Based on inverse system of internal model control

2010 ◽  
Author(s):  
Zhang Yanhong ◽  
Zheng Zhongqiao
Keyword(s):  
Internal Model ◽  
Internal Model Control ◽  
Inverse System ◽  
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

Nonlinear Internal Model Control for Bearingless Induction Motor Based on Inverse System Theory

2014 ◽  
Vol 1037 ◽  
pp. 258-263
Author(s):  
Zheng Qi Wang ◽  
Xue Liang Huang
Keyword(s):  
System Theory ◽  
Induction Motor ◽  
Internal Model ◽  
Control Method ◽  
Internal Model Control ◽  
Inverse System ◽  
Inverse System Method ◽  
Coupling System ◽  
System Method ◽  
Model Control

The bearingless induction motor is a nonlinear, multi-variable and strongly coupling system. In this paper, a new nonlinear internal model control (IMC) strategy based on inverse system theory is proposed to realize the decoupling control for the bearingless induction motor. The mathematical model of the motor is built and then the inverse system method is applied to decouple the original nonlinear system. Finally the internal model control method is introduced to ensure the robustness of the closed-loop system. The effectiveness of the proposed strategy are demonstrated by simulation.

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