基于改进涡流搜索算法的外骨骼迭代学习控制  

Iterative learning control of exoskeleton based on improved vortex search algorithm

作　　者：钟佩思[1] 张大卫 张超[1] 王晓[1] Zhong Peisi;Zhang Dawei;Zhang Chao;Wang Xiao(Advanced Technology Research Center,Shandong University of Science&Technology,Qingdao Shandong 266590,China)

机构地区：[1]山东科技大学先进制造技术研究中心,山东青岛266590

出　　处：《计算机应用研究》2024年第3期873-879,共7页Application Research of Computers

基　　金：国家自然科学基金资助项目(52234005);山东省自然科学基金资助项目(ZR202103070107)。

摘　　要：为提升康复外骨骼机器人的步态跟踪性能,提出一种基于改进涡流搜索算法的迭代学习控制方法。首先针对传统迭代学习控制抗扰性差和控制信息缺失问题,引入PD控制器、自适应遗忘因子、误差过渡曲线和控制信息搜索等策略,改进迭代学习控制律;其次,基于多种策略对涡流搜索算法进行改进,提出了一种改进涡流搜索算法,改进后的算法可优化迭代学习控制的PD参数;最后进行行走实验,将提出的迭代学习控制方法与现有的同类算法进行仿真和数值比较,并测试了扰动情况下的跟踪性能。实验结果表明,所提方法的误差更小,跟踪性能更强。该算法改进了迭代学习控制的不足,具有较强的抗扰性能,保证了使用时的稳定性。In order to improve the gait tracking performance of the rehabilitation exoskeleton robot,this paper proposed an iterative learning control method based on improved vortex search algorithm.Firstly,for the problems of poor immunity and missing control information of traditional iterative learning control,it introduced strategies such as PD controller,adaptive forgetting factor,error transition curve and control information search to improve the iterative learning control law.Secondly,it proposed an improved vortex search algorithm based on multiple strategies,and the algorithm could optimize the PD parameters of iterative learning control.Finally,it simulated and numerically compared the proposed iterative learning control method with existing similar algorithms on walking experiments,and test the tracking performance under perturbation.The experimental results show that the proposed iterative learning control method has smaller error and stronger tracking performance.The algorithm improves the shortcomings of the iterative learning control,has strong anti-interference performance,and ensures stability in use.

关 键 词：迭代学习控制 涡流搜索算法 步态跟踪 外骨骼机器人 轨迹过渡 参数优化 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置]