改进的灰狼算法及其在运动体控制中的应用  

Application of Improved Grey Wolf Algorithm in Control of Moving Object

作　　者：赵鑫 李文 ZHAO Xin;LI Wen(Department of Electronic and Information Engineering,Hunan University of Science and Engineering,Yongzhou 425199,China)

机构地区：[1]湖南科技学院电子与信息工程学院,湖南永州425100

出　　处：《电脑知识与技术》2021年第27期1-2,共2页Computer Knowledge and Technology

基　　金：湖南省教育厅优秀青年项目(项目编号19B217);国家级大学生创新创业训练项目(项目编号:201910551021X);湖南科技学院计算机科学与技术应用特色学科资助;湖南省课程思政研究项目(课题号:HNKCSZ-2020-0548)。

摘　　要：针对基本灰狼算法因早收敛陷入局部最优的问题,提出了一种通过在解空间均匀分布搜索个体的改进灰狼算法,将其应用在复杂、高维、时变的运动体非线性控制系统中。该方法兼顾了优化算法的全局勘探和局部开采能力,利用MAT⁃LAB对运动体系统近似模型进行了仿真分析,结果表明算法在保证控制系统稳定性的基础上,提高了控制器的动静态性能,具有较好的工程应用前景。Aiming at the problem that the basic Gray Wolf algorithm falls into local optimum due to early convergence,an improved gray wolf algorithm is proposed by searching individuals uniformly in the solution space,which is applied to the complex,high-di⁃mensional,time-varying nonlinear control system of moving body.This method takes into account the global exploration and local mining ability of the optimization algorithm,and uses MATLAB to simulate and analyze the approximate model of the moving body system.The results show that the algorithm improves the dynamic and static performance of the controller on the basis of ensuring the stability of the control system,and has a good engineering application prospect.

关 键 词：运动体控制 灰狼优化算法 MATLAB 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]