Article
Engineering, Electrical & Electronic
Gang Wang, Bei Peng, Zhenyu Feng, Xinyue Yang, Jing Deng, Nianci Wang
Summary: This paper presents a new robust adaptive algorithm, the recursive minimum error entropy, which performs well under impulsive noise compared to traditional least squares and maximum correntropy algorithms. Theoretical analyses and numerical simulations demonstrate the superior performance of the new algorithm.
Article
Computer Science, Artificial Intelligence
Soumya Ranjan Das, Ambika Prasad Hota, Hari Mohan Pandey, Biswa Mohan Sahoo
Summary: Solar photovoltaic (PV) sources, as one of the most favorable renewable sources, can fulfill a larger percentage of the total electricity demand with clean energy. However, the intermittent characteristics of PV inject uncertainty into power systems, impacting power quality issues. This proposal presents a solar PV integrated with a shunt hybrid active filter (SHAF) to reduce current harmonics and supply active power. The proposal focuses on controlling PV variables and current control in the SHAF's voltage source inverter (VSI) through adaptive notch filters (ANF), hysteresis controller, and fuzzy-based maximum power point tracking (MPPT). The study demonstrates embedded applications of SHAF in regulating grid-interfaced PV systems and compares ANF with non-adaptive notch filters (NNF) through rigorous computer simulations.
APPLIED SOFT COMPUTING
(2022)
Article
Automation & Control Systems
Yao Wei, Hector Young, Dongliang Ke, Fengxiang Wang, Jose Rodriguez
Summary: This article proposes a model-free predictive current control method based on extended affine ultralocal to solve the issues of model accuracy and robustness in motor driving systems. The model is built using data-driven approach and the coefficients are estimated online without prior knowledge. Experimental results demonstrate that the proposed method improves current quality and robustness compared to traditional methods.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Computer Science, Information Systems
Pei-Jarn Chen, Szu-Yueh Yang, Yen-Pei Chen, Muslikhin Muslikhin, Ming-Shyan Wang
Summary: This paper proposes a slip estimation and compensation control method for an omnidirectional Mecanum-wheeled automated guided vehicle, which adjusts the speed of the four omnidirectional wheels to accurately track the predetermined motion trajectory. Experimental results demonstrate a significant reduction in tracking errors and improved tracking accuracy using this method.
Article
Multidisciplinary Sciences
Laura-Maria Dogariu, Cristian-Lucian Stanciu, Camelia Elisei-Iliescu, Constantin Paleologu, Jacob Benesty, Silviu Ciochina
Summary: This paper introduces a family of tensor-based adaptive filtering algorithms suitable for high-dimension system identification problems, aiming to estimate the global impulse response of the system using a combination of shorter adaptive filters. These algorithms are primarily designed for multiple-input/single-output systems but can be extended to other systems as well. Compared to traditional adaptive filters, tensor-based algorithms achieve faster convergence and better accuracy.
Article
Chemistry, Multidisciplinary
Maaz Mahadi, Tarig Ballal, Muhammad Moinuddin, Ubaid M. Al-Saggaf
Summary: Recursive least-squares (RLS) algorithms are widely used in various applications. This paper focuses on time-varying regularized RLS (RRLS) techniques and proposes a low-complexity update method using an approximate recursive formula. Simulation results demonstrate the superiority of the time-varying RRLS strategy over the fixed one.
APPLIED SCIENCES-BASEL
(2022)
Article
Automation & Control Systems
Zheng Zhu, Xiangyu Wang, Bingjie Yan, Liang Li, Qiong Wu
Summary: This paper proposes a dynamic decoupling control method for PMSM in BBW system, which improves the dynamic response performance of the system by optimizing the boost time and braking time. The results show a reduction in boost time by 18.30% and braking time by 9.63%.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Article
Automation & Control Systems
Zheng Zhu, Xiangyu Wang, Bingjie Yan, Liang Li, Qiong Wu
Summary: A dynamic decoupling control method for permanent magnet synchronous motor (PMSM) of BBW system is proposed in this paper. The results from simulations and experiments show that the method can effectively improve the dynamic response performance and reduce the braking time.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Article
Computer Science, Artificial Intelligence
Wenling Li, Zidong Wang, Jun Hu, Junping Du, Weiguo Sheng
Summary: This paper focuses on the problem of kernel adaptive filtering for a complex network. It proposes a coupled KLMS algorithm and a coupled KRLS algorithm to improve the filtering performance. The validity and convergence of the algorithms are demonstrated through theoretical analysis and simulation.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Po Li, Ying He, Jingrui Zhang
Summary: This paper presents a real-time detection method for harmonic extraction that is able to handle sudden fluctuations in amplitude, phase, and frequency of the fundamental wave. The method utilizes the Least Squares method with forgetting factor to extract the phase and frequency of the fundamental wave, and then uses this information to design a linear time-varying observer for the extraction of DC bias and harmonics. The proposed method is shown to be robust and accurate in various scenarios such as distorted power grid signals, white noise, inter-harmonics, and high-order harmonics.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Gang Wang, Jingci Qiao, Rui Xue, Bei Peng
Summary: This paper investigates the kernel recursive least squares (KRLS) algorithm in the quaternion domain using the generalized Hamilton-real calculus method. The study shows the feasibility and performance of the proposed algorithm by first examining the quaternion recursive least squares (QRLS) algorithm and then generalizing it to the quaternion KRLS algorithm, with theoretical analysis and simulations demonstrating convergence and accuracy.
