BP Neural Network PID Variable Pressure Control of Airborne Pump Source

L. Jing, Guo Zongzhi, Wu Shuangwei
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Abstract

Supply pressure control of the aircraft hydraulic pump is of great importance. However, the pressure control system of variable displacement axial piston pumps is significantly affected by fast changing, unknown loads and time-varying parameters. In the present paper, PID control strategy based on BP neural network was proposed to improve the tracking performance of the piston pump outlet pressure. First, the working principle and the mathematical model of the aircraft variable pressure hydraulic system are described. Then the architecture of the BP neural network and the structure of the PID controller are established. In this control strategy, the PID controller parameters kp, ki, kd can be adjusted online through the neural network in order to achieve an excellent control effect. Finally, simulation results demonstrate that there is a good supply pressure tracking performance under the proposed control strategy.
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机载泵源的BP神经网络PID变压力控制
飞机液压泵的供油压力控制具有十分重要的意义。然而,变量轴向柱塞泵的压力控制系统受快速变化、未知载荷和时变参数的影响较大。本文提出了基于BP神经网络的PID控制策略,以改善柱塞泵出口压力的跟踪性能。首先,介绍了飞机变压液压系统的工作原理和数学模型。然后建立了BP神经网络的结构和PID控制器的结构。在该控制策略中,PID控制器参数kp、ki、kd可以通过神经网络在线调节,以达到良好的控制效果。仿真结果表明,该控制策略具有良好的供电压力跟踪性能。
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