian coordinates and the measurements are described in the polar coordinate system. The object dynamics is characterized by acceleration described by the univariate non-stationary growth model (UNGM) function. The filtering accuracy was evaluated not only by the root-mean-square errors (RMSE) but also by statistical testing of innovations through the expected value test, the whiteness test and the WSSR (weighted sum squared residual) test as well. The comparison of filtering quality was done in the MATLAB environment. The presented results provide a basis for designing more accurate algorithms for object location estimation.
W artykule opisane zostały algorytmy filtrów nieliniowych (rozszerzony EKF i bezśladowy UKF filtr Kalmana oraz filtr cząstkowy PF) stosowane powszechnie do estymacji położenia. Porównano dokładność estymacji tych filtrów dla nieliniowego równania pomiarowego. Zaprezentowane zostały rezultaty badań symulacyjnych porównujących jakość estymacji analizowanych rodzajów filtrów nieliniowych dla złożonej nieliniowości wektora stanu. Ruch obiektu manewrującego opisano w dwuwymiarowym układzie kartezjańskim, natomiast pomiary w polarnym układzie współrzędnych. Dynamikę obiektu charakteryzuje przyspieszenie opisane funkcją Univariate-Non-Stationary-Growth-Model. Efektywność badań, poza określaniem błędów średniokwadratowych RMSE, oceniano poprzez statystyczne testowanie innowacji za pomocą: testu wartości oczekiwanej, testu białości oraz testu WSSR (Weighted-Sum-Squared-Residual). Ocena jakości procesu filtracji została przeprowadzona w środowisku MATLAB. Przedstawione wyniki stanowią podstawę do projektowania dokładniejszych algorytmów estymacji położenia obiektu.
Źródło:
Annual of Navigation; 2016, 23; 69-87
1640-8632
Pojawia się w:
Annual of Navigation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Two cascaded and extended kalman filters combined with sliding mode control for sustainable management of marine fish stocks
Autorzy:
Benz, Katharina
Rech, Claus
Mercorelli, Paolo
Sergiyenko, Oleg
Powiązania:
https://bibliotekanauki.pl/articles/1837383.pdf
Data publikacji:
2020
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
Lotka‐Volterra model
sliding mode control
Extended Kalman Filter
Opis:
This paper deals with a possible approach to controlling marine fish stocks using the prey‐predator model described by the Lotka‐Volterra equations. The control strategy is conceived using the sliding mode control (SMC) approach which, based on the Lyapunov theorem, offers the possibility to track desired functions, thus guaranteeing the stability of the controlled system. One of the most important aspects of this model is the identification of some parameters which characterizes the model. In this work two cascaded and Extended Kalman Filters (EKFs) are proposed to estimate them in order to be utilized in SMC. This approach can be used for sustainable management of marine fish stocks: through the developed algorithm, the appropriate number of active fishermen and the suitable period for fishing can be determined. Computer simulations validate the proposed approach.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 3; 28-35
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Experimental study on damage detection of base-isolated structure using an adaptive extended Kalman filter
Autorzy:
Yin, Q.
Zhou, L.
Mu, T.
Yang, J. N.
Powiązania:
https://bibliotekanauki.pl/articles/280160.pdf
Data publikacji:
2013
Wydawca:
Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:
damage detection
adaptive extended Kalman filter
base-isolated structure
Opis:
In this paper, experimental studies are performed and presented to verify the capability of the adaptive extended Kalman filter (AEKF) approach for identifying and tracking damages in nonlinear structures. A base-isolated building model consisting of a scaled building model mounted on a rubber-bearing isolation system has been tested experimentally in the laboratory. The non-linear behavior of the base isolators is represented by the Bouc-Wen model. To simulate the structural damages during the test, an innovative device, referred to as the stiffness element device (SED), is proposed to reduce the stiffness of the upper storey of the structure. Various damage scenarios have been simulated and tested. The measured acceleration response data and the AEKF approach are used to track the variation of the stiffness during the test. The tracking results for the stiffness variations correlate well with that of the referenced values. It is concluded that the AEKF approach is capable of tracking the variation of structural parameters leading to the detection of damages in nonlinear structures.
