Position tracking performance enhancement of linear ultrasonic motor with direct learning control technique

Author(s):  
K. Mainali ◽  
S.K. Panda ◽  
J.X. Xu
Actuators ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 20
Author(s):  
Manh Hung Nguyen ◽  
Hoang Vu Dao ◽  
Kyoung Kwan Ahn

In this paper, an active disturbance rejection control is designed to improve the position tracking performance of an electro-hydraulic actuation system in the presence of parametric uncertainties, non-parametric uncertainties, and external disturbances as well. The disturbance observers (Dos) are proposed to estimate not only the matched lumped uncertainties but also mismatched disturbance. Without the velocity measurement, the unmeasurable angular velocity is robustly calculated based on the high-order Levant’s exact differentiator. These disturbances and angular velocity are integrated into the control design system based on the backstepping framework which guarantees high-accuracy tracking performance. The system stability analysis is analyzed by using the Lyapunov theory. Simulations based on an electro-hydraulic rotary actuator are conducted to verify the effectiveness of the proposed control method.


AIP Advances ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 025238
Author(s):  
Danhong Lu ◽  
Qiuxiang Lin ◽  
Yanxiang Han ◽  
Bingxun Chen ◽  
Chunrong Jiang ◽  
...  

2021 ◽  
Vol 11 (12) ◽  
pp. 5468
Author(s):  
Elizaveta Shmalko ◽  
Askhat Diveev

The problem of control synthesis is considered as machine learning control. The paper proposes a mathematical formulation of machine learning control, discusses approaches of supervised and unsupervised learning by symbolic regression methods. The principle of small variation of the basic solution is presented to set up the neighbourhood of the search and to increase search efficiency of symbolic regression methods. Different symbolic regression methods such as genetic programming, network operator, Cartesian and binary genetic programming are presented in details. It is shown on the computational example the possibilities of symbolic regression methods as unsupervised machine learning control technique to the solution of MLC problem of control synthesis for obtaining the stabilization system for a mobile robot.


Author(s):  
Xiaofu Zhang ◽  
Guanglin Shi

This article presents a composite adaptive control method to improve the position-tracking performance of an electro-hydraulic system driven by dual constant displacement pump and dual servo motor named as a novel electro-hydraulic system with unknown disturbance. A composite adaptive controller based on backstepping method is designed to estimate the uncertainties of electro-hydraulic control system, including the damping coefficient and elastic modulus. In order to release the persistent excitation condition of conventional adaptive control, which is often infeasible in practice, a prediction error based on the online historical data is used to update the estimated parameters. Furthermore, a disturbance observer is used to estimate the disturbance including the unmeasurable load force, friction and other unmodeled disturbance. The experiment results are provided and compared with other methods to verify the effectiveness of the proposed method, and the results have indicated that the proposed method has a better position-tracking performance with the convergent estimated parameters.


2002 ◽  
Vol 35 (1) ◽  
pp. 61-66 ◽  
Author(s):  
Hyun-Sik Ahn ◽  
Joong-Min Park ◽  
Do-Hyun Kim ◽  
Ick Choy ◽  
Joong-Ho Song ◽  
...  

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