基于间隔灰色模型的通用预测控制与模式移动系统的自适应缓冲操作器
Ning Li1, Zhengguang Xu1, Xiangquan Li2
1School of Automation and Electrical Engineering, University of Science and Technology, Beijing, 100083, China.
Scientific reports
|August 25, 2025
概括
本研究为复杂的工业系统引入了一个新的间隔灰色自适应缓冲通用预测控制 (IGAB-GPC). 这种新方法显著减少了跟踪错误,提高了模式移动系统的控制精度.
科学领域:
- 控制工程
- 复杂系统分析
- 工业流程优化
背景情况:
- 在工业过程中常见的模式移动系统,如烧结和水泥,是复杂的非线性系统,由统计学规律支配.
- 现有的控制方法难以使用确定性变量来捕捉这些系统的统计性质,通常忽视它们的内在性质或将它们视为随机性.
- 这种局限性需要先进的控制策略,能够应对模式移动系统带来的独特挑战.
研究的目的:
- 开发一种新的控制策略,准确地捕捉模式移动系统的统计属性.
- 提高复杂工业过程中跟踪动态模式转换的精度.
- 提高复杂的不确定系统的干扰排斥能力.
主要方法:
- 提出了一种新的间隔灰色自适应缓冲通用预测控制 (IGAB-GPC),利用模式移动理论 (PMT) 的双向映射框架.
- 包含一个适应性缓冲操作器以减轻基于单调性的模式类序列的振荡.
- 开发了一个基于间隔灰色模型IGM ((1,2) 的预测模型用于不确定性分析,并实施了GPC控制方案,其中包括回归视界优化和反校正.
主要成果:
- 与CARIMA-GPC和IG-GPC相比,IGAB-GPC的追踪性能更好,追踪错误减少了大约两倍.
- 实现了0.0056的平均绝对误差 (MAE) 和0.0074的根平均平方误差 (RMSE),表明了高精度.
- 集成的自适应缓冲操作器,灰色系统建模和GPC有效地处理了系统的不确定性和改善了干扰排斥.
结论:
- IGAB-GPC策略有效量化模式类别变量,并精确地跟踪复杂非线性系统中的动态模式转换.
- 这种新的方法显著提高了以模式移动动态为特征的工业过程的控制精度和干扰排斥.
- 这项工作为从模式动态角度控制复杂的不确定系统提供了强大的框架.
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