Article
Multidisciplinary Sciences
Zia Ur Rehman, Malak Abid Ali Khan, Hongbin Ma, Mizanur Rahman
Summary: The proposed work utilizes a non-minimal state space model and a multi-innovation recursive least squares (MIRLS) scheme for parameter estimation in time-varying systems. The incorporation of a time-varying objective function enables adaptability to changing system dynamics. Simulation experiments using a benchmark time-varying model demonstrate the effectiveness and benefits of the proposed methodology in dealing with time-varying systems.
Article
Computer Science, Artificial Intelligence
Yang Chen, Chenxi Li, Jiaxiu Yang
Summary: This paper presents a Nagar-Bardini structure based on IT2 fuzzy logic systems for forecasting uncertain parameters of permanent magnetic drive. By optimizing the parameters of the fuzzy logic system, the study shows that non-singleton IT2 FLS performs better in convergence analysis.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Automation & Control Systems
Yelong Yu, Xiaoyan Huang, Zhaokai Li, Min Wu, Tingna Shi, Yanfei Cao, Geng Yang, Feng Niu
Summary: This article introduces a novel online full parameter estimation method for permanent magnet synchronous motors (PMSMs). By utilizing the recursive least squares algorithm in the alpha-beta frame, the proposed method can estimate all motor parameters simultaneously. Simulation and experimental results demonstrate the superiority of the proposed method in terms of convergence rate, computational cost, and accuracy compared to the traditional method in the d-q frame.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Engineering, Electrical & Electronic
Chuanqiang Lian, Fei Xiao, Jilong Liu, Shan Gao
Summary: This article proposes a novel parameter and VSI nonlinearity hybrid estimation method to accurately estimate electrical parameters of PMSMs. The method considers the effects of magnetic saturation, cross saturation, and temperature. It consists of offline estimation and online estimation. Experimental results demonstrate higher estimation accuracy and improved control performance.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2023)
Article
Computer Science, Artificial Intelligence
Sonali Dash, Manas Ranjan Senapati
EGYPTIAN INFORMATICS JOURNAL
(2020)
Article
Engineering, Electrical & Electronic
Gupteswar Sahu, Sonali Dash, Birendra Biswal
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS
(2020)
Article
Multidisciplinary Sciences
Sonali Dash, Sahil Verma, Kavita, Savitri Bevinakoppa, Marcin Wozniak, Jana Shafi, Muhammad Fazal Ijaz
Summary: Fundus images play a significant role in analyzing cardiovascular and ophthalmological diseases, requiring precise blood vessel segmentation for accurate diagnosis. This study proposes a technique using a combination of fast guided filter and matched filter for enhancing vessel extraction in abnormal retinal images. The technique was evaluated on DRIVE and CHASE_DB1 datasets, achieving accuracies of 0.9613 and 0.960 respectively, outperforming existing vessel segmentation algorithms.
Article
Medicine, General & Internal
Sonali Dash, Sahil Verma, Kavita, Md Sameeruddin Khan, Marcin Wozniak, Jana Shafi, Muhammad Fazal Ijaz
Summary: Retinal blood vessels are analyzed for ophthalmic diseases using the Jerman filter and curvelet transform to improve structure visualization and data recovery. The fusion of curvelet transform and the Jerman filter achieves good segmentation accuracy for retinal blood vessels. The method shows better performance and faster implementation compared to similar approaches in existing literature.
Proceedings Paper
Computer Science, Artificial Intelligence
Sonali Dash
SMART INTELLIGENT COMPUTING AND APPLICATIONS, VOL 2
(2020)
Article
Computer Science, Artificial Intelligence
Sonali Dash, Manas Ranjan Senapati, Uma Ranjan Jena
EGYPTIAN INFORMATICS JOURNAL
(2018)
Article
Multidisciplinary Sciences
Sonali Dash, Uma Ranjan Jena, Manas Ranjan Senapati
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2018)
Proceedings Paper
Engineering, Electrical & Electronic
Sonali Dash, Uma Ranjan Jena
2017 2ND IEEE INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, SIGNAL PROCESSING AND NETWORKING (WISPNET)
(2017)
Proceedings Paper
Engineering, Electrical & Electronic
Sonali Dash, Uma Ranjan Jena
2017 2ND IEEE INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, SIGNAL PROCESSING AND NETWORKING (WISPNET)
(2017)
Article
Computer Science, Artificial Intelligence
Sonali Dash, Manas Ranjan Senapati
Summary: This study introduces a new texture classification approach by extracting features from gray level run length matrix using robust illumination normalization techniques. The purpose is to successfully deal with texture variations caused by changes in illumination and camera pose. Experimental results demonstrate a significant performance improvement compared to traditional GLRLM descriptor, using 2D wavelet, Tan and Triggs (TT) normalization methods.
EVOLUTIONARY INTELLIGENCE
(2021)
