2020
DOI: 10.1049/gtd2.12014
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Sparse LMS algorithm for two‐level DSTATCOM

Abstract: Sparse least mean square algorithm is proposed for the DSTATCOM as an optimal current harmonic extractor to cope with the intermittent nature of loadings. Sparse least mean square is the improved version of adaptive least mean square learning mechanism with regards to sparsity. This innovative approach is utilized for better parameter estimation due to its algorithmic simplicity and parallel computing nature. Hence, sparse least mean square is expected to reduce the computation and storage requirements signifi… Show more

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Cited by 11 publications
(4 citation statements)
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“…Mrutyunjaya Mangaraj Email: mrutyunjaya.m@srmap.edu.in 2 N Toushif Khan Email: tousif.k@srmap.edu.in 3 B Chitti Babu Email: bcbabu@iiitdm.ac.in 4 S M Muyeen Email: sm.muyeen@qu.edu.qa Indian Institute of Information Technology, Design and Manufacturing Kancheepuram, Chennai-600127. 4 Department of Electrical Engineering, Qatar University, Doha, Qatar-2713 These algorithms like Kernel Hebbian Least Mean Square [7], Levenberg Marquard back propagation [8], Hebbian Least Mean Square [9], Sparse Least Mean Square [10], Adaptive control [11], Recurrent neural network [12][13], CFNN-AMF [14], Neuro Fuzzy learning [15], neural network [16][17][18], Predictive control [19][20], PNK-LMF [21] are reported for harmoncs ellimination. But, few authors are addressed synchronous theory (abc-dq0) rotating model for SMES based VS-APF to improve the steady and dynamic state performance [3][4][5][6].…”
Section: Review Of Literature and Research Backgroundmentioning
confidence: 99%
“…Mrutyunjaya Mangaraj Email: mrutyunjaya.m@srmap.edu.in 2 N Toushif Khan Email: tousif.k@srmap.edu.in 3 B Chitti Babu Email: bcbabu@iiitdm.ac.in 4 S M Muyeen Email: sm.muyeen@qu.edu.qa Indian Institute of Information Technology, Design and Manufacturing Kancheepuram, Chennai-600127. 4 Department of Electrical Engineering, Qatar University, Doha, Qatar-2713 These algorithms like Kernel Hebbian Least Mean Square [7], Levenberg Marquard back propagation [8], Hebbian Least Mean Square [9], Sparse Least Mean Square [10], Adaptive control [11], Recurrent neural network [12][13], CFNN-AMF [14], Neuro Fuzzy learning [15], neural network [16][17][18], Predictive control [19][20], PNK-LMF [21] are reported for harmoncs ellimination. But, few authors are addressed synchronous theory (abc-dq0) rotating model for SMES based VS-APF to improve the steady and dynamic state performance [3][4][5][6].…”
Section: Review Of Literature and Research Backgroundmentioning
confidence: 99%
“…The dynamic assessment on power quality under the different loading is explained in subsequent section. Finally, the complete procedure is presented by using mathematical equation from ( 1) to (20). The weights of the active and reactive parts of the load current are listed:…”
Section: Design Of the Proposed Dstatcommentioning
confidence: 99%
“…𝑖 𝑟𝑎 = 𝑤 𝑠𝑞 𝑢 𝑞𝑎 , 𝑖 𝑟𝑏 = 𝑤 𝑠𝑞 𝑢 𝑞𝑏 , 𝑖 𝑟𝑐 = 𝑤 𝑠𝑞 𝑢 𝑞𝑐 (19) Finally, the total reference source currents are determined by (20).…”
Section: Switching Pulses Generationmentioning
confidence: 99%
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