无监督的最佳模型库用于多个模型控制系统:基于基因的自动集群方法.
Mohammad Fathi1, Hossein Bolandi1
1Electrical Engineering Department, Iran University of Science and Technology, Narmak, Tehran, Iran.
Heliyon
|February 23, 2024
概括
本研究介绍了一种基于GA的新型聚类方法,用于多模型控制 (MMC) 系统. 它优化了本地模型的数量和分布,以提高系统性能.
科学领域:
- 控制工程 控制工程 控制工程
- 人工智能的人工智能
- 航空航天工程 航空航天工程
背景情况:
- 多重模型控制 (MMC) 用于复杂系统的本地模型.
- 挑战包括确定这些模型的最佳数量和分布.
- 有效的MMC模型银行对于系统性能至关重要.
研究的目的:
- 为MMC系统开发一个最佳的模型银行.
- 为了应对模型数量和分布方面的挑战.
- 通过最佳的模型银行形成来提高MMC系统性能.
主要方法:
- 建议采用基于GA的自动集群方法.
- 一个新的无监督算法被设计用于最佳的模型银行确定.
- 将MMC概念映射到自动集群技术中.
主要成果:
- 提出的方法形成了一个全球最佳模型银行.
- 它避免了局部最佳,无论初始条件如何.
- 在航天器态度动态上表现出令人满意的性能.
结论:
- 基于GA的集群方法有效地优化了MMC模型银行.
- 该方法为复杂的MIMO,非线性系统提供了强大的解决方案.
- 通过航天器态度动力学案例研究来验证.
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