Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Hybrid active direct current filter control method based on self-adaptive linear neurons

A technology of DC filter and control method, applied in biological neural network models, AC networks to reduce harmonics/ripples, harmonic reduction devices, etc., can solve problems such as poor robustness, small stability margin, and complex structure

Inactive Publication Date: 2013-04-24
SHANDONG UNIV
View PDF4 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Aiming at the shortcomings of the existing HVDC hybrid DC filter control strategy, such as small stability margin, poor robustness, complex structure, narrow filtering spectrum range and complex algorithm, a hybrid active DC filter based on an adaptive linear neuron network is provided. Filter Control Method

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Hybrid active direct current filter control method based on self-adaptive linear neurons
  • Hybrid active direct current filter control method based on self-adaptive linear neurons
  • Hybrid active direct current filter control method based on self-adaptive linear neurons

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0057] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0058] The structure of HVDC hybrid active DC filter control system based on linear neural network is shown in the attachment figure 1 shown. In the figure y r(k-1) is the sampling value of harmonic current at time k-1; u(k) is the control quantity at time k; y r (k+1), y d (k+1), ξ(k+1), y(k+1), e p (k+1) and e i (k+1) are respectively the reference quantity at time k+1 (that is, the negative value of the sampling value of the harmonic current at the converter side), the pre-measurement, the disturbance of the control object, the actual output of the control object, the output of the identifier, and the prediction error and identification errors. The network structure of a single linear neuron is attached figure 2 As shown, the input vector in the figure is

[0059] X=[x 1 ,x 2 ,...,x n ] T

[0060] where x i (i=1,2,...n, n is a natura...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a hybrid active direct current filter control method based on self-adaptive linear neuron networks. The hybrid active direct current filter control method includes a first step of establishing a model of a hybrid active direct current filter as a controlled object, a second step of using the three linear neuron networks respectively as a recognizer, a controller and a predictor, and establishing a control system for the controlled object, a third step of using the recognizer to track the dynamic characteristics of the controlled object, and enabling the dynamic characteristics to be reflected on weighted vectors of the linear neuron networks, a fourth step of enabling the controller to do timely adjustment according to the dynamic changes of network parameters of the third step, and providing excellent control quantity, and a fifth step of enabling the predictor to compensate inherent hysteresis quality of the control system through a learning principle. Through the learning principle of the self-adaptive linear neuron networks to track the dynamic characteristics of the controlled object in real time and adjust the parameters of the controller on line, the hybrid active direct current filter control method solves the problems of uncertainty and time-varying characteristics of the parameters of the controlled object, and enables the performance of a hybrid active direct current filter control system to reach the optimum.

Description

technical field [0001] The invention relates to an HVDC hybrid active DC filter (HADF, Hybrid Active DC Filter) control method based on an adaptive linear neuron (ADALINE, Adaptive Linear Neuron) network. Background technique [0002] Due to the inherent shortcomings of passive filters and the rapid development of power electronics and digital signal processors (DSP), hybrid active DC filters have been applied to HVDC (high voltage direct current) DC side harmonic current filtering. The hybrid active DC filter combines the advantages of the large capacity of the passive filter and the good dynamic characteristics of the active filter, and is an ideal filtering device. [0003] However, the filtering effect of the hybrid active DC filter is largely affected by its control strategy. At present, comb filters or band-stop filters are mainly used as their closed-loop controllers. Some academic literatures in recent years have proposed other control strategies, such as control b...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/01G06N3/02
CPCY02E40/40
Inventor 李可军孙正
Owner SHANDONG UNIV
Features
  • Generate Ideas
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com