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Model-Following Controller Based on Neural Network for Variable Displacement Pump

机译:基于神经网络的模型 - 后续控制器可变排量泵

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The Electro-hydraulic proportional variable displacement axial piston pump (VDAPP) is widely used in heavy-load pump control system, which is inherently nonlinear, time variant and subjected to intensive disturbance. In this paper, a neural network model-following controller is proposed to approach the nonlinear anti-model of the object, and to realize the control of electro-hydraulic swashplate angle and flow, so that the uncertainty and nonlinear of the system can be compensated. The results of simulation and experiment show that the proposed neural network controller can conduct nonlinear control in VDAPP, enhance adaptability and robustness, and improve the performance of the control system.
机译:电动液压比例可变位移轴向活塞泵(VDAPP)广泛用于重载泵控制系统,这是固有的非线性,时间变体,并进行密集扰动。本文提出了一种神经网络模型控制器,以接近物体的非线性反模型,并实现电液涡旋角度和流量的控制,从而可以补偿系统的不确定性和非线性。模拟和实验结果表明,该提出的神经网络控制器可以在VDAPP中进行非线性控制,增强适应性和鲁棒性,提高控制系统的性能。

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