Research on Iterative Learning Servo Controller of Permanent Magnet Linear Synchronous Motor

2011 ◽  
Vol 299-300 ◽  
pp. 856-859
Author(s):  
Yong Cao ◽  
De Jun Luo ◽  
Hua De Li
Keyword(s):  
Permanent Magnet ◽  
Position Control ◽  
Iterative Learning ◽  
Nonlinear Load ◽  
Feed Forward ◽  
Rbf Network ◽  
Position Signal ◽  
Position Controller ◽  
Feedback Error ◽  
Servo Controller

An iterative learning servo controller with RBF network feed-forward position compensation is proposed to control the mover of permanent magnet linear servo system to track reference position signal. The structure of RBF feed-forward position controller is analyzed in detail. The effective estimation of nonlinear load is realized by higher-order D-type iterative learning identification method. The feedback position control law was made up of load identification and feedback error signal. Finally, the simulation results demonstrate that this method can assure system obtains good servo performance.

A Position Control Scheme Using High-Order Iterative Learning Control for Permanent Magnet Linear Motor

2012 ◽  
Vol 546-547 ◽  
pp. 236-241
Author(s):  
Song Yang ◽  
Hang Ma ◽  
Jun You Yang ◽  
Huai Yang Shen ◽  
Sheng Quan Chang
Keyword(s):  
Permanent Magnet ◽  
Iterative Learning Control ◽  
Position Control ◽  
Learning Control ◽  
Linear Motor ◽  
Iterative Learning ◽  
High Order ◽  
State Uncertainty ◽  
Permanent Magnet Linear Motor ◽  
Point To Point

A high-order Iterative Learning Control (ILC) strategy is designed for Permanent Magnet Linear Motor (PMLSM). This iterative learning controller is designed to high-order open and closed loop PID-type. This paper gives the convergence conditions of the proposed controller and proves that the tracking bound is determined by the bounds of state uncertainty and output disturbance to the system. The proposed ILC strategy result shows that position precision of PMLSM in point-to-point motion can be effectively improved with this scheme. The experiments demonstrate that the presented ILC strategy is effective and robust.

A global robust iterative learning position control for current-fed permanent magnet step motors

Automatica ◽  
2011 ◽  
Vol 47 (1) ◽  
pp. 227-234 ◽  
Author(s):  
Stefano Bifaretti ◽  
Patrizio Tomei ◽  
Cristiano Maria Verrelli
Keyword(s):  
Permanent Magnet ◽  
Position Control ◽  
Iterative Learning

HYBRID ITERATIVE LEARNING CONTROL FOR POSITION TRACKING OF AN ELECTRO HYDRAULIC SERVO SYSTEM

2019 ◽  
Vol XVI (2) ◽  
pp. 31-42
Author(s):  
Mansoor Zahoor Qadri ◽  
Ahsan Ali ◽  
Inam-ul-Hassan Sheikh
Keyword(s):  
Iterative Learning Control ◽  
Position Control ◽  
Servo System ◽  
Learning Control ◽  
Iterative Learning ◽  
Feed Forward ◽  
Percent Improvement ◽  
Hydraulic Servo ◽  
Hydraulic Servo System ◽  
Feed Forward Controller

Accurate position control of an electro hydraulic servo system (EHSS) is a challenging task due to inherent system nonlinearities, parametric variations and un-modelled dynamics. Since feedback controllers alone cannot provide perfect tracking control, an integration of feedback and feed forward controller is required. A cascaded iterative learning control (ILC) technique for position control of EHSS is proposed in this paper. ILC is a feed forward controller which modifies the reference signal for a feedback fractional order proportional-integral-derivative (PID) controller by learning through current control input and previous error obtained through trails. Unlike other feed forward controllers, ILC works on signal instead of system which eliminates the need of complete knowledge of the system. As compared to other controllers, the proposed technique provides fast convergence without the need of reconfiguring the existing control loop. Simulation and experiments revealed the effectiveness of the proposed technique for EHSS. The obtained results indicated eight percent improvement in rise time and nearly twenty one percent improvement in the settling time.

Robust Two-degree-of-freedom Control Based on H∞ Method for PMSM Drive System

2020 ◽  
Vol 13 (4) ◽  
pp. 496-506
Author(s):  
Qixin Zhu ◽  
Lei Xiong ◽  
Hongli Liu ◽  
Yonghong Zhu ◽  
Guoping Zhang
Keyword(s):  
Control System ◽  
Control Theory ◽  
Position Control ◽  
Dynamic Performance ◽  
Servo System ◽  
Degree Of Freedom ◽  
Trade Off ◽  
Standard Design ◽  
Position Controller ◽  
Two Degree Of Freedom

Background: The conventional method using one-degree-of-freedom (1DOF) controller for Permanent Magnet Synchronous Motor (PMSM) servo system has the trade-off problem between the dynamic performance and the robustness. Methods: In this paper, by using H∞ control theory, a novel robust two-degree-of-freedom (2DOF) controller has been proposed to improve the position control performance of PMSM servo system. Using robust control theory and 2DOF control theory, a H∞ robust position controller has been designed and discussed in detail. Results: The trade-off problem between the dynamic performance and robustness which exists in one-degree-of-freedom (1DOF) control can be dealt with by the application of 2DOF control theory. Then, through H∞ control theory, the design of robust position controller can be translated to H∞ robust standard design problem. Moreover, the control system with robust controller has been proved to be stable. Conclusion: Further simulation results demonstrate that compared with the conventional PID control, the designed control system has better robustness and attenuation to the disturbance of load impact.

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