Źródło:
Journal of Theoretical and Applied Mechanics; 2013, 51, 4; 1013-1026
1429-2955
Pojawia się w:
Journal of Theoretical and Applied Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Nonlinear observers design for multivariable ship motion control
Autorzy:
Tomera, M.
Powiązania:
https://bibliotekanauki.pl/articles/259089.pdf
Data publikacji:
2012
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
extended Kalman filter
nonlinear observers
ship control
dynamic positioning
Opis:
This paper presents the designs of two observers, which are: the extended Kalman filter and the nonlinear passive observer. Based on the measured values of ship position and heading, the observers estimate the surge, sway and yaw velocities of the ship motion. The observers make use of the simplified nonlinear mathematical model of ship motion in which the neglected ship dynamics and disturbances are modelled using bias. The designed observers firstly have been simulated on a computer model where their parameters were calibrated, and then were implemented on the physical model of the training ship “Blue Lady” in the ship handling centre in Ilawa-Kamionka. The comparative analysis was done with respect to the estimated variables describing the ship motion in three directions: surge, sway and yaw.
Źródło:
Polish Maritime Research; 2012, S 1; 50-56
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Introduction to the Special Section on State and Parameter Estimation Methods for Sensorless Drives
Autorzy:
Barut, M.
Hinkkanen, M.
Orlowska-Kowalska, T.
Powiązania:
https://bibliotekanauki.pl/articles/1193677.pdf
Data publikacji:
2018
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
sensorless control
extended Kalman filter
unscented Kalman filter
MRAS estimators
neural networks
Opis:
This short article constitutes an introductory part of the Special Section (SS) on State and Parameter Estimation Methods in Sensorless Drives. In the current issue of the journal, the first part of this section is published. Accepted articles are focussed mainly on estimation of the state variables and parameters for vector-controlled induction motor (IM) drives, using different concepts, such as different types of Kalman filters (KFs) and model reference adaptive systems (MRASs). The KF was also proposed for brushless DC motor (BLDC). Also, neural networks (NNs) have been proposed for mechanical state variables’ estimation of the drive system with elastic couplings.
Źródło:
Power Electronics and Drives; 2018, 3, 38; 111-113
2451-0262
2543-4292
Pojawia się w:
Power Electronics and Drives
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Takagi Sugeno fuzzy expert model based soft fault diagnosis for two tank interacting system
Autorzy:
Manikandan, P.
Geetha, M.
Powiązania:
https://bibliotekanauki.pl/articles/229272.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
extended Kalman filter
fault diagnosis
fuzzy logic
two-tank system
Opis:
The inherent characteristics of fuzzy logic theory make it suitable for fault detection and diagnosis (FDI). Fault detection can benefit from nonlinear fuzzy modeling and fault diagnosis can profit from a transparent reasoning system, which can embed operator experience, but also learn from experimental and/or simulation data. Thus, fuzzy logic-based diagnostic is advantageous since it allows the incorporation of a-priori knowledge and lets the user understand the inference of the system. In this paper, the successful use of a fuzzy FDI based system, based on dynamic fuzzy models for fault detection and diagnosis of an industrial two tank system is presented. The plant data is used for the design and validation of the fuzzy FDI system. The validation results show the effectiveness of this approach.
Źródło:
Archives of Control Sciences; 2014, 24, 3; 271-287
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Simulation analysis of extended Kalman filter applied for estimating position and speed of a brushless DC motor
Autorzy:
Chojowski, M.
Powiązania:
https://bibliotekanauki.pl/articles/1193591.pdf
Data publikacji:
2018
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
extended Kalman filter
brushless DC motor
covariance matrix
sensorless control
BLDC
Opis:
The purpose of this paper was to present a method for the estimation of the rotor speed and position of brushless DC (BLDC) motor. The BLDC motor state equations were developed, and the model was discretised. Extended Kalman filter has been designed to observe specific states from the state vector, needed for the sensorless control (rotor position) and to determine the speed, which may be useful to use as a feedback for the controller. A test was carried out to determine the noise covariance matrices in a simulation manner.
Źródło:
Power Electronics and Drives; 2018, 3, 38; 145-155
2451-0262
2543-4292
Pojawia się w:
Power Electronics and Drives
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Joint Channel and Carrier Estimation Using Extended Kalman Filter
Autorzy:
Hanza, G.
Powiązania:
https://bibliotekanauki.pl/articles/227355.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
extended Kalman filter
EKF
joint channel
carrier estimation
synchronization
digital receiver
Opis:
In this paper a proposal of joint channel and carrier estimation using extended Kalman filter (EKF) is presented. For the proposed algorithm simulations are performed and the results are compared with the separate channel estimation based on the Kalman filter (KF) and carrier estimation based on the extended Kalman filter (EKF).
Źródło:
International Journal of Electronics and Telecommunications; 2013, 59, 1; 33-39
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
D-Step Ahead Kalman Predictor for Controlled Autoregressive Processes With Random Coefficients
Autorzy:
Hilgert, N.
Vila, J. P.
Powiązania:
https://bibliotekanauki.pl/articles/908306.pdf
Data publikacji:
1999
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
proces autoregresji
wzór wstępny Kalmana
filtr Kalmana
autoregressive processes
Kalman predictor
Kalman filter
extended Kalman filter
Opis:
This paper deals with prediction of controlled autoregressive processes with additive white Gaussian noise and random coefficients adapted to an observation process. Our aim is twofold. We begin by extending to the standard Kalman predictor a result of Chen et al. (1989) on the optimality of the standard Kalman filter when applied to linear stochastic processes with almost surely finite random coefficients. We then show on an example how some particular nonlinear autoregressive processes can be embedded in these linear processes with random coefficients. Such nonlinear processes can then benefit from this optimal prediction, which is not provided by the usual extended Kalman predictor.
Źródło:
International Journal of Applied Mathematics and Computer Science; 1999, 9, 1; 207-217
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of extended Kalman filter for estimation of periodic disturbance and velocity ripple reduction in PMSM drive
Autorzy:
Niewiara, Ł. J.
Tarczewski, T.
Grzesiak, L M.
Powiązania:
https://bibliotekanauki.pl/articles/201499.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
extended Kalman filter
disturbance estimation
PMSM drive
pulsating torque
velocity ripple reduction
Opis:
In this paper an application of extended Kalman filter (EKF) for estimation and attenuation of periodic disturbance in permanent magnet synchronous motor (PMSM) drive is investigated. Most types of disturbances present into PMSM drive were discussed and described. The mathematical model of the plant is presented. Detailed information about the design process of the disturbance estimator was introduced. A state feedback controller (SFC) with feedforward realizes the regulation and disturbance compensation. The theoretical analysis was supported by experimental tests on the laboratory stand. Both time- and frequency-domain analysis of the estimation results and angular velocity were performed. A significant reduction of velocity ripple has been achieved.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2020, 68, 5; 983-995
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Extended Kalman filter based speed-sensorless load torque and inertia estimations with observability analysis for induction motors
Autorzy:
Zerdali, E.
Barut, M.
Powiązania:
https://bibliotekanauki.pl/articles/1193483.pdf
Data publikacji:
2018
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
extended Kalman filter
induction motor
load torque estimation
inertia estimation
speed-sensorless control
observability analysis
Opis:
This paper aims to introduce a novel extended Kalman filter (EKF) based estimator including observability analysis to the literature associated with the high performance speed-sensorless control of induction motors (IMs). The proposed estimator simultaneously performs the estimations of stator stationary axis components of stator currents and rotor fluxes, rotor mechanical speed, load torque including the viscous friction term, and reciprocal of total inertia by using measured stator phase currents and voltages. The inertia estimation is done since it varies with the load coupled to the shaft and affects the performance of speed estimation especially when the rotor speed changes. In this context, the estimations of all mechanical state and parameters besides flux estimation required for high performance control methods are performed together. The performance of the proposed estimator is tested by simulation and real-time experiments under challenging variations in load torque and velocity references; and in both transient and steady states, the quite satisfactory estimation performance is achieved.
