模型预测控制与适应式卡尔曼波器用于预混合轮增压天然气发动机
Wenyu Xiong1, Qichangyi Gong2,3, Songtao Huang4
1School of Intelligent Manufacturing, Jianghan University, Wuhan, 470056, China.
Scientific reports
|February 14, 2026
概括
这项研究引入了天然气发动机的新控制框架,提高了负载干扰下的性能. 适应式卡尔曼波器和增强调度模型预测控制 (MPC) 提高了发动机的稳定性和效率.
科学领域:
- 工程 工程师 工程师 工程师
- 控制系统 控制系统
- 汽车工程 汽车工程
背景情况:
- 由于复杂的动力学和未知的负载干扰,控制天然气发动机很困难.
- 现有的方法在多输入多输出 (MIMO) 系统中扎着强的合和延迟.
研究的目的:
- 为天然气发动机开发一个强大的控制框架,以应对未知的负载干扰.
- 通过自适应控制策略来提高发动机性能,稳定性和效率.
主要方法:
- 基于速率的模型预测控制 (MPC) 与增益调度方案的集成.
- 使用具有新适应机制的适应卡尔曼波器来估计负载扭矩.
- 在线扭矩估计计算平衡点并生成自适应增益调度参数.
主要成果:
- 适应式卡尔曼波器快速跟踪负载扭矩瞬态,同时最大限度地降低稳定状态噪声.
- 获得计划的MPC显著减少了速度和空气-燃料比率偏差.
- 实验验证显示,在负载变化后,过渡反应得到改善,沉时间缩短.
结论:
- 拟议的控制框架为天然气发动机提供了改进的干扰排斥.
- 适应性增益调度方法提高了发电发动机的实际适用性.
- 这种方法为动态发动机控制挑战提供了强大的解决方案.
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