3DoF-KF HMPC:一种基于卡尔曼波器的混合模型预测控制算法,用于混合逻辑动态系统
Owais Khan1, Mohamed El Mistiri1, Sarasij Banerjee1
1Control Systems Engineering Laboratory, School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ 85287 USA.
概括
本研究引入了混合系统的混合模型预测控制 (HMPC),增强了设定点跟踪和干扰拒绝. 先进的控制方案确保了复杂,不确定的环境中的稳定性和性能.
科学领域:
- 控制系统工程 控制系统工程
- 混合系统分析 混合系统分析
- 优化理论 优化理论
背景情况:
- 混合系统由于它们的混合连续和离散动态,因此存在重大控制挑战.
- 现有的控制策略往往难以应对混合系统固有的干扰和不确定性.
研究的目的:
- 在混合逻辑动态 (MLD) 框架内开发和验证用于混合系统的新型混合模型预测控制 (HMPC) 方案.
- 为了提高混合系统控制器的设定点跟踪精度和干扰排斥能力.
- 为了证明拟议的HMPC在各种应用中的多功能性和有效性.
主要方法:
- 混合模型预测控制 (HMPC) 方案的制定和设计.
- 整合了三度自由度 (3DoF) 调方法,以实现精确的控制.
- 包括设定点和干扰预测,以积极提升性能.
- 利用松变量来保持混合整数二次编程问题的可行性.
主要成果:
- 该HMPC方案有效地管理混合动力,实现精确的设定点跟踪.
- 证明了对测量和未测量的干扰和系统不确定性的稳定性.
- 在各种案例研究中成功应用,包括生产库存系统,体育活动干预和流行病预防.
结论:
- 拟议的HMPC算法为控制具有复杂动态的混合系统提供了强大的和有效的解决方案.
- 控制器在设定点跟踪和干扰拒绝方面表现出强的性能,即使在非线性和不确定性条件下.
- 通过在各种各样的,苛刻的现实场景中成功实施,证实了HMPC的适应性.
相关概念视频
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