| 基于改进麻雀搜索算法的分数阶混沌系统参数辨识 |
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| 引用本文：李悠1，彭越兮2.基于改进麻雀搜索算法的分数阶混沌系统参数辨识[J].计算技术与自动化,2024,(3):88-94 |
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| 中文摘要:混沌系统的参数辨识是非线性科学中的一个经典反问题。由于智能优化算法的高效率和鲁棒性，利用算法对混沌系统进行参数辨识已成为近年来兴起的热点话题。本文致力于针对分数阶定义下的混沌系统进行参数辨识研究，在经典麻雀搜索算法的基础上提出随机扰动和Lévy局部飞行搜索的改进方式，并对分数阶Chen混沌系统和分数阶Lorenz混沌系统进行了参数辨识。仿真实验在6种不同的智能优化算法中进行，其结果证明了所提出的改进麻雀搜索算法具有更快的收敛速率和更高的辨识精度，并能够保证所有的辨识参数与原始参数的误差在10-4以下。研究成果可为非线性系统的智能同步控制提供新的解决办法。 |
| 中文关键词:分数阶微积分 混沌系统 参数辨识 麻雀搜索算法 |
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| Parameter Identification of Fractional-order Chaotic Systems Based on Improved Sparrow Search Algorithm |
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| Abstract:Parameter identification of chaotic systems is a classical inverse problem in nonlinear science. Due to the high efficiency and robustness of intelligent optimization algorithm, parameter identification of chaotic system based on intelligent optimization algorithm has become a hot topic in recent years. This paper focuses on the parameter identification of fractional-order chaotic system. Based on the classical sparrow search algorithm, an improved sparrow search algorithm which introduced a random disturbance and the Lévy local flight search is proposed. The identified systems were selected as fractional-order Chen chaotic system and fractional-order Lorenz chaotic system, and simulation were carried out in six different intelligent optimization algorithms. The results demonstrate that the improved sparrow search algorithm has faster convergence rate and higher identification accuracy, and it can ensure that the error of identified parameters are less than 10-4. The research results can provide a new solution for intelligent synchronization control of nonlinear systems. |
| keywords:fractional order chaotic system parameter identification sparrow search algorithm |
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