Disturbance Observer based Internal Model Control for Three Phase LCL-type Inverter

2019 ◽  
Author(s):  
Jinmu Lai ◽  
Xianggen Yin ◽  
Zhen Wang ◽  
Langzi Li ◽  
Zhenyu Qi ◽  
...  
Keyword(s):  
Internal Model ◽  
Disturbance Observer ◽  
Internal Model Control ◽  
Three Phase ◽  
Model Control

Internal Model Control of Three-Phase Four-Leg Active Power Filter Based on Online LS-SVM ANN Inverse System Method

2011 ◽  
Vol 383-390 ◽  
pp. 2132-2137
Author(s):  
Hong Qi ◽  
Zhen Hua Shao
Keyword(s):  
Internal Model ◽  
Active Power Filter ◽  
Coupling Model ◽  
Active Power ◽  
Internal Model Control ◽  
Inverse System ◽  
Control Effect ◽  
Power Filter ◽  
Three Phase ◽  
Model Control

In dealing with the problem of the SAPF’s nonlinear and strong coupling model, the internal model control of three-phase four-leg active power filter based on online ANN method is studied in this paper. With the ANN’s nonlinear mapping ability of self-learning and self-organizing modeling, the inverse system can be approximated by online LS-SVM. In order to have a good linearization control effect, the internal model control based on ANN is proposed for the combined pseudo-linear system. This method can be used to design effective controllers for nonlinear system with unknown mathematical models. At last, the simulation results show that a good steady-state performance can be obtained under the improved method

scholarly journals An Internal Model Controller for Three-Phase APF Based on LS-Extreme Learning Machine

2014 ◽  
Vol 8 (1) ◽  
pp. 717-722
Author(s):  
Zhenhua Shao ◽  
Tianxiang Chen ◽  
Li-an Chen ◽  
Hong Tian
Keyword(s):  
Control System ◽  
Least Squares ◽  
Extreme Learning Machine ◽  
Internal Model ◽  
Internal Model Control ◽  
Support Vector ◽  
Three Phase ◽  
Model Control ◽  
Internal Model Controller ◽  
Learning Machine

Aiming at the problem that the three-phase APF’s dynamic model is a multi-variable, nonlinear and strong coupling system, an internal model controller for three-phase APF based on LS-Extreme Learning Machine is studied in this paper. As a novel single hidden layer feed-forward neural networks, extreme learning machine (ELM) has several advantages: simple net structural, fast learning speed, good generalization performance and so on. In order to improve the controller’s dynamic responses, a least squares extreme learning machine for internal model control is proposed. A least squares ELM regression (LS-ELMR) model for the three-phase APFS on-line monitoring was built from external factors with in-out datum. Moreover, the relative stable error is presented to evaluate the system performance and the features for the internal model control system based on extreme learning machine, neural network, kernel ridge regress and support vector machine. The experimental results show that the LS-internal model control system based on extreme learning machine has good dynamic performance and strong filtering result.

Design of Disturbance Observers for Multi-Input Multi-Output Systems

2008 ◽  
Vol 130 (3) ◽  
Author(s):  
S. M. Shahruz
Keyword(s):  
Internal Model ◽  
Disturbance Observer ◽  
Simple Structure ◽  
Mimo Systems ◽  
Design Procedure ◽  
Internal Model Control ◽  
Model Control ◽  
System Inversion ◽  
Inversion Techniques ◽  
Standing Problem

In this paper, the long-standing problem of designing disturbance observers for multi-input multi-output (MIMO) systems is solved. The disturbance observer presented here has a simple structure equivalent to that of the internal model control (IMC), thereby there is no need for the system inversion. Techniques to design the proposed disturbance observer are given. Furthermore, the design procedure is illustrated via examples for different MIMO systems.

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