双重驱动的果蝇优化算法及其在PID控制器中的应用
作者:
作者单位:

1.天津财经大学;2.中央财经大学

作者简介:

通讯作者:

中图分类号:

TP273

基金项目:

国家社会科学基金项目;国家自然科学基金项目(青年项目);教育部人文社科项目


Double Drive Fruit Fly Optimization Algorithm and its application in PID Controller
Author:
Affiliation:

1.Tianjin University of Finance and Economics;2.Central University of Finance and Economics

Fund Project:

The National Social Science Foundation of China ;the National Natural Science Foundation of China; the Ministry of education of Humanities and Social Science project

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    摘要:

    针对传统群智能优化算法面临计算复杂性高、参数依赖性强、全局优化能力弱的问题,在传统果蝇优化算法中引入细菌趋化理论,提出一种基于双重驱动的果蝇优化算法。综合考虑优势果蝇群体和劣势果蝇群体的分布特点,提出多驱逐剂与多引诱剂的概念,并在二者的双重驱动下更新果蝇位置,避免传统果蝇方法在位置更新过程中单纯依靠局部最优(差)位置带来的无效搜索;利用果蝇适应值信息,提出多驱逐剂和多引诱剂的带权质心向量计算方法,自适应地确定果蝇搜索半径,避免传统方法面临的参数依赖性强问题。在典型测试函数上的实验结果表明,该算法较现有典型算法参数依赖性小、收敛精度高、收敛速度快,且用其优化后的PID控制器响应速度快,稳定性高,验证了其在PID参数优化领域的有效性。

    Abstract:

    In order to solve the problems of high computational complexity, strong parameter dependence and weak global optimization ability of traditional swarm intelligence optimization algorithm, a new fruit fly optimization algorithm based on double drive with the theory of bacterial chemotaxis was proposed. Considering the distribution of the superior and the inferior fruit fly groups, the concepts of multiple repellents and multiple attractants were proposed, and the location of fruit fly was updated under the double drive, so as to avoid the invalid search of the traditional methods which only depend on the local best (worst) fruit flies of the position updating process. Then, based on the fitness value information of the fruit flies, a weighted centroid vector calculation method of multiple repellents and multiple attractants was proposed to determine the searching radiuses of fruit flies adaptively and avoid the problem of strong parameter dependence faced by traditional methods. The experimental results on standard functions show that, the proposed method has lower parameter dependence, higher convergence accuracy and convergence speed than existing typical algorithms. Moreover, the PID controller optimized by the proposed method has high response speed and stability, showing the ability of the proposed algorithm on PID parameter optimization.

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  • 收稿日期:2020-01-10
  • 最后修改日期:2020-04-21
  • 录用日期:2020-04-22
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