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基于迭代学习的忆阻器电阻跟踪控制

Resistance Tracking Control of Memristors Based on Iterative Learning.

作者信息

Cao Wei, Qiao Jinjie

机构信息

College of Computer and Control Engineering, Qiqihar University, Qiqihar 161006, China.

College of Economics and Management, Qiqihar University, Qiqihar 161006, China.

出版信息

Entropy (Basel). 2023 May 10;25(5):774. doi: 10.3390/e25050774.

DOI:10.3390/e25050774
PMID:37238529
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10217619/
Abstract

A memristor is a kind of nonlinear two-port circuit element with memory characteristics, whose resistance value is subject to being controlled by the voltage or current on both its ends, and thus it has broad application prospects. At present, most of the memristor application research is based on the change of resistance and memory characteristics, which involves how to make the memristor change according to the desired trajectory. Aiming at this problem, a resistance tracking control method of memristors is proposed based on iterative learning controls. This method is based on the general mathematical model of the voltage-controlled memristor, and uses the derivative of the error between the actual resistance and the desired resistance to continuously modify the control voltage, making the current control voltage gradually approach the desired control voltage. Furthermore, the convergence of the proposed algorithm is proved theoretically, and the convergence conditions of the algorithm are given. Theoretical analysis and simulation results show that the proposed algorithm can make the resistance of the memristor completely track the desired resistance in a finite time interval with the increase of iterations. This method can realize the design of the controller when the mathematical model of the memristor is unknown, and the structure of the controller is simple. The proposed method can lay a theoretical foundation for the application research on memristors in the future.

摘要

忆阻器是一种具有记忆特性的非线性二端口电路元件，其电阻值受两端电压或电流的控制，因而具有广阔的应用前景。目前，大多数忆阻器应用研究基于电阻变化和记忆特性，这涉及如何使忆阻器按期望轨迹变化。针对这一问题，基于迭代学习控制提出了一种忆阻器电阻跟踪控制方法。该方法基于压控忆阻器的一般数学模型，利用实际电阻与期望电阻之间误差的导数不断修正控制电压，使当前控制电压逐渐逼近期望控制电压。此外，从理论上证明了所提算法的收敛性，并给出了算法的收敛条件。理论分析和仿真结果表明，所提算法能使忆阻器的电阻在有限时间间隔内随着迭代次数的增加而完全跟踪期望电阻。该方法在忆阻器数学模型未知时可实现控制器设计，且控制器结构简单。所提方法可为未来忆阻器的应用研究奠定理论基础。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8fc2/10217619/2d44183995a9/entropy-25-00774-g012.jpg

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