2014
DOI: 10.1109/tii.2013.2264290
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Neural Network Based Conductance Estimation Control Algorithm for Shunt Compensation

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Cited by 63 publications
(32 citation statements)
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“…A learning based antihebbian based control approach is shown in [15]. A neural network based conductance estimation based control approach is shown in [16]. A back propagation based control approach is shown in [17].…”
Section: Introductionmentioning
confidence: 99%
“…A learning based antihebbian based control approach is shown in [15]. A neural network based conductance estimation based control approach is shown in [16]. A back propagation based control approach is shown in [17].…”
Section: Introductionmentioning
confidence: 99%
“…Shunt compensator provides suitable load compensation to prevent distorted currents entering the utility grid. Also, there is an increased interest in the development of advanced and fast digital control algorithms to achieve the desired power quality standards.…”
Section: Introductionmentioning
confidence: 99%
“…Two review papers present different configurations and controllers for shunt compensator. Advanced soft computing controllers based on artificial neural network, fuzzy techniques, adaline, and adaptive neuro fuzzy inference system are interesting but complex. Recently, a number of new controllers based on repetitive computation and updating of weights such as anti Hebbian, least means square–based technique, adaptive notch–based control and recursive techniques, and other signal cancelation techniques have gained immense popularity.…”
Section: Introductionmentioning
confidence: 99%
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“…A back propagation algorithm based control algorithm for power quality improvement is shown in [7]. A control algorithm which uses neural network based conductance estimation is shown in [8].…”
Section: Introductionmentioning
confidence: 99%