Inversion-based fuzzy adaptive control with prespecifiable tracking accuracy for uncertain hysteretic systems

IF 3.2 1区数学 Q2 COMPUTER SCIENCE, THEORY & METHODS

Fuzzy Sets and Systems Pub Date : 2024-09-27 DOI:10.1016/j.fss.2024.109141

Zihao Wu , Weijun Huang , Kai Huang , Zhi Liu , Guanyu Lai , Hanzhen Xiao , C.L. Philip Chen

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引用次数: 0

Abstract

Inversion-based control strategies have the outstanding effectiveness in the compensation for hysteresis nonlinearities. However, when the plant is driven by smart material-based actuator with the information absence of hysteresis output, there still exist technical gaps in the construction of hysteresis inverse controller. Therefore, this study aims to address this gap by proposing a novel control scheme. Technically, a novel hysteresis inverse algorithm, significantly reducing computational burden, has been proposed based on a novel adaptive estimation method for the unknown parameter (density function) in the Preisach-typed hysteresis nonlinearity. Furthermore, the inverse compensation error, the nonlinearities and uncertainties appeared in the controlled plant are accommodated by the innovative adaptive fuzzy feedback controller. With our scheme, it can ensure that the closed-loop stability, predefined steady-stated tracking performance and the convergence of algorithms including inverse algorithm and adaptive updating laws. In addition to theoretical analysis, we have validated the effectiveness of the proposed control scheme through simulation comparisons and experimental results conducted by the real-life piezoelectric actuator.

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基于反演的模糊自适应控制，为不确定滞后系统提供可预设的跟踪精度

基于反演的控制策略在补偿磁滞非线性方面具有显著效果。然而，当工厂由无滞后输出信息的智能材料制动器驱动时，滞后反控制器的构建仍存在技术空白。因此，本研究旨在通过提出一种新型控制方案来弥补这一空白。在技术上，本研究提出了一种新型的磁滞反算法，该算法基于一种新型的自适应估计方法，用于估计普雷萨克型磁滞非线性中的未知参数（密度函数），从而大大减轻了计算负担。此外，创新的自适应模糊反馈控制器还能适应被控设备中出现的反向补偿误差、非线性和不确定性。通过我们的方案，可以确保闭环稳定性、预定义的稳态跟踪性能以及包括逆算法和自适应更新规律在内的算法的收敛性。除理论分析外，我们还通过仿真比较和实际压电致动器的实验结果验证了所提控制方案的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Fuzzy Sets and Systems 数学-计算机：理论方法

CiteScore

6.50

自引率

17.90%

发文量

321

审稿时长

6.1 months

期刊介绍： Since its launching in 1978, the journal Fuzzy Sets and Systems has been devoted to the international advancement of the theory and application of fuzzy sets and systems. The theory of fuzzy sets now encompasses a well organized corpus of basic notions including (and not restricted to) aggregation operations, a generalized theory of relations, specific measures of information content, a calculus of fuzzy numbers. Fuzzy sets are also the cornerstone of a non-additive uncertainty theory, namely possibility theory, and of a versatile tool for both linguistic and numerical modeling: fuzzy rule-based systems. Numerous works now combine fuzzy concepts with other scientific disciplines as well as modern technologies. In mathematics fuzzy sets have triggered new research topics in connection with category theory, topology, algebra, analysis. Fuzzy sets are also part of a recent trend in the study of generalized measures and integrals, and are combined with statistical methods. Furthermore, fuzzy sets have strong logical underpinnings in the tradition of many-valued logics.