An inverter repetitive control design method based on a neural network

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...

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 boundary, the dynamic response and control accuracy of the system It will be affected accordingly, so that the system cannot meet the original control requirements, and in severe cases, it may even appear "unstable", resulting in out-of-control damage to equipment and personal injury accidents

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