Źródło:
Power Electronics and Drives; 2018, 3, 38; 115-127
2451-0262
2543-4292
Pojawia się w:
Power Electronics and Drives
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
SLAM aided Inertial Navigation System
System nawigacji inercjalnej wspomagany SLAM
Autorzy:
Naus, K.
Marchel, Ł.
Powiązania:
https://bibliotekanauki.pl/articles/222977.pdf
Data publikacji:
2015
Wydawca:
Akademia Marynarki Wojennej. Wydział Dowodzenia i Operacji Morskich
Tematy:
SLAM
inertial navigation
data fusion
extended Kalman filter
nawigacja inercjalna
fuzja danych
rozszerzony filtr Kalmana
Opis:
The interdisciplinary nature of navigation leads us to drawing on knowledge contained in solutions used in related technical fields. An example of this trend is combining it with elements of robotics, in which SLAM (Simultaneous Localization And Mapping) is commonly used for positioning a vehicle. To calculate position changes, the location of characteristic objects on a continuously updated map of an environment is used. The attractiveness of the implementation of this technology in connection with marine navigational aids, stems from the possibility of enhancing positioning accuracy in harbor, off-shore or narrow areas. That is in the areas where there is a built up hydro-technical infrastructure, such as breakwaters, waterfronts or navigational infrastructure in the form of marked water fairways and anchorages. In this article an analysis of SLAM combined with INS (Inertial Navigation System) is carried out. It focuses on the possibilities of enhancing accuracy in fixing position coordinates for a submarine. The first part of the article presents a mathematical base for combining INS and SLAM using the Extended Kalman Filter. The second part describes a study on the accuracy in positioning a mobile robot (in this instance a wheeled vehicle) which employs a navigation system based on INS and INS aided SLAM. The final part of the article includes the results of the study and their analysis. It also contains generalized conclusions indicating advantages and disadvantages of the proposed solution.
Interdyscyplinarność nawigacji skłania do czerpania wiedzy z rozwiązań stosowanych w pokrewnych dziedzinach nauk technicznych. Przykładem jest połączenie z elementami robotyki, w której do pozycjonowania pojazdu powszechnie wykorzystywana jest technika SLAM (Simultaneous Localization And Mapping). Polega ona na pozycjonowaniu pojazdu na podstawie zmian położenia obiektów charakterystycznych znajdujących się na stale aktualizowanej mapie otoczenia. Implementacja tej technologii w połączeniu z morskimi urządzeniami nawigacyjnymi zwiększa dokładność pozycjonowania w obszarach portowych, przybrzeżnych lub ścieśnionych, gdzie istnieje rozbudowana infrastruktura hydrotechniczna, np. falochrony, nabrzeża, oraz infrastruktura nawigacyjna w postaci oznakowanych torów wodnych i kotwicowisk. W artykule przeprowadzono analizę technologii SLAM w połączeniu z INS (Inertial Navigation System) pod kątem możliwości zwiększenia dokładności wypracowywania współrzędnych pozycji na okręcie podwodnym. W pierwszej części przedstawiono podstawę matematyczną zespolenia INS ze SLAM przy użyciu rozszerzonego filtru Kalmana (Extended Kalman Filter), w drugiej opisano badanie dokładności pozycjonowania robota mobilnego (pojazdu kołowego) wykorzystującego system nawigacyjny oparty na INS i INS wspomagany SLAM, na zakończenie przedstawiono wyniki badania oraz ich analizę, a także uogólnione wnioski ukazujące zalety i wady zaproponowanego rozwiązania.
Źródło:
Zeszyty Naukowe Akademii Marynarki Wojennej; 2015, R. 56 nr 1 (200), 1 (200); 15-28
0860-889X
Pojawia się w:
Zeszyty Naukowe Akademii Marynarki Wojennej
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Identification of Ship Maneuvering Model Using Extended Kalman Filters
Autorzy:
Shi, C.
Zhao, D.
Peng, J.
Shen, C.
