Gantry Crane Position Control via Parallel Feed-forward Compensator

Author(s):  
Ievgen Golovin ◽  
Anton Maksakov ◽  
Stefan Palis
2019 ◽  
Vol 109 (05) ◽  
pp. 352-357
Author(s):  
C. Brecher ◽  
L. Gründel ◽  
L. Lienenlüke ◽  
S. Storms

Die Lageregelung von konventionellen Industrierobotern ist nicht auf den dynamischen Fräsprozess ausgelegt. Eine Möglichkeit, das Verhalten der Regelkreise zu optimieren, ist eine modellbasierte Momentenvorsteuerung, welche in dieser Arbeit aufgrund vieler Vorteile durch einen Machine-Learning-Ansatz erweitert wird. Hierzu wird die Umsetzung in Matlab und die simulative Evaluation erläutert, die im Anschluss das Potenzial dieses Konzeptes bestätigt.   The position control of conventional industrial robots is not designed for the dynamic milling process. One possibility to optimize the behavior of the control loops is a model-based feed-forward torque control which is supported by a machine learning approach due to many advantages. The implementation in Matlab and the simulative evaluation are explained, which subsequently confirms the potential of this concept.


2011 ◽  
Vol 299-300 ◽  
pp. 856-859
Author(s):  
Yong Cao ◽  
De Jun Luo ◽  
Hua De Li

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.


2020 ◽  
Vol 13 (4) ◽  
pp. 366-377 ◽  
Author(s):  
Bingwei Gao ◽  
Yongtai Ye

Background: In some applications, the requirements of electro-hydraulic servo system are not only precise positioning, but also the speediness capability at which the actuator is operated. Objective: In order to enable the system to achieve rapid start and stop during the work process, reduce the vibration and impact caused by the change of the velocity, at the same time improve the positioning accuracy, and further strengthen the stability and the work efficiency of the system, it is necessary to perform the synergistic control between the position and the velocity of the electrohydraulic servo system. Methods: In order to achieve synergistic control between the position and the velocity, a control method of velocity feed-forward and position feedback is adopted. That is, based on the position control, the speed feed-forward is added to the outer loop as compensation. The position control adopts the PID controller, and the velocity control adopts the adaptive fuzzy neural network controller. At the same time, the position and velocity sensors are used for feedback, and the deviation signals between the position and the velocity obtained by superimposing the feedback are used as the final input of the control object, thereby controlling the whole system. Results: The control effect of the designed position / velocity synergistic controller is verified by simulation and experiment. The results show that the designed controller can effectively reduce the vibration and impact caused by the change of the velocity, and greatly improve the response velocity and the position accuracy of the system. Conclusion: The proposed method provides technical support for multi-objective synergistic control of the electro-hydraulic servo system, completes the requirements of multi-task operation, improves the positioning accuracy and response velocity of the electro-hydraulic servo system, and realizes the synergy between the position and the velocity. In this article, various patents have been discussed.


2014 ◽  
Vol 555 ◽  
pp. 186-191 ◽  
Author(s):  
Mamoru Minami ◽  
Ken Adachi ◽  
Satoshi Sasaki ◽  
Akira Yanou

This research aims to achieve a new grinding robot system that can grind an object into desired shape with force-sensorless feed-forward control. However, there is a problem that vibration occurs during the grinding work has emerged, which makes the accuracy of the grinding become worse. Therefore, this paper proposes a method that changes the gain of position control for suppressing the vibration. Results observed by real grinding experiment have confirmed how our proposed method effectively improved accuracy of the grinding.


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