Quadrant glitch compensation using friction model-based feedforward and an inverse-model-based disturbance observer

2008 ◽  
Author(s):  
Z. Jamaludin ◽  
H. Van Brussel ◽  
J. Swevers
Keyword(s):  
Disturbance Observer ◽  
Friction Model ◽  
Inverse Model ◽  
Model Based

Inverse model-based virtual sensors for detection of hard faults in air handling units

2021 ◽  
pp. 111493
Author(s):  
Narges Torabi ◽  
H. Burak Gunay ◽  
William O'Brien ◽  
Ricardo Moromisato
Keyword(s):  
Inverse Model ◽  
Virtual Sensors ◽  
Model Based ◽  
Air Handling Units

scholarly journals A New Linear Motor Force Ripple Compensation Method Based on Inverse Model Iterative Learning and Robust Disturbance Observer

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-19
Author(s):  
Xuewei Fu ◽  
Xiaofeng Yang ◽  
Zhenyu Chen
Keyword(s):  
Iterative Learning Control ◽  
Disturbance Observer ◽  
Learning Control ◽  
Inverse Model ◽  
Iterative Learning ◽  
Compensation Method ◽  
Tracking Accuracy ◽  
Linear Motors ◽  
Learning Speed ◽  
Force Ripple

Permanent magnet linear motors (PMLMs) are gaining increasing interest in ultra-precision and long stroke motion stage, such as reticle and wafer stage of scanner for semiconductor lithography. However, the performances of PMLM are greatly affected by inherent force ripple. A number of compensation methods have been studied to solve its influence to the system precision. However, aiming at some application, the system characteristics limit the design of controller. In this paper, a new compensation strategy based on the inverse model iterative learning control and robust disturbance observer is proposed to suppress the influence of force ripple. The proposed compensation method makes fully use of not only achievable high tracking accuracy of the inverse model iterative learning control but also the higher robustness and better iterative learning speed by using robust disturbance observer. Simulation and experiments verify effectiveness and superiority of the proposed method.

Backlash Robotic Systems Compensation by Inverse Model-Based PID Control

2019 ◽  
Author(s):  
Fernando da Fonseca Schneider ◽  
Cesar Bastos da Silva ◽  
Paulo Jefferson Dias de Oliveira Evald ◽  
Rodrigo Sousa e Silva ◽  
Rodrigo Zelir Azzolin
Keyword(s):  
Pid Control ◽  
Inverse Model ◽  
Robotic Systems ◽  
Model Based
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