Disturbance rejection of two-dimensional repetitive control system based on T-S fuzzy model

Author(s):  
Shengnan Tian ◽  
Min Wu ◽  
Manli Zhang ◽  
Chengda Lu ◽  
Luefeng Chen ◽  
...  
2016 ◽  
Vol 25 (06) ◽  
pp. 1650061 ◽  
Author(s):  
Zhen Shao ◽  
Zhengrong Xiang

This paper concerns the design of an observer-based repetitive control system (RCS) to improve the periodic disturbance rejection performance. The periodic disturbance is estimated by a repetitive learning based estimator (RLE) and rejected by incorporation of the estimation into a repetitive control (RC) input. Firstly, the configuration of the observer-based RCS with the RLE is described. Then, a continuous–discrete two-dimensional (2D) model is built to describe the RCS. By choosing an appropriate Lyapunov functional, a sufficient condition is proposed to guarantee the stability of the RCS. Finally, a numerical example is given to verify the effectiveness of the proposed method.


2014 ◽  
Vol 70 ◽  
pp. 100-108 ◽  
Author(s):  
Rui-Juan Liu ◽  
Guo-Ping Liu ◽  
Min Wu ◽  
Jinhua She ◽  
Zhuo-Yun Nie

2016 ◽  
Vol 26 (2) ◽  
pp. 285-295 ◽  
Author(s):  
Lan Zhou ◽  
Jinhua She ◽  
Chaoyi Li ◽  
Changzhong Pan

Abstract This paper concerns the problem of designing an EID-based robust output-feedback modified repetitive-control system (ROFMRCS) that provides satisfactory aperiodic-disturbance rejection performance for a class of plants with time-varying structured uncertainties. An equivalent-input-disturbance (EID) estimator is added to the ROFMRCS that estimates the influences of all types of disturbances and compensates them. A continuous-discrete two-dimensional model is built to describe the EID-based ROFMRCS that accurately presents the features of repetitive control, thereby enabling the control and learning actions to be preferentially adjusted. A robust stability condition for the closed-loop system is given in terms of a linear matrix inequality. It yields the parameters of the repetitive controller, the output-feedback controller, and the EID-estimator. Finally, a numerical example demonstrates the validity of the method.


2020 ◽  
Vol 106 ◽  
pp. 97-108
Author(s):  
C. Antony Crispin Sweety ◽  
S. Mohanapriya ◽  
O.M. Kwon ◽  
R. Sakthivel

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