| 基于神经网络PID控制器的组合式空调机组温度控制方法 |
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| 引用本文：张印洲.基于神经网络PID控制器的组合式空调机组温度控制方法[J].计算技术与自动化,2025,(2):80-84 |
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| 中文摘要:组合式空调机组运行过程中，具有大迟延和大惯性的特性，这意味着单一控制系统对控制信号的响应存在明显的延迟和滞后。因此，提出了基于神经网络PID控制器的组合式空调机组温度控制方法。分析组合式空调机组温度阶跃响应变化，以分析结果为基础，借助动态矩阵分析历史温度数据，预测未来时刻空调机组输出温度，为温度控制提供依据。结合BP神经网络和PID调节器，搭建具有参数自适应整定性能的神经网络PID控制器。通过神经网络的自学习不断调整控制参数，最终实现高质量的空调机组温度控制。实验结果表明：该方法温度控制结果表现出的超调量总是不大于0.6%，极大提高了温度控制过程的稳定性。 |
| 中文关键词:BP神经网络 PID控制器 组合式空调机组 温度控制 参数整定 |
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| A Temperature Control Method for Combined Air Conditioning Units Based on Neural Network PID Controller |
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| Abstract:During the operation of a modular air conditioning unit, it has the characteristics of large delay and inertia, which means that there is a significant delay and lag in the response of a single control system to control signals. Therefore, a combined air conditioning unit temperature control method based on neural network PID controller is proposed. Analyze the temperature step response changes of the combined air conditioning unit. Based on the analysis results, using dynamic matrix to analyze historical temperature data, predict the output temperature of the air conditioning unit at future times, and provide a basis for temperature control. Build a neural network PID controller with parameter adaptive tuning performance by combining BP neural network and PID controller. By continuously adjusting control parameters through self learning of neural networks, high quality temperature control of air conditioning units is ultimately achieved. The experimental results show that the overshoot exhibited by this method in temperature control is always not greater than 0.6%, greatly improving the stability of the temperature control process. |
| keywords:BP neural network PID controller combination air conditioning unit temperature control parameter tuning |
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