A novel disturbance observer based sliding mode combined repetitive learning control strategy for large range nanopositioning system

Author(s):  
Cunhuan Liu ◽  
Yongchun Fang ◽  
Ningning Qi
Author(s):  
Yan Zhang ◽  
Jian Liu ◽  
Yuteng Zhang ◽  
Ying Zhou ◽  
Lingling Chen

This article proposes a new adaptive sliding mode repetitive learning control strategy. The proposed controller can obtain satisfactory position tracking performance in the presence of unknown dynamics and external disturbance. The unknown dynamics parameters of the exoskeleton system can be estimated via an adaptive algorithm, which is used to design the sliding mode control law. Besides, the periodic external disturbance of the system can be compensated by repetitive learning to reduce the tracking error. The stability of the proposed method is demonstrated rigorous by the Lyapunov theory. Using an upper-limb exoskeleton model, simulation results demonstrate the effectiveness of the control strategy. The proposed method has a better control performance than other methods.


Electronics ◽  
2021 ◽  
Vol 10 (18) ◽  
pp. 2242
Author(s):  
Pengyu Qiao ◽  
Jun Yang ◽  
Chen Dai ◽  
Xi Xiao

The nonlinearities of piezoelectric actuators and external disturbances of the piezoelectric nanopositioning stage impose great, undesirable influences on the positioning accuracy of nanopositioning stage systems. This paper considers nonlinearities and external disturbances as a lumped disturbance and designs a composite control strategy for the piezoelectric nanopositioning stage to realize ultra-high precision motion control. The proposed strategy contains a composite disturbance observer and a continuous terminal sliding mode controller. The composite disturbance observer can estimate both periodic and aperiodic disturbances so that the composite control strategy can deal with the disturbances with high accuracy. Meanwhile, the continuous terminal sliding mode control is employed to eliminate the chattering phenomenon and speed up the convergence rate. The simulation and experiment results show that the composite control strategy achieves accurate estimation of different forms of disturbances and excellent tracking performance.


2020 ◽  
Vol 2020 ◽  
pp. 1-22 ◽  
Author(s):  
Xiangxiang Meng ◽  
Haisheng Yu ◽  
Herong Wu ◽  
Tao Xu

A novel method of disturbance observer-based integral backstepping control is proposed for the two-tank liquid level system with external disturbances. The problem of external disturbances can be settled in this paper. Firstly, the mathematical model of the two-tank liquid level system is established based on fluid mechanics and principle of mass conservation. Secondly, an integral backstepping control strategy is designed in order to ensure liquid level tracking performance by making the tracking errors converge to zero in finite time. Thirdly, a disturbance observer is designed for the two-tank liquid level system with external disturbances. Finally, the validity of the proposed method is verified by simulation and experiment. By doing so, the simulation and experimental results prove that the scheme of disturbance observer-based integral backstepping control strategy can suppress external disturbances more effective than the disturbance observer-based sliding mode control method and has better dynamic and steady performance of the two-tank liquid level system.


2011 ◽  
Vol 14 (4) ◽  
pp. 991-1001 ◽  
Author(s):  
Yu-Sheng Lu ◽  
Bing-Xuan Wu ◽  
Shu-Fen Lien

1999 ◽  
Vol 122 (1) ◽  
pp. 40-48 ◽  
Author(s):  
T. S. Liu ◽  
W. S. Lee

In order to make a robot precisely track desired periodic trajectories, this work proposes a sliding mode based repetitive learning control method, which incorporates characteristics of sliding mode control into repetitive learning control. The learning algorithm not only utilizes shape functions to approximate influence functions in integral transforms, but also estimates inverse dynamics functions based on integral transforms. It learns at each sampling instant the desired input joint torques without prior knowledge of the robot dynamics. To carry out sliding mode control, a reaching law method is employed, which is robust against model uncertainties and external disturbances. Experiments are performed to validate the proposed method. [S0022-0434(00)02001-3]


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