基于RBF神经网络电液恒功率调速自整定PID控制 |
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引用本文: | 王雪丽. 基于RBF神经网络电液恒功率调速自整定PID控制[J]. 机床与液压, 2016, 44(22): 115-117. DOI: 10.3969/j.issn.1001-3881.2016.22.034 |
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作者姓名: | 王雪丽 |
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作者单位: | 长春职业技术学院,吉林长春,130033 |
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基金项目: | 国家自然科学基金项目(60674066) |
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摘 要: | 采煤机电液调速系统对保证煤矿生产具有重要的作用。在分析恒功率自动调速的电液控制系统原理的基础上,建立了基于RBF神经网络自整定的PID控制的数学模型。通过在MATLAB/GUI仿真平台上计算得到系统的实际输出和模型输出的误差不超过5%,设计的RBF神经网络的电液恒功率调速自整定PID控制系统具有更高的跟踪精度和响应特性,完全可以实现系统的高精度与快速调速控制。
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关 键 词: | 电液调速 RBF神经网络 自整定PID 响应特性 |
Self tuning PID Control of Electric Hydraulic Constant Power Speed Regulation Based on RBF Neural Network |
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Abstract: | The electrical hydraulic speed control system of coal mining mechanical plays an important role to ensure the coal mine production .Based on the analysis about the principle of the electro-hydraulic control system of constant power automatic speed control , the mathematical model of the self-tuning PID control was built by using the RBF neural network self-tuning PID control strategy .By MATLAB/GUI simulation platform , the output error between the real output and the model output was less than 5%.It is shown the designed electric hydraulic constant power speed regulation self-tuning PID control system has higher tracking precision and response characteristics , by which high precision and fast speed regulation control can be achieved . |
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Keywords: | Electric hydraulic speed regulating RBF neural network Self-tuning PID Response characteristics |
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