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基于量化观测和其应用的哈默斯坦式系统识别的自适应性规定的性能估计器
Huijie Lei1, Yanwei Zhang2, Xikun Lu3
1School of Electronic Information and Electrical Engineering, Anyang Institute of Technology, Anyang, 455000, People's Republic of China. anyang1109@163.com.
Scientific reports
|December 31, 2024
概括
本研究介绍了适应性规定的性能,用于识别与量化数据的汉默斯坦式系统中的参数. 它提高了参数估计中的短暂性能,解决了系统识别研究中的差距.
科学领域:
- 控制系统工程 控制系统工程
- 系统识别系统识别系统
- 适应性控制控制是适应性的
背景情况:
- 规定的性能技术为控制系统的稳定状态和短暂行为提供了定量见解.
- 在参数估计中改进过渡性能简化了控制器设计,减少了系统调节时间.
- 由于错误变量设计的挑战,对参数识别中的过渡性能的研究有限.
研究的目的:
- 开发一种适应性规定的性能方法,用于Hammerstein类系统中的参数识别,使用量化观测.
- 为了解决在参数识别中设计错误变量的难度,以实现暂时性能的参数识别.
- 为了提高参数估计的暂时性能,以改进控制系统设计.
主要方法:
- 将规定的性能技术集成到估计器设计中.
- 开发低通波器并迫使变量定义暂时性能的错误.
- 为参数估计误差界限引入了改进的规定的性能函数.
- 使用识别错误转换来重新构建系统并避免约束.
- 提出一个新的适应性法律,以保证规定的性能参数的识别.
主要成果:
- 成功地将规定的性能集成到Hammerstein类系统的参数识别中.
- 开发了一种方法来描述和绑定参数估计错误,使用一个改进的规定的性能函数.
- 证明了拟议的适应性法律在实现规定的性能方面的有效性.
- 通过模拟和过程示例验证了方法.
结论:
- 拟议的方法有效地解决了量子化哈默斯坦式系统参数识别中的过渡性能的挑战.
- 规定的性能技术的整合提供了一个可行的解决方案,以提高参数估计的准确性和短暂的行为.
- 这些发现有助于推进系统识别技术,特别是复杂的非线性系统.
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