An inverter repetitive control design method based on a neural network

A repetitive control, neural network technology, applied in the field of power electronics, can solve problems such as instability, equipment out-of-control damage, personal injury, etc., to improve high-frequency stability, avoid the impact of repetitive control, and improve stability and robustness Effect

Active Publication Date: 2019-01-08
ELECTRIC POWER RESEARCH INSTITUTE OF STATE GRID SHANDONG ELECTRIC POWER COMPANY +1
View PDF1 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Considering that the system parameters will change with the operation of the device, the possibility of mismatch between the control parameters of the repeated control link and the original system will also increase. When the parameters gradually change beyond the system stability bounda

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
  • An inverter repetitive control design method based on a neural network
  • An inverter repetitive control design method based on a neural network
  • An inverter repetitive control design method based on a neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0024] refer to figure 1 , the concrete design steps of the present invention are as follows:

[0025] Step 1: Use control theory to analyze the traditional transfer function of the inverter, and select an appropriate control algorithm for the bottom layer control of the inverter. The neural network algorithm is used to identify the theoretical model offline, and the basic structure of the model is selected to obtain the initial parameters of the neural network identification model.

[0026] figure 2 It is the schematic diagram of the structure of the selected inverter, which is a voltage-type current inverter. Impedance devices are connected in series on the AC side of the inverter, representing the impedance characteristics of the controlled objects (motor, transformer, reactor, etc.) in the actual system , and its structure is simplified and analyzed, the inverter modulation command r can be obtained * The open-loop transfer function G to the actual output u p .

[00...

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 an inverter repetitive control design method based on a neural network. The method includes the following steps: 1, analyzing that traditional transfer function of the inverterby using the control theory, selecting an appropriate control algorithm for the bottom control of the inverter, identifying the theoretical model offline by use the neural network algorithm, and obtaining the initial parameters of the model by selecting the basic structure of the model; 2, taking the obtained initial identification model as a reference for on-line identification learning, and obtaining the actual identification model of the traditional control closed loop of the inverter; 3, constructing an inverse transfer function by utilizing that identification model information to replace the repeat control compensation link; 4, storing that parameters of the identify model in real time, and importing the latest data of the learning model of the system every time the identification model is put into the device. The method of the invention saves a large amount of tedious work of parameter design and selection, avoids the influence of parameter drift on repetitive control, improvesthe stability and robustness of repetitive control links, and can be popularized and used in inverters and related fields.

Description

technical field [0001] The invention belongs to the field of power electronics, and in particular relates to a neural network-based inverter repetitive control design method. Background technique [0002] In order to achieve precise tracking of high-frequency signals and suppression of high-frequency interference, power electronic inverters need to use specific control algorithms to improve control accuracy and achieve excellent control effects. Common control methods include PI control, proportional resonance control, robust control, and repetitive control, etc. Among them, the repetitive control based on the inner membrane principle has the characteristics of simple structure, stability and high efficiency, and can theoretically realize integer multiple harmonics. Differential tracking control, widely used in frequency converters, high-speed motors and active filters and other fields. [0003] Repeated control uses the inner membrane principle, and its control structure i...

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
IPC IPC(8): G06F17/50G06N3/04
CPCG06F30/20G06N3/045Y02E40/40
Inventor 王华佳王德丽王庆玉张岩赵康张青青张高峰邢鲁华麻常辉
Owner ELECTRIC POWER RESEARCH INSTITUTE OF STATE GRID SHANDONG ELECTRIC POWER COMPANY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap