通过将鱼算法集成到PID控制系统中,对有机发光二极管温度控制的改进分析
1School of Intelligent Manufacturing and Elevator, Huzhou Vocational and Technical College, Huzhou, China.
PloS one
|July 22, 2025
概括
本研究介绍了一种改进的鱼优化算法 (WOA) -长期短期内存 (LSTM) 优化的PID控制器,用于精确的有机发光二极管 (OLED) 温度管理. 这种新方法显著提高了对温度敏感电子产品的控制精度和稳定性.
科学领域:
- 材料科学与工程 材料科学与工程
- 控制系统和自动化控制系统和自动化
- 人工智能和机器学习
背景情况:
- 有机发光二极管 (OLED) 对工作温度敏感,影响性能和寿命.
- 传统的比例积分导数 (PID) 控制器在与OLED温度控制的非线性和时间变化的特征作斗争.
- 精确的温度管理对于确保OLED显示器的可靠性和寿命至关重要.
研究的目的:
- 为OLED开发一种先进的温度控制策略,克服传统方法的局限性.
- 为了提高OLED温度控制系统的准确性,适应性和稳定性.
- 引入一款结合全球优化和时间序列分析能力的新型控制器.
主要方法:
- 提出了一个改进的PID控制器,集成长期短期记忆 (LSTM) 神经网络.
- 使用鱼优化算法 (WOA) 优化了PID控制器参数,用于增强的全球搜索.
- 通过热力学模型和实验数据分析验证了控制器的有效性.
主要成果:
- WOA-LSTM-PID控制器显著降低了超越 (8.5°C至0.3°C) 和稳定状态错误 (1.2°C至0.2°C).
- 实现了调节时间 (42.5秒到20.2秒) 和响应时间 (70.5秒到21.9秒) 的大幅缩短.
- 从5.23°C (传统PID) 到0.78°C的根平均平方误差显著下降.
结论:
- WOA-LSTM-PID控制器为OLED温度控制提供了卓越的准确性和稳定性.
- 提出的方法有效地解决了非线性和时间变化的系统动态.
- 联合WOA和LSTM方法为温度敏感系统提供了一个全新的,普遍适用的解决方案.
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