分数级神经滑动模式控制,基于FO-汉默斯坦模型的压电驱动器
Liu Yang1, Zhongyang Zhao1, Dongjie Li1
1School of Automation, Harbin University of Science and Technology, Harbin 150040, China.
ISA transactions
|September 2, 2023
概括
本研究引入了一种新的分数顺序神经滑动模式控制方法,通过减轻取决于速率的歇斯底里作用来提高压电执行器 (PEA) 的精度和稳定性. 新方法展示了更快的响应时间和更少的跟踪错误的优越性能.
科学领域:
- 控制系统工程 控制系统工程
- 材料科学 材料科学 材料科学
- 机械电子学是什么意思 机械电子学
背景情况:
- 压电驱动器 (PEA) 对于高精度应用至关重要,但遭受了取决于速率的歇斯底里,影响了精度和稳定性.
- 现有的控制方法很难完全弥补PEA复杂的动态特性.
研究的目的:
- 开发一个先进的反控制系统,以减少PEA对定位系统的取决于速率的影响.
- 为准确的PEA动态建模提出一种新的分数顺序积分滑动模式表面.
- 通过分数神经滑动模式控制 (BP-FSMC) 方法来提高控制性能.
主要方法:
- 使用分数顺序汉默斯坦模型 (FO-汉默斯坦) 来表示PEA动态.
- 提出了一种新的滑动模式表面,将分数多项式和积分项结合起来.
- 实施了分数神经滑动模式控制 (BP-FSMC) 策略.
- 采用神经网络和修改的人工蜂群算法 (DeC-ABC) 来进行参数优化.
主要成果:
- 拟议的BP-FSMC方法有效地界定了PEA的动态特性,并最大限度地减少了静态错误.
- 该系统在跟踪复合和单个输入信号方面表现出高度的弹性.
- 与现有的分数顺序滑动模式控制方法相比,实现了显著更快的响应时间和更低的跟踪错误.
结论:
- 开发的分数顺序神经滑动模式控制方法为提高高精度系统中PEA性能提供了强大的解决方案.
- 这种方法提供了卓越的准确性和稳定性,优于传统的控制策略.
- 该方法可以适应由分数顺序模型和分数转移函数描述的各种系统.
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