一个基于通用控制器的动态线性化无模型自适应控制及其对PMLSM的应用
Xian Yu1, Jingyu Fang1, Juanping Zhu2
1College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, 518060, Guangdong, PR China.
这项研究增强了使用动态线性化对未知非线性系统的无模型自适应控制. 数据驱动的方法确保了跟踪错误的局限性,并改进了数学分析.
科学领域:
- 控制工程 控制工程 控制工程
- 系统理论系统理论
- 非线性动力学是一种非线性动力学.
背景情况:
- 现有的无模型自适应控制 (MFAC) 方法对复杂系统有局限性.
- 非线性,非亲缘的离散时间系统带来了重要的控制挑战.
- 动态线性化为简化控制设计提供了一个有希望的方法.
研究的目的:
- 扩展和改进基于控制器的动态线性化无模型自适应控制方法.
- 为未知非线性非亲系离散时间系统开发数据驱动的控制方法.
- 在不那么严格的条件下分析跟踪错误的边界性.
主要方法:
- 全形动态线性化数据模型和控制器设计.
- 简化牛顿型优化与自适应估计算法.
- 数学感应,格尔斯戈林盘,和收缩映射原理用于分析.
主要成果:
- 拟议的方法整合了紧和部分形式模型.
- 改进了对追踪错误的终极边界度的分析.
- 使用永久磁铁线性同步电机的证明有效性.
结论:
- 增强的MFAC方法对未知的非线性系统有效.
- 数据驱动的方法提供了强大的跟踪性能.
- 这种方法在各种工程领域都有潜在的应用.
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