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基于DE-RBF神经网络的短电弧脉冲电源恒压控制
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国家自然科学基金资助项目(51765063);自治区重点研发计划项目课题资助(2018B02009-1;2018B02009-4)


Constant Voltage Control of Short Arc Pulse Power Supply Based on DE-RBF Neural Network
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    摘要:

    为获得较好的短电弧脉冲电源稳压效果,实现短电弧加工高效率、低损耗的目的,提出了一种基于差分进化算法(DE)优化RBF神经网络的PID控制策略。建立了MATLAB/Simulink电源系统仿真模型,仿真对比分析了传统PID及RBF PID控制策略,并进行了短电弧铣削加工对比实验。结果表明:新型控制策略下的脉冲电源输出稳定、抗干扰性强、稳压效果好,加工效率提升59.7%,相对电极损耗减少3.07%。

    Abstract:

    In order to obtain better voltage stabilizing effect of short arc pulse power supply and to achieve the purpose of high efficiency and low loss for short arc processing, a Proportion Integral Derivative (PID) control strategy based on differential evolution algorithm (DE) to optimize Radial Basis Function (RBF) neural network is proposed. The simulation model of MATLAB/Simulink power system was established. The traditional PID and RBF PID control strategies were compared and analyzed, and the comparison experiment of short arc milling was carried out. The results show that the output of the pulse power supply under the new control strategy has stable output, strong anti-interference and good voltage regulation effect. The processing efficiency is increased by 597% and the relative electrode loss is reduced by 307%.

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孟崇崇,周建平,胡国玉.基于DE-RBF神经网络的短电弧脉冲电源恒压控制[J].机床与液压,2019,47(19):16-19.
. Constant Voltage Control of Short Arc Pulse Power Supply Based on DE-RBF Neural Network[J]. Machine Tool & Hydraulics,2019,47(19):16-19

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  • 在线发布日期: 2020-03-12
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