Hybrid genetic algorithm-system identification approach to model force sensing resistors

IF 2.4 3区 材料科学 Q3 MATERIALS SCIENCE, MULTIDISCIPLINARY Journal of Intelligent Material Systems and Structures Pub Date : 2023-04-07 DOI:10.1177/1045389X231167178
M. Saadeh
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Abstract

Force sensing resistor (FSR) is a passive component that is composed of polymer thick films that change resistance between its terminals due to force applied at its surface. FSRs inherently exhibit many nonlinear behaviors. This work employs a Genetic Algorithm agent to navigate the search space to identify the optimal modeling systems for five circular FSRs of comparable sizes. The Hybrid GA-System Identification allows the globally optimized models for the original systems to be identified without the need of a differentiable measure function or linearly separable parameters. The GA searches for the order of the linear model (zeros and poles), the input and output nonlinearities, and the order and the interval of these nonlinearities. Meanwhile, the system identification optimizes the locations of the poles and zeros as well as the parameters of the input and output nonlinearities. The synergy between the two agents allows the entire space to be evaluated for a global solution using the heuristic search advantage of the GA coupled with the fine-tuning of the parameters using the localized search advantage of the system identification. Results show that using the GA agent expedited the search process and allowed for reaching a globally optimized model.
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力感电阻模型的混合遗传算法系统辨识方法
力感电阻(FSR)是一种被动元件,由聚合物厚膜组成,由于施加在其表面的力而改变其端子之间的电阻。fsr固有地表现出许多非线性行为。这项工作采用遗传算法代理来导航搜索空间,以确定大小相当的五个圆形fsr的最佳建模系统。混合ga系统辨识允许辨识原始系统的全局优化模型,而不需要可微测量函数或线性可分参数。遗传算法搜索线性模型(零点和极点)的阶数,输入和输出非线性,以及这些非线性的阶数和区间。同时,系统辨识优化了极点和零点的位置以及输入输出非线性参数。两个代理之间的协同作用允许使用遗传算法的启发式搜索优势以及使用系统识别的局部搜索优势对参数进行微调来评估整个空间的全局解决方案。结果表明,使用GA代理加快了搜索过程,并允许达到全局优化模型。
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来源期刊
Journal of Intelligent Material Systems and Structures
Journal of Intelligent Material Systems and Structures 工程技术-材料科学:综合
CiteScore
5.40
自引率
11.10%
发文量
126
审稿时长
4.7 months
期刊介绍: The Journal of Intelligent Materials Systems and Structures is an international peer-reviewed journal that publishes the highest quality original research reporting the results of experimental or theoretical work on any aspect of intelligent materials systems and/or structures research also called smart structure, smart materials, active materials, adaptive structures and adaptive materials.
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