Results 21 to 30 of about 23,782 (215)
Prediction Error Analysis of Finite-Control-Set Model Predictive Current Control for IPMSMs
Energies, 2018 Finite-control-set model predictive current control (FCS-MPCC) has been widely investigated in the field of motor control. When the discrete motor prediction model is not obtained accurately, prediction error often occurs, which can result in improper ...
Jian Li +5 more
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Machine Learning Based Adaptive Prediction Horizon in Finite Control Set Model Predictive Control
IEEE Access, 2018 In this paper, an adaptive prediction horizon approach based on machine learning is presented for the finite control set model predictive control (FCS-MPC) of power converters. Usually, in FCS-MPC, the prediction horizon is kept constant.
Muhammad Saleh Murtaza Gardezi +1 more
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电力工程技术Permanent magnet synchronous motor (PMSM) has been widely used in industry due to the advantages of high efficiency, high power density and high reliability.
LIU Xing +4 more
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CES Transactions on Electrical Machines and Systems, 2018 This paper presents an improved finite control set model predictive current control (FCS-MPCC) of a five-phase permanent magnet synchronous motor (PMSM).
Wusen Wang +3 more
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Complexity, 2021 Photovoltaic (PV) power generation is the main aspect of new energy power generation, and it is an important means to achieve the goal of carbon neutrality. When the PV system is connected to the grid, the nonlinear load of the grid will affect the power
Xuejiao Gong, Shifeng Hu, Ruijin Zhu
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Overview of Predictive Control Technology for Permanent Magnet Synchronous Motor Systems
Applied Sciences, 2023 Permanent magnet synchronous motors (PMSMs) are commonly used in the automation industry. With the speedy development of digital system processors, predictive control as a modern control scheme has been applied to improve the dynamic performance and work
Jingyao Peng, Ming Yao
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FEBS Letters, EarlyView.Ascidian Ciona larvae initially show strong clockwise tail twisting, which is largely corrected during development. However, a small residual twist remains. This study shows that organized helical myofibrils in tail muscles mechanically stabilize this residual asymmetry, preventing complete restoration of bilateral symmetry and revealing how embryos ...
Yuki S. Kogure +3 more
wiley +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora +4 more
wiley +1 more source