Powiązania:
https://bibliotekanauki.pl/articles/116777.pdf
Data publikacji:
2009
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
Manoeuvring
Ship Manoeuvering Model
Kalman filter
extended Kalman filter (EKF)
Ship Manoeuvrability
ship handling simulator
Turning Circle Test
Zig-Zag Test
Opis:
Ship maneuvering models are the keys to the research of ship maneuverability, design of ship motion control system and development of ship handling simulators. For various frames of ship maneuvering models, determining the parameters of the models is always a tedious task. System identification theory can be used to establish system mathematical models by the system’s input data and output data. In this paper, based on the analysis of ship hydrodynamics, a nonlinear model frame of ship maneuvering is established. System identification theory is employed to estimate the parameters of the model. An algorithm based on the extended Kalman filter theory is proposed to calculate the parameters. In order to gain the system’s input and output data, which is necessary for the parameters identification experiment, turning circle tests and Zig-zag tests are performed on shiphandling simulator and the initial data is collected. Based on the Fixed Interval Kalman Smoothing algorithm, a pre-processing algorithm is proposed to process the raw data of the tests. With this algorithm, the errors introduced during the measurement process are eliminated. Parameters identification experiments are designed to estimate the model parameters, and the ship maneuvering model parameters estimation algorithm is extended to modify the parameters being estimated. Then the model parameters and the ship maneuvering model are determined. Simulation validation was carried out to simulate the ship maneuverability. Comparisons have been made to the simulated data and measured data. The results show that the ship maneuvering model determined by our approach can seasonably reflect the actual motion of ship, and the parameter estimation procedure and algorithms are effective.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2009, 3, 1; 105-110
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Sky-hook control and Kalman filtering in nonlinear model of tracked vehicle suspension system
Autorzy:
Jurkiewicz, A.
Kowal, J.
Zając, K.
Powiązania:
https://bibliotekanauki.pl/articles/386619.pdf
Data publikacji:
2017
Wydawca:
Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
Tematy:
continuous sky-hook control strategy
extended Kalman filter
military vehicle
nonlinear model
semi-active suspension system
simulation
Opis:
The essence of the undertaken topic is application of the continuous sky-hook control strategy and the Extended Kalman Filter as the state observer in the 2S1 tracked vehicle suspension system. The half-car model of this suspension system consists of seven logarithmic spiral springs and two magnetorheological dampers which has been described by the Bingham model. The applied continuous skyhook control strategy considers nonlinear stiffness characteristic of the logarithmic spiral springs. The control is determined on estimates generated by the Extended Kalman Filter. Improve of ride comfort is verified by comparing simulation results, under the same driving conditions, of controlled and passive vehicle suspension systems.
Źródło:
Acta Mechanica et Automatica; 2017, 11, 3; 222-228
1898-4088
2300-5319
Pojawia się w:
Acta Mechanica et Automatica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Simultaneous localization and mapping for tracked wheel robots combining monocular and stereo vision
Autorzy:
Jesus, F.
Ventura, R.
Powiązania:
https://bibliotekanauki.pl/articles/384393.pdf
Data publikacji:
2013
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
simultaneous localisation and mapping
extended Kalman filter
feature detector
inverse depth parametrization
landmark evaluation
temporal difference learning
Opis:
This paper addresses an online 6D SLAM method for a tracked wheel robot in an unknown and unstructured environment. While the robot pose is represented by its position and orientation over a 3D space, the environment is mapped with natural landmarks in the same space, autonomously collected using visual data from feature detectors. The observation model employs opportunistically features detected from either monocular and stereo vision. These features are represented using an inverse depth parametrization. The motion model uses odometry readings from motor encoders and orientation changes measured with an IMU. A dimensional-bounded EKF (DBEKF) is introduced here, that keeps the dimension of the state bounded. A new landmark classifier using a Temporal Difference Learning methodology is used to identify undesired landmarks from the state. By forcing an upper bound to the number of landmarks in the EKF state, the computational complexity is reduced to up to a constant while not compromising its integrity. All experimental work was done using real data from RAPOSA-NG, a tracked wheel robot developed for Search and Rescue missions.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2013, 7, 1; 21-27
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
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