Abstract
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.
Keywords: Adaptive fuzzy neural network control, electro-hydraulic servo system, position/velocity synergistic control, PID control, position feedback, velocity feed-forward.
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