Results 11 to 20 of about 95,139 (292)
IEEE Access, 2019 Recursive least square (RLS) algorithms are considered as a kind of accurate parameter identification method for lithium-ion batteries. However, traditional RLS algorithms usually employ a fixed forgetting factor, which does not have adequate robustness ...
Qiang Song, Yuxuan Mi, Wuxuan Lai
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An Improved Hybrid Beamforming Algorithm for Fast Target Tracking in Satellite and V2X Communication
Remote Sensing, 2023 Autonomous remote sensing systems establish communication links between nodes. Ensuring coverage and seamless communication in highly dense environments is not a trivial task as localization, separation, and tracking of targets, as well as interference ...
Aral Ertug Zorkun +2 more
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Energies, 2018 For model-based state of charge (SOC) estimation methods, the battery model parameters change with temperature, SOC, and so forth, causing the estimation error to increase.
Zizhou Lao +5 more
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Recursive least squares for online dynamic identification on gas turbine engines [PDF]
, 2016 Online identification for a gas turbine engine is vital for health monitoring and control decisions because the engine electronic control system uses the identified model to analyze the performance for optimization of fuel consumption, a response to ...
Nalianda, Devaiah +2 more
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IEEE Access, 2018 A new cost function that introduces the minimum-disturbance (MD) constraint into the conventional recursive least squares (RLS) with a sparsity-promoting penalty is first defined in this paper.
Zhou Fan Li, Dan Li, Jian Qiu Zhang
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Energies, 2019 With the popularity of electric vehicles, lithium-ion batteries as a power source are an important part of electric vehicles, and online identification of equivalent circuit model parameters of a lithium-ion battery has gradually become a focus of ...
Xiangdong Sun +4 more
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Kernel RLS Algorithm Using Variable Forgetting Factor
The Journal of Korean Institute of Communications and Information Sciences, 2015 In a recent work, kernel recursive least-squares tracker (KRLS-T) algorithm has been proposed. It is capable of tracking in non-stationary environments using a forgetting mechanism built on a Bayesian framework. The forgetting mechanism in KRLS-T is implemented by a fixed forgetting factor.
Jun-Seok Lim, Yong-Guk Pyeon
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International Islamic University Malaysia Engineering Journal, 2016 In this paper, a hybrid configuration algorithm called stochastic gradient method with variable forgetting factor (SGVFF) is proposed to better estimate unknown parameters in a power system such as amplitude and phase of harmonics using variable ...
Ahmad Mohammadzadeh +2 more
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Applied Sciences, 2022 Mechanical resonance occurs during the operation of a maglev inertially stabilized platform (MISP). The MISP is driven by the motor gear and the gear clearance changes during commutation, which makes the resonance frequency variable.
Wanfa Shi, Kun Liu, Jingbo Wei
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Large Time-Varying Parameter VARs [PDF]
, 2012 In this paper, we develop methods for estimation and forecasting in large time-varying parameter vector autoregressive models (TVP-VARs). To overcome computational constraints, we draw on ideas from the dynamic model averaging literature which achieve ...
Banbura +26 more
core +5